WO2023035499A1 - Method and system for comprehensive evaluation of resilience of power distribution network - Google Patents

Method and system for comprehensive evaluation of resilience of power distribution network Download PDF

Info

Publication number
WO2023035499A1
WO2023035499A1 PCT/CN2021/142298 CN2021142298W WO2023035499A1 WO 2023035499 A1 WO2023035499 A1 WO 2023035499A1 CN 2021142298 W CN2021142298 W CN 2021142298W WO 2023035499 A1 WO2023035499 A1 WO 2023035499A1
Authority
WO
WIPO (PCT)
Prior art keywords
index
formula
resilience
distribution network
calculation expression
Prior art date
Application number
PCT/CN2021/142298
Other languages
French (fr)
Chinese (zh)
Inventor
魏新迟
何维国
黄晨宏
周健
宋平
时珊珊
张琪祁
郑真
黄鑫
张开宇
Original Assignee
国网上海市电力公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 国网上海市电力公司 filed Critical 国网上海市电力公司
Priority to AU2021335236A priority Critical patent/AU2021335236A1/en
Publication of WO2023035499A1 publication Critical patent/WO2023035499A1/en

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/11—Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Electricity, gas or water supply
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00002—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by monitoring

Definitions

  • the invention relates to the technical field of resilience evaluation of distribution networks, in particular to a comprehensive evaluation method and system for resilience of distribution networks.
  • Resilient grid is one of the main goals of power system development in the next stage. Its huge complexity and high coupling with other systems in resilient cities make it more difficult to accurately evaluate grid resilience. In order to quickly and accurately grasp the current resilience level of the distribution network and provide reliable data support for the subsequent operation decision-making, it is of great research significance to analyze the distribution network resilience assessment method and establish a comprehensive evaluation system.
  • the purpose of the present invention is to overcome the relatively limited evaluation research on the three generalized resilience characteristics of perception, synergy, and learning ability in the above-mentioned prior art.
  • perception there are only some discussions on perception, but most of them focus on combining situational awareness technology Evaluating the specific operational performance of the power grid, and the evaluation of the respective realization effects of the generalized characteristics under the resilience demand are still in the initial stage of development, so as to provide a comprehensive evaluation method and system for the resilience of the distribution network.
  • a method for comprehensively evaluating the resilience of distribution networks comprising the following steps:
  • the distribution network resilience comprehensive evaluation system includes first-level evaluation indicators and second-level evaluation indicators, and each of the first-level evaluation indicators is There are corresponding secondary evaluation indicators;
  • the first-level evaluation indicators of the distribution network resilience comprehensive evaluation system include perception, response, defense, resilience, synergy and learning;
  • the secondary evaluation index corresponding to the perception includes one or more of smart meter coverage, weak node observability, power grid measurement redundancy, average transmission delay, situation visibility and distribution automation system operation index ;
  • the secondary evaluation index corresponding to the synergy includes one or more of distribution line connection rate, coordinated flexible load ratio, distribution network transfer rate and local clean energy consumption rate;
  • the secondary evaluation index corresponding to the learning ability includes one or more of the error expectation between the situation prediction data and the actual data and the ratio of repairable loopholes in the post-disaster perception system;
  • the calculation expression of the smart meter coverage A1 is:
  • n sm represents the number of smart meters in the grid area
  • n m represents the total number of meters in the grid area
  • n wm represents the number of considerable weak nodes, and n w represents the total number of weak nodes;
  • n pm represents the number of considerable nodes
  • n p represents the total number of grid nodes
  • t mi represents the time when meter i collects and measures
  • t ui represents the time when the measurement data of electric meter i is updated to the database
  • n m represents the total number of electric meters in the grid area
  • n is the number of blocks divided by the situation graph
  • N i is the number of nodes in block i, is the arithmetic mean of N i ;
  • the calculation expression of the operation index A6 of the distribution automation system is:
  • a 6 ⁇ aor ⁇ P aor + ⁇ rs ⁇ P rs + ⁇ rc ⁇ P rc + ⁇ fac ⁇ P fac
  • P aor represents the average online rate of distribution automation terminals
  • P rs represents the success rate of remote control
  • P rc represents the correct rate of remote signaling action
  • P fac represents the success rate of feeder automation
  • connection ratio E1 of the distribution line is:
  • n l,H is the total number of 35-110kV high-voltage lines in the area
  • n tl,H is the number of 35-110kV high-voltage connection lines in the area
  • n l,L is the total number of 10(20)kV low-voltage lines in the area
  • the number of lines, n tl,L is the number of 10(20)kV low-voltage connection lines in the area
  • n l, tl are the number of transferable lines within the scope of the distribution network, and n l is the total number of lines.
  • S FL is the peak value of the coordinated flexible load
  • S L,max is the maximum load of the annual network supply
  • P oi is the net electricity received outside the region
  • P oa is the agreed electricity outside the region
  • P co is the on-grid electricity of local clean energy
  • P cg is the power generation of local clean energy
  • T is the total duration of measurement
  • N z,t is the total number of measurements predicted by the sensing system at time t, is the predicted value of the i-th measurement obtained by the perception system at time t, Measure the true value of the corresponding system state for the i-th item at time t;
  • the calculation expression of the repairable vulnerability ratio F2 of the post-disaster awareness system is:
  • n vf is the total number of vulnerabilities found in the perception system after the disaster
  • n vr is the number of repairable vulnerabilities in the perception system after the disaster.
  • the secondary evaluation indicators corresponding to the strain force include voltage transient rate, power flow overrun rate, voltage harmonic distortion rate, frequency deviation rate, power distribution demand rate, N-1 verification pass rate, active power reserve rate One or more of and topological integrity.
  • n p is the number of voltage transients, is the voltage transient variable at the current transient moment of node i
  • V i,max is the transient upper limit voltage of node i
  • V i,min is the transient lower limit voltage of node i
  • V i (t) refers to the current transient moment of node i voltage
  • T is the statistical period
  • the calculation expression of the power flow limit rate B2 is:
  • V 1,i is the effective value of the fundamental wave voltage of node i
  • V k,i is the effective value of the kth harmonic voltage of node i
  • n p is the total number of nodes
  • f is the current frequency of the system
  • f N is the rated frequency
  • ⁇ f th is the frequency deviation limit
  • P a is the total power actually consumed by users of the resilient grid
  • P N is the total rated frequency of users of the resilient grid
  • n t is the total number of substations within the power grid
  • n t(N-1) is the number of substations passing N-1 verification
  • n l is the total number of lines within the power grid
  • n l(N-1) is the number of substations passing N-1 1
  • P r is the active power reserve capacity of the power grid
  • P r.lim is the limit value of the power grid active power reserve capacity
  • the calculation expression of the topological integrity B8 is:
  • the secondary evaluation index corresponding to the defense force includes one or more of performance index, distribution capacity-to-load ratio, and grid failure rate.
  • P o is the original grid capacity before the disaster
  • P d is the grid capacity after taking active defense measures
  • P low is the capacity when the grid performance drops to the lowest level
  • t low is the time when the grid performance drops to the lowest level
  • t d is the time for taking active defense measures
  • S T is the total capacity of distribution network substation equipment
  • S L,max is the maximum load of annual network supply
  • n pe is the total number of power equipment in the grid
  • p fault,i is the failure probability of equipment i.
  • the secondary evaluation index corresponding to the resilience includes one or more of the average power outage time of users, the fault self-healing rate, the success rate of black start, and the average pre-arranged power outage time of the system.
  • t cut is the power outage duration of the i-th fault
  • n ucut,i is the number of users of the i-th fault power outage
  • n u is the total number of users of the power grid
  • n ush,i is the number of self-healing users of the i-th fault
  • n ufault,i is the total number of users affected by the i-th fault
  • n ubs,i is the number of users whose power supply is restored through black start for the i-th fault
  • n ufault,i is the total number of users affected by the i-th fault.
  • t pc,i is the i-th pre-scheduled power outage time
  • n upc,i is the number of pre-scheduled power outage users for the i-th time
  • n u is the total number of power grid users.
  • the setting process of the weight of the secondary evaluation index and the primary evaluation index includes the following steps:
  • Subjective weighting step carry out subjective weighting on each indicator
  • Objective empowerment step objectively empower each indicator
  • M is the total number of weighting methods
  • u m (u m1 ,u m2 ,...,u mN ) is the weight vector of the mth weighting method
  • u mn is the nth weighting method obtained by the mth weighting method
  • the weight of indicators, N is the total number of indicators, d n is the set weight;
  • h(u m ,d) is the relative entropy between the weight vector of the mth weighting method and the set weight
  • the calculation expression of the preference coefficient is:
  • a m is the preference coefficient of the mth weighting method
  • the comprehensive index weight coefficient of each index is calculated according to the preference coefficient, and the calculation expression of the comprehensive index weight coefficient is:
  • w n is the comprehensive index weight coefficient of the nth index.
  • the subjective weighting step includes: using the binomial coefficient method to subjectively weight each index, and the binomial coefficient method includes the following steps:
  • O(x n ) is the average importance ranking of the nth index
  • O m (n) is the importance ranking of the mth index to the nth index
  • x 1 , x 2 ,..., x N are the sorted evaluation indicators
  • u i is the subjective weight of the indicator whose index number is i, Computational results for indicator permutations.
  • the execution of the objective weighting step it also includes: performing normalization processing on each index, and the normalization processing is specifically:
  • x mn is the actual calculated value of the nth index of the mth candidate
  • y mn ′ is the normalized value of the benefit index of the nth index of the mth candidate
  • x n,min is The minimum value of the nth item index
  • x n, max is the maximum value of the nth item index
  • the described candidate scheme is each actual index value obtained by adopting the described index
  • y mn ′′ is the normalized value of the cost index of the nth index of the mth objective weighting scheme.
  • the objective weighting step includes: using the anti-entropy weight method to carry out objective weighting on various indicators, and the calculation process of the anti-entropy weight method includes:
  • y mn is the index normalization value of the nth item index of the mth objective weighting scheme, and M is the total number of alternative schemes;
  • index weight is further determined according to the anti-entropy value, and the calculation expression of the index weight is:
  • u n is the indicator weight of the nth indicator
  • N is the total number of indicators.
  • the objective weighting step includes: adopting the CRITIC (Criteria Importance Through Intercriteria Correlation) method to carry out objective weighting to each index, and the calculation process of the CRITIC method includes:
  • p n is the redundant information entropy of the nth item index
  • y mn is the index normalization value of the nth item index of the mth objective weighting scheme
  • M is the total number of alternative schemes
  • n * th index is the normalized value of the nth index
  • s n is the variation coefficient of the nth index
  • N is the total number of indexes
  • correlation coefficient between the nth item and the n * th item is the index value of the n * th item
  • the covariance between is the coefficient of variation of the n * th item
  • i n is the amount of information of the nth index
  • the indicator weight is determined according to the amount of information, and the calculation expression of the indicator weight is:
  • u n is the index weight of the nth index.
  • the present invention also provides a comprehensive evaluation system for the resilience of distribution networks, including a memory and a processor, the memory stores a computer program, and the processor invokes the computer program to execute the steps of the above-mentioned method.
  • the present invention has the following advantages:
  • the present invention constructs a comprehensive evaluation of the resilience of the distribution network including 27 micro indicators from the six macroscopic resilience measurement dimensions of perception, strain, defense, resilience, coordination, and learning
  • the indicator system especially the setting of the secondary indicators of perception, synergy, and learning ability, is set and proposed for the innovation of the present invention, which can realize the situation awareness, disturbance response, and self-improvement of the distribution network under the demand of resilience to be more comprehensive.
  • comprehensive evaluation the present invention focuses on the six categories of key characteristics of the resilient power grid, focusing on the three functions of distribution network situation awareness, disturbance response and self-improvement capabilities, and can establish a more comprehensive and refined comprehensive evaluation system under the demand for resilience to improve the evaluation Accuracy and reliability of results.
  • the present invention adopts a comprehensive weight optimization method based on relative entropy, combined with the binomial coefficient method, anti-entropy weight method, and correlation weight method to carry out comprehensive weighting on the index system, which can realize subjective and objective weight calculations and improve evaluation results accuracy and reliability.
  • the present invention mainly considers its hardware configuration and operating level and the grasping degree to the system state for the assessment of perception, and the specific indicators of perception have the following technical effects respectively:
  • the smart meter is the basic terminal equipment that realizes the measurement, storage, and calculation of power measurement by the situation awareness system and the two-way communication with the data center. Its coverage reflects the basic perception of the resilient grid. level;
  • weak nodes When high-risk events occur, weak nodes have a greater probability of power performance degradation.
  • the degree of grasp of the real-time status of weak nodes can reflect the ability of the resilient power grid perception system to deal with potential disasters, remove hidden dangers in time, and prevent further expansion of faults;
  • Grid measurement redundancy Different from the observability of weak nodes, which mainly reflects the response ability of the power grid sensing system under disaster conditions, the power grid measurement redundancy reflects whether the sensing system can fully grasp the operating status of the power grid and Assist other systems to make decisions, which can be used as a supplement to the observability of weak nodes;
  • the average transmission delay is defined as the average time required for the resilient grid operation data to be transmitted in the sensing system and updated to the database, which reflects the real-time requirements of the resilient grid sensing system;
  • Situational visibility reflects the visualization level of the perception system. Convenient and clear situational information is helpful for operation managers to quickly identify and analyze power events and make corresponding decisions when responding to disasters; evaluate the situational map through the uniformity of node distribution Visualization level, the smaller the uniformity of node distribution, the more uniform the distribution of sample data and the higher the degree of visualization;
  • Operation index of distribution automation system as a collection of power grid data collection and monitoring system, geographic information system, demand side management and other systems, distribution automation system integrates functions such as power data monitoring analysis and remote control; it is different from previous system configuration indicators , the operation index of the distribution automation system mainly reflects the perceived results of the decision-making execution accuracy and execution efficiency of the resilient power grid, which is a real-time dynamic index.
  • the synergy index set by the present invention represents the ability of the resilient power grid to use internal and external resources reasonably and efficiently, and jointly concentrate forces to resist disturbance events.
  • the synergy-related indicators can be used to improve and reflect the internal and external defense resources and multi-dimensional system information of the distribution network and other control capabilities; the specific indicators of synergy have the following technical effects:
  • Distribution line contact rate As the most intuitive and basic contact method, the direct connection of distribution lines provides flexibility for the dispatching and cooperation of physical systems inside and outside the region, and the increase of its coupling elements also provides higher measurement redundancy;
  • Coordinated flexible load ratio As an important component of the active distribution network, flexible loads are responsible for maintaining power balance and coordinated recovery from disasters; the coordinated flexible load ratio determines the peak capacity of the resilient grid’s collaborative anti-disturbance, reflecting the flexible load Synergies for grid management
  • Distribution network transfer rate line transfer can effectively reduce the number of lost loads in the resilient power grid under partial fault conditions, and exert a greater degree of coordinated disaster response capabilities of the system. It also provides a basis for distribution network risk situation assessment and decision-making effect simulation Greater flexibility;
  • the amount of clean energy consumption can comprehensively reflect the synergistic effect of the resilient grid, which is different from the coordinated flexible load ratio, which dynamically represents the coordinated balance level of power and electricity inside and outside the region and the flexible anti-disturbance capability.
  • the learning power set by the present invention serves as a common support for the rest of the features, which represents the ability of the resilient power grid to self-correct and improve from historical experience and combine new technologies to improve innovation, and can be used to reflect the ability of the resilient distribution network to self-correct and continuously improve ;
  • the specific indicators of learning ability have the following technical effects respectively:
  • the proportion of vulnerabilities that can be repaired by the post-disaster perception system directly reflects the vulnerability identification, error correction and self-learning capabilities of the resilient grid system.
  • Fig. 1 is the schematic flow chart of a kind of binomial coefficient method provided in the embodiment of the present invention
  • Fig. 2 is a schematic flow chart of an anti-entropy weight method provided in an embodiment of the present invention
  • Fig. 3 is a schematic flow chart of a CRITIC method provided in an embodiment of the present invention.
  • FIG. 4 is a schematic diagram of a comprehensive weight optimization process based on relative entropy provided in an embodiment of the present invention
  • Fig. 5 is a schematic flow diagram of a comprehensive resilience assessment process of a distribution network provided in an embodiment of the present invention.
  • This embodiment provides a method for comprehensively evaluating resilience of a distribution network, including the following steps:
  • distribution network resilience comprehensive evaluation system includes first-level evaluation indicators and second-level evaluation indicators, and each first-level evaluation index has a corresponding Secondary evaluation index;
  • the first-level evaluation indicators of the distribution network resilience comprehensive evaluation system include perception, response, defense, resilience, coordination and learning;
  • the secondary evaluation indicators corresponding to perception include one or more of smart meter coverage, weak node observability, power grid measurement redundancy, average transmission delay, situation visibility and distribution automation system operation indicators; , smart meter coverage, weak node observability and power grid measurement redundancy are used to reflect the perception level of the edge side of the distribution network; average transmission delay, situation visibility and distribution automation system operation indicators are used to reflect the distribution network control center perception level;
  • the secondary evaluation indicators corresponding to strain stress include voltage transient rate, power flow exceeding rate, voltage harmonic distortion rate, frequency deviation rate, power distribution demand rate, N-1 verification pass rate, active power reserve rate and topology integrity One or more of them; Among them, the voltage transient rate, the power flow limit rate, the voltage harmonic distortion rate and the frequency deviation rate are used to reflect the electrical quantity parameter indicators of the distribution network operation process; the distribution demand rate, N-1 verification Through rate, active power reserve rate and topology integrity are used to reflect the macro planning indicators of distribution network;
  • the secondary evaluation indicators corresponding to the defense force include one or more of performance index, distribution capacity load ratio and grid failure rate;
  • the secondary evaluation indicators corresponding to the resilience include one or more of the user average power outage time, fault self-healing rate, black start success rate, and system average pre-scheduled power outage time; among them, the system’s average pre-scheduled power outage time is used to reflect the power distribution
  • the pre-accident warning and maintenance level of the distribution network; the average power outage time of users, the fault self-healing rate and the black start success rate are used to reflect the post-accident recovery level of the distribution network;
  • the secondary evaluation indicators corresponding to synergy include one or more of distribution line connection rate, coordinated flexible load ratio, distribution network transfer rate and local clean energy consumption rate; among them, distribution line connection rate and distribution network
  • the transfer rate is used to reflect the physical line coordination level of the distribution network; the coordinated flexible load ratio and the local clean energy consumption rate are used to reflect the flexible resource coordination level of the distribution network.
  • the secondary evaluation indicators corresponding to the learning ability include one or more of the error expectation between the situation prediction data and the actual data and the ratio of repairable loopholes in the post-disaster perception system;
  • the number of secondary evaluation indicators corresponding to the above-mentioned perception, strain, defense, resilience, synergy and learning ability is not limited, and can be arbitrarily selected from the above-mentioned secondary evaluation indicators, preferably using the one provided by this embodiment. For all the corresponding secondary evaluation indicators, an optimal implementation manner will be described in detail below.
  • the actual resilience level of the distribution network is comprehensively evaluated from the six dimensions of perception, strain, defense, resilience, coordination, and learning, and the power distribution system is established.
  • the comprehensive evaluation index system of network toughness is shown in Table 1.
  • the evaluation of perception mainly considers its hardware configuration and operation level and the degree of grasp of the system state. Algorithmic efficiency, risk situation prediction, and other related indicators of the resilience level of the power grid that are difficult to evaluate directly will be indirectly reflected by subsequent indicators of other dimensions.
  • the smart meter is the basic terminal equipment that realizes the measurement, storage and calculation of the power measurement of the situation awareness system and the two-way communication with the data center. Its coverage reflects the basic perception level of the resilient grid.
  • the calculation formula is as follows :
  • n sm represents the number of smart meters in the grid area
  • n m represents the total number of meters in the grid area
  • the calculation formula of the load-system short-circuit capacity ratio is as follows:
  • E Pi and Z Pi are the Thevenin equivalent circuit parameters of the power grid at the node
  • U Li and Z Li are the Thevenin equivalent circuit parameters of the load at the node.
  • the node is considered to be a weak node.
  • a node is substantial when its voltage phasor can be measured directly or calculated.
  • the formula for calculating the observability of weak nodes is as follows:
  • n wm represents the number of considerable weak nodes
  • n w represents the total number of weak nodes
  • the grid measurement redundancy reflects whether the sensing system can fully grasp the operating status of the grid and assist other systems to make decisions under the normal state of the resilient grid. Can be used as a supplement to the observability of weak nodes.
  • the grid measurement redundancy calculation formula is as follows:
  • n pm represents the number of considerable nodes
  • n p represents the total number of grid nodes
  • the average transmission delay is defined as the average time required for the resilient grid operation data to be transmitted in the sensing system and updated to the database, reflecting the real-time requirements of the resilient grid sensing system. Calculated as follows:
  • t mi represents the time when the meter i collects and measures
  • t ui represents the time when the measurement data of the electric meter i is updated to the database.
  • n is the number of blocks divided by the situation graph
  • N i is the number of nodes in block i
  • the distribution automation system integrates functions such as power data monitoring, analysis, and remote control.
  • the distribution automation system operation indicators mainly reflect the perception results of the decision-making execution accuracy and execution efficiency of the resilient power grid. They are real-time dynamic indicators, including the average online rate of distribution automation terminals, remote control success rate, The four sub-items are the correct rate of remote signaling action and the success rate of feeder automation.
  • a 6 ⁇ aor ⁇ P aor + ⁇ rs ⁇ P rs + ⁇ rc ⁇ P rc + ⁇ fac ⁇ P fac
  • P aor represents the average online rate of distribution automation terminals
  • P rs represents the success rate of remote control
  • P rc represents the correct rate of remote signaling action
  • P fac represents the success rate of feeder automation
  • this embodiment provides the specific calculation formula of the optimal weight configuration of the distribution automation system operation index A6 as follows:
  • a 6 0.25 ⁇ P aor +0.25 ⁇ P rs +0.2 ⁇ P rc +0.3 ⁇ P fac (7)
  • P aor represents the average online rate of distribution automation terminals
  • P rs represents the success rate of remote control
  • P rc represents the correct rate of remote signaling actions
  • P fac represents the success rate of feeder automation.
  • the coefficients in the distribution automation system operation index A6 can be adjusted according to the actual situation and are not specifically limited. This embodiment provides the optimal coefficient of the distribution automation system operation index A6 .
  • Resilience reflects the ability of a resilient grid to resist disturbances, maintain its own performance, and formulate risk plans before extreme events occur. Resilience-related indicators can be used to reflect the reliability, efficiency, risk prediction and pre-accident deployment effectiveness of the power grid in daily operation decisions.
  • the voltage transient rate is mainly used to reflect the frequency and magnitude of voltage sags (or swells) in the normal operation of the power grid.
  • the lower voltage transient rate reflects the strong transient stability and anti-interference ability of the system, and also reflects the It improves the monitoring and early warning capabilities of the power grid for transient disturbances.
  • the calculation formula of voltage transient rate is as follows:
  • n p is the number of voltage transients, is the voltage transient variable at the current transient moment of node i
  • V i,max is the transient upper limit voltage of node i
  • V i,min is the transient lower limit voltage of node i
  • V i (t) refers to the current transient moment of node i
  • the voltage, T is the statistical period.
  • V 1,i is the effective value of the fundamental wave voltage of node i
  • V k,i is the effective value of the kth harmonic voltage of node i
  • n p is the total number of nodes.
  • the frequency deviation rate belongs to the steady-state power index of the power grid, which reflects the active safety performance of the system. Technologies such as power flow monitoring and load forecasting and deployment are conducive to reducing the frequency deviation of the resilient power grid.
  • the calculation formula of frequency deviation rate is as follows:
  • f is the current frequency of the system
  • f N is the rated frequency
  • ⁇ f th is the frequency deviation limit of 0.2 Hz.
  • the power distribution demand rate is defined as the ratio of the actual operating power of the user to the rated power in the resilient grid. This value reflects the rationality and economy of power resource allocation in the resilient grid, and also reflects the grid's ability in flexible load scheduling and resource allocation. .
  • the formula for calculating the power distribution demand rate is as follows:
  • P a is the actual total power consumption of the resilient grid users
  • P N is the total rated frequency of the resilient grid users
  • the N-1 pass rate includes the N-1 pass rate of substations and transmission lines within the power grid. As the most intuitive indicator to characterize the reliability and risk warning capabilities of the power grid, it also reflects the perceived risk situation of the resilient power grid and Ability to simulate anticipated accidents.
  • N-1 verification pass rate B 6 The calculation expression of N-1 verification pass rate B 6 is:
  • n t is the total number of substations within the power grid
  • n t(N-1) is the number of substations passing N-1 verification
  • n l is the total number of lines within the power grid
  • n l(N-1) is the number of substations passing N-1 1
  • this embodiment provides the calculation formula for the optimal weight configuration of the N-1 verification pass rate as follows:
  • n t is the total number of substations within the power grid
  • n t(N-1) is the number of substations passing N-1 verification
  • n l is the total number of lines within the power grid
  • n l(N-1) is the number of substations passing N-1 1 The number of lines to check.
  • the active power reserve rate pays more attention to the pre-arrangement of emergency resources.
  • An appropriate amount of active power reserve is conducive to maintaining system performance in risky accidents, reducing losses caused by disasters, and meeting the economy of normal system operation.
  • the specific calculation formula is as follows:
  • P r is the active power reserve capacity of the grid
  • P r.lim is the limit value of the active power reserve capacity of the power grid, which is generally taken as 0.1 times the maximum load of the system.
  • topological integrity greatly affects its vulnerability to disasters. Reducing the number of outage lines and the outage time is conducive to building a stronger and more reliable resilient power grid.
  • the calculation formula of topological integrity is as follows:
  • Defensive power focuses on the ability of the resilient power grid to use internal and external defense resources to actively resist disaster damage and reduce the overall impact of events during the occurrence of extreme events.
  • the defense-related indicators can be used to reflect the operational efficiency of the power grid under extreme conditions and the response rate under variable conditions.
  • the availability performance curve describes the dynamic changes of the resilient grid during extreme events, and the grid capacity is selected as the performance index.
  • the performance index is defined as the product of factors such as active defense speed and active defense effect. This index simultaneously reflects the real-time response ability of perception during the disaster occurrence process, the ability to predict the development of disaster situation, and the ability to evaluate defense resources.
  • the specific calculation formula is as follows:
  • P o is the original grid capacity before the disaster
  • P d is the grid capacity after taking active defense measures
  • P low is the capacity when the grid performance drops to the lowest level
  • t low is the time when the grid performance drops to the lowest level
  • t d is the time to take active defense measures.
  • the distribution network capacity-load ratio is defined as the ratio of the total capacity of substation equipment in the distribution network area to the annual maximum load.
  • a certain transformer reserve capacity is conducive to improving the adaptability of the power grid in the process of disasters and bringing greater flexibility to the deployment of defense resources; at the same time, an excessive capacity-to-load ratio not only increases the investment cost and construction period of the resilient power grid, It also reduces the economics of grid operation. How to reduce the capacity-load ratio of the distribution network while satisfying reliability depends on more accurate load forecasting and operation control technology of the distribution network.
  • the calculation formula of distribution network capacity load ratio is as follows:
  • S T is the total capacity of distribution network substation equipment
  • S L,max is the maximum load of annual network supply.
  • n pe is the total number of power equipment in the power grid
  • p fault,i is the failure probability of equipment i, which can be obtained from historical data combined with situation prediction technology.
  • Resilience considers the emergency guarantee and gradual restoration of power grid performance after an accident, and timeliness is the most important consideration for resilience.
  • Resilience-related indicators can be used to reflect the power grid's capabilities in fault location, maintenance and repair, remote control, and decision-making simulation evaluation.
  • Power outage time is the most intuitive indicator to reflect the resilience level of the resilient grid after a disturbance. Technologies such as fault location, fault data recording, and disturbance factor analysis can effectively reduce the average power outage time.
  • the formula for calculating the average outage time of users is as follows:
  • t cut is the power outage duration of the i-th fault
  • n ucut,i is the number of users in the i-th fault outage
  • n u is the total number of users in the power grid.
  • Fault self-healing is mainly reflected in the self-healing ability of the power grid in the face of small disturbances or the initial stage of extreme events, and its cycle includes three levels of monitoring and early warning, diagnosis and analysis, and automatic repair.
  • a high-level resilient power grid can give an alarm and diagnose its triggering factors when the fault is still in the "potential" stage, and use remote control to achieve fault self-healing attempts.
  • the formula for calculating the fault self-healing rate is as follows:
  • n ush,i is the number of self-healing users of the i-th fault
  • n ufault,i is the total number of users affected by the i-th fault
  • Black start is a key measure for emergency protection after extreme events.
  • the formulation of its optimal scheme largely depends on the estimation of the system state under the fault set by the distribution network and the operation effect of the scheme in the simulation environment such as the twin system.
  • the black start success rate can effectively reflect the initial post-disaster recovery ability of the resilient grid, and its calculation formula is as follows:
  • n ubs,i is the number of users whose power supply is restored through black start for the i-th fault.
  • Pre-arranged power outages refer to the planned outage maintenance or capacity expansion of relevant areas by the power department, which is suitable for delayable fault repairs that do not cause damage in a short period of time. Pre-blackout is mainly judged based on indicators such as failure rate and failure rate.
  • the formula for calculating the average pre-scheduled outage time of the system is as follows:
  • t pc,i is the i-th pre-scheduled power outage time
  • n upc,i is the number of i-th pre-scheduled power outage users.
  • Synergy represents the ability of the resilient grid to rationally and efficiently utilize internal and external resources, and jointly concentrate forces to resist disturbance events. Like perception, it serves as a basic feature for the three core features.
  • the indicators related to synergy can be used to improve and reflect the ability of the distribution network to control internal and external defense resources and multi-dimensional system information.
  • the direct connection of distribution lines provides flexibility for the scheduling and cooperation of physical systems inside and outside the region, and the increase of its coupling elements also provides higher measurement redundancy for the distribution network .
  • n l,H is the total number of 35-110kV high-voltage lines in the area
  • n tl,H is the number of 35-110kV high-voltage connection lines in the area
  • n l,L is the total number of 10(20)kV low-voltage lines in the area
  • the number of lines, n tl,L is the number of 10(20)kV low-voltage connection lines in the area
  • this embodiment provides the calculation formula for the optimal weight configuration of the distribution network connection ratio as follows:
  • n l,H is the total number of 35-110kV high-voltage lines in the area
  • n tl,H is the number of 35-110kV high-voltage connection lines in the area
  • n l,L is the total number of 10(20)kV low-voltage lines in the area
  • the number of lines, n tl,L is the number of 10(20)kV low-voltage contact lines in the area.
  • the coefficients in the formula for calculating the connection ratio of the distribution network can be adjusted according to actual conditions, and are not specifically limited. This embodiment provides the optimal coefficient of the formula for calculating the connection ratio of the distribution network.
  • Line transfer can effectively reduce the number of lost loads in the case of partial faults in resilient power grids, give play to a greater degree of coordinated disaster response capabilities of the system, and also provide greater flexibility for distribution network risk situation assessment and decision-making effect simulation.
  • the formula for calculating the distribution network transfer rate is as follows:
  • S FL is the peak value of adjustable flexible load.
  • n l, tl are the number of transferable lines within the distribution network range.
  • the amount of clean energy consumed can comprehensively reflect the synergistic effect of the resilient power grid. Different from the proportion of flexible loads that can be coordinated, it dynamically represents the coordinated balance level of power and electricity inside and outside the region and the flexible anti-disturbance capability.
  • the specific calculation formula is as follows:
  • P oi is the net electricity received outside the region
  • P oa is the agreed electricity outside the region
  • P co is the on-grid electricity of local clean energy
  • P cg is the power generation of local clean energy
  • Learning ability represents the ability of the resilient grid to self-correct and improve from historical experience and combine new technologies to promote innovation.
  • Indicators related to learning ability can be used to reflect the ability of autonomous error correction and continuous improvement of resilient distribution network.
  • the error between the forecast data and the actual data of the resilient power grid can be obtained.
  • the error expectation and change trend can effectively reflect the self-correction and self-improvement capabilities of the distribution network.
  • T is the total duration of measurement
  • N z,t is the total number of measurements predicted by the sensing system at time t
  • N z,t is the predicted value of the i-th measurement obtained by the perception system at time t
  • the proportion of vulnerabilities that can be repaired by the post-disaster perception system directly reflects the vulnerability identification, error correction and self-learning capabilities of the resilient grid system.
  • the calculation formula is as follows:
  • n vf is the total number of vulnerabilities found in the perception system after the disaster
  • n vr is the number of repairable vulnerabilities in the perception system after the disaster.
  • the weighting method can be divided into subjective weighting method and objective weighting method according to its basis, and there is a possibility of one-sided evaluation in the single use of any type of method, so the present invention utilizes the comprehensive weighting optimization method based on relative entropy to optimize the binomial
  • the subjective and objective weights obtained by the coefficient method, the anti-entropy weight method and the CRITIC method realize the weight calculation of the comprehensive evaluation of power grid resilience.
  • the subjective weighting method of this embodiment adopts the binomial coefficient method.
  • the binomial coefficient method is easier to calculate, and comprehensively considers the opinions of all parties to avoid ignoring minority opinions.
  • the flow chart of the binomial coefficient method is shown in Figure 1, and the weighting steps are as follows:
  • S104 sort the index set symmetrically and number each index again from left to right, denoted as i.
  • the binomial coefficients can be determined according to the serial number results to calculate the subjective weight of each indicator, the formula is as follows:
  • u i is the subjective weight of the indicator whose index number is i, Computational results for indicator permutations.
  • the subjective weighting method relies on the subjective cognition of evaluation experts on the evaluation index set, and there is a possibility of random deviation and one-sidedness. It must be used in combination with the objective weighting method that relies on objective data.
  • the objective weighting method selected in the present invention is the anti-entropy weighting method with the CRITIC Act.
  • the anti-entropy weight method is based on the concept of information entropy, which can effectively evaluate the quality of information provided by indicators for decision-making, and avoids the extreme situation of too small weighting in the entropy weight method.
  • the CRITIC method which is suitable for high correlation index weighting, is supplemented to improve the effectiveness of objective weighting.
  • x mn represents the actual calculated value of the nth indicator of the mth scheme. Since the actual calculation value range of each micro-indicator is quite different, and there are different dimensions, it is not conducive to determine its objective weight. Therefore, each indicator is first normalized, and the specific formula is as follows:
  • Benefit-type indicators that is, the index value is positively correlated with the evaluated ability.
  • Cost-type indicators that is, the indicator value is negatively correlated with the assessed ability.
  • each index value y mn is a dimensionless constant with a range of 0 to 1, and the larger the index value, the stronger the ability to reflect the scheme.
  • the specific weight calculation process of the anti-entropy weight method and the CRITIC method will be introduced below.
  • n * th is the normalized value of the nth index
  • s n is the variation coefficient of the nth index
  • N is the total number of indexes
  • s n is the variation coefficient of the nth index
  • N is the total number of indexes
  • s n is the variation coefficient of the nth index
  • N is the total number of indexes
  • index value of the n * th item is the index value y n
  • the covariance between is the coefficient of variation of the n * th term.
  • the specific optimization model can refer to the prior art, such as the following model formula:
  • S3 Calculate the subjective weight and objective weight of each first-level evaluation index and second-level evaluation index
  • This embodiment also provides a system for comprehensively evaluating resilience of a distribution network, including a memory and a processor, the memory stores a computer program, and the processor invokes the computer program to execute the method for comprehensively evaluating resilience of a distribution network as described above A step of.

Abstract

The present invention relates to a method and system for comprehensively evaluating the resilience of a power distribution network. The method comprises: obtaining parameters of a power distribution network, and performing an evaluation according to a preset power distribution network resilience comprehensive evaluation system, wherein the power distribution network resilience comprehensive evaluation system comprises first-level evaluation indices and second-level evaluation indices, and each first-level evaluation index is provided with a corresponding second-level evaluation index; the first-level evaluation indexes comprises perceptibility, adaptability, defense capabilities, restoration capabilities, synergistic capabilities and learning capabilities, and on the basis of an evaluation result of each second-level evaluation index, carrying out a comprehensive calculation according to the weight of each second-level evaluation index and the weight of each first-level evaluation index to obtain a comprehensive evaluation result for the resilience of the power distribution network. Compared to the prior art, the present invention focuses on the three functions of distribution network situation awareness, disturbance response and self improvement capabilities with regards to six categories of key features of a resilient power grid, which can establish a more comprehensive and refined comprehensive evaluation system under resilience requirements, and improve the accuracy and reliability of the evaluation result.

Description

一种配电网的韧性综合评估方法和系统A method and system for comprehensive evaluation of distribution network resilience 技术领域technical field
本发明涉及配电网韧性评估技术领域，尤其是涉及一种配电网的韧性综合评估方法和系统。The invention relates to the technical field of resilience evaluation of distribution networks, in particular to a comprehensive evaluation method and system for resilience of distribution networks.
背景技术Background technique
当下，传统化石能源的逐步枯竭和全球环境形势的日益严峻，使得大力发展包括风电、光伏在内的可再生能源已迫在眉睫；亟需建设一个更加坚强、更加智能化的电力系统，尤其是提升其应对小概率高风险事件的能力，“韧性电网”的概念就在此背景下应运而生。At present, the gradual depletion of traditional fossil energy and the increasingly severe global environmental situation make it urgent to vigorously develop renewable energy including wind power and photovoltaics; it is urgent to build a stronger and more intelligent power system, especially to upgrade its The ability to deal with low-probability and high-risk events, the concept of "resilient power grid" came into being in this context.
针对韧性电网这一理念，国外学者已进行了相关理论方法以及所需关键技术的初步研究，而国内学者结合我国电力系统发展现状和特色，也创新性地提出了韧性电网内涵和概念，其中包括指出了韧性电网的6个关键特征：“感知力”、“应变力”、“防御力”、“恢复力”、“协同力”、“学习力”。现有关于电网韧性评估的研究主要集中于狭义韧性的特征，也即分别表征系统在突发事故前、中、后期应对能力的应变力、防御力和恢复力。文献“地震灾害下海岛综合能源系统韧性评估方法研究”(李雪,孙霆锴,侯恺,姜涛,陈厚合,李国庆,贾宏杰.中国电机工程学报,2020,40(17):5476-5493)提出了鲁棒性、快速性和冗余性三个指标评估海岛综合能源系统；文献“系统安全韧性的塑造与评估建模”(黄浪，吴超，王秉.中国安全生产科学技术,2016,12(12):15-21)从系统构成元素、关联关系和韧性功能三个维度构建了安全韧性量化评估模型；文献“面向突发事件的电网韧性能力评价及构建方法”(肖智文,王国庆,朱建明,等.系统工程理论与实践,2019,39(10):26372645)利用性能曲线量化评估了电网在事故全周期中的韧性能力。而考虑感知力、协同力、学习力三大广义韧性特征的评估研究相对有限，目前仅有一些针对感知力的讨论，但多数着力于结合态势感知技术评估电网的特定运行性能，对韧性需求下广义特征的各自实现效果评价仍处于初步发展阶段。For the concept of resilient grid, foreign scholars have carried out preliminary research on relevant theoretical methods and key technologies required, while domestic scholars have also innovatively proposed the connotation and concept of resilient grid in combination with the development status and characteristics of my country's power system, including Six key characteristics of the resilient grid are pointed out: "perception", "response", "defense", "resilience", "synergy", and "learning". Existing research on the evaluation of power grid resilience mainly focuses on the characteristics of resilience in the narrow sense, that is, the resilience, defense, and resilience that characterize the ability of the system to respond to emergencies before, during, and later. The paper "Research on the Resilience Evaluation Method of Island Comprehensive Energy System under Earthquake Disasters" (Li Xue, Sun Tingkai, Hou Kai, Jiang Tao, Chen Houhe, Li Guoqing, Jia Hongjie. Proceedings of the Chinese Society for Electrical Engineering, 2020, 40(17): 5476-5493) proposed Three indicators of robustness, rapidity and redundancy evaluate island comprehensive energy systems; literature "Shaping and Evaluation Modeling of System Security Resilience" (Huang Lang, Wu Chao, Wang Bing. China Safety Production Science and Technology, 2016,12 (12): 15-21) A security resilience quantitative evaluation model was constructed from three dimensions of system components, correlations and resilience functions; the literature "Evaluation and construction method of power grid resilience facing emergencies" (Xiao Zhiwen, Wang Guoqing, Zhu Jianming, et al. System Engineering Theory and Practice, 2019, 39(10): 26372645) used the performance curve to quantitatively evaluate the resilience of the power grid in the full cycle of accidents. However, evaluation studies considering the three generalized resilience characteristics of perception, synergy, and learning ability are relatively limited. At present, there are only some discussions on perception, but most of them focus on evaluating the specific operation performance of power grids combined with situational awareness technology. Evaluation of the respective implementation effects of generalized features is still in the initial stage of development.
韧性电网作为下阶段电力系统发展的主要目标之一，自身的庞大复杂再加上与韧性城市下其他系统的高度耦合，使得精确评估电网韧性能力变得更为困难。为了快速准确掌握配电网当前韧性水平，为后续运行决策的制定提供可靠数据支撑，分析配网韧性评估方法并建立一套综合评价体系具有重要研究意义。Resilient grid is one of the main goals of power system development in the next stage. Its huge complexity and high coupling with other systems in resilient cities make it more difficult to accurately evaluate grid resilience. In order to quickly and accurately grasp the current resilience level of the distribution network and provide reliable data support for the subsequent operation decision-making, it is of great research significance to analyze the distribution network resilience assessment method and establish a comprehensive evaluation system.
发明内容Contents of the invention
本发明的目的就是为了克服上述现有技术存在考虑感知力、协同力、学习力三大广义韧性特征的评估研究相对有限，目前仅有一些针对感知力的讨论，但多数着力于结合态势感知技术评估电网的特定运行性能，对韧性需求下广义特征的各自实现效果评价仍处于初步发展阶的缺陷而提供一种配电网的韧性综合评估方法和系统。The purpose of the present invention is to overcome the relatively limited evaluation research on the three generalized resilience characteristics of perception, synergy, and learning ability in the above-mentioned prior art. At present, there are only some discussions on perception, but most of them focus on combining situational awareness technology Evaluating the specific operational performance of the power grid, and the evaluation of the respective realization effects of the generalized characteristics under the resilience demand are still in the initial stage of development, so as to provide a comprehensive evaluation method and system for the resilience of the distribution network.
本发明的目的可以通过以下技术方案来实现：The purpose of the present invention can be achieved through the following technical solutions:
一种配电网的韧性综合评估方法，包括以下步骤：A method for comprehensively evaluating the resilience of distribution networks, comprising the following steps:
获取配电网参数，根据预设的配电网韧性综合评价体系，进行评估；所述配电网韧性综合评价体系包括一级评价指标和二级评价指标，每个所述一级评价指标均设有对应的二级评价指标；Obtain distribution network parameters, and evaluate according to the preset distribution network resilience comprehensive evaluation system; the distribution network resilience comprehensive evaluation system includes first-level evaluation indicators and second-level evaluation indicators, and each of the first-level evaluation indicators is There are corresponding secondary evaluation indicators;
所述配电网韧性综合评价体系的一级评价指标包括感知力、应变力、防御力、恢复力、协同力和学习力；The first-level evaluation indicators of the distribution network resilience comprehensive evaluation system include perception, response, defense, resilience, synergy and learning;
所述感知力对应的二级评价指标包括智能电表覆盖率、薄弱节点可观度、电网量测冗余度、平均传输延时、态势可视度和配电自动化系统运行指标中的一个或多个；The secondary evaluation index corresponding to the perception includes one or more of smart meter coverage, weak node observability, power grid measurement redundancy, average transmission delay, situation visibility and distribution automation system operation index ;
所述协同力对应的二级评价指标包括配电线路联络率、可协调柔性负荷比例、配网转供率和本地清洁能源消纳率中的一个或多个；The secondary evaluation index corresponding to the synergy includes one or more of distribution line connection rate, coordinated flexible load ratio, distribution network transfer rate and local clean energy consumption rate;
所述学习力对应的二级评价指标包括态势预测数据与实际数据误差期望和灾后感知系统可修复漏洞比例中的一个或多个；The secondary evaluation index corresponding to the learning ability includes one or more of the error expectation between the situation prediction data and the actual data and the ratio of repairable loopholes in the post-disaster perception system;
基于各个二级评价指标的评估结果，根据预设的各个二级评价指标的权重以及各个一级评价指标的权重，进行综合计算，获取配电网的韧性综合评估结果。Based on the evaluation results of each secondary evaluation index, according to the preset weight of each secondary evaluation index and the weight of each first-level evaluation index, a comprehensive calculation is performed to obtain the comprehensive evaluation result of the resilience of the distribution network.
进一步地，所述感知力对应的二级评价指标中，所述智能电表覆盖率A 1的计算表达式为： Further, in the secondary evaluation index corresponding to the perception, the calculation expression of the smart meter coverage A1 is:
Figure PCTCN2021142298-appb-000001
Figure PCTCN2021142298-appb-000001
式中，n sm表示电网区域内的智能电表数量，n m表示电网区域内的总电表数； In the formula, n sm represents the number of smart meters in the grid area, and n m represents the total number of meters in the grid area;
所述薄弱节点可观度A 2的计算表达式为： The calculation expression of the observability A2 of the weak node is:
Figure PCTCN2021142298-appb-000002
Figure PCTCN2021142298-appb-000002
式中，n wm表示可观薄弱节点的数量，n w表示薄弱节点总数； In the formula, n wm represents the number of considerable weak nodes, and n w represents the total number of weak nodes;
所述电网量测冗余度A 3的计算表达式为： The calculation expression of the grid measurement redundancy A3 is:
Figure PCTCN2021142298-appb-000003
Figure PCTCN2021142298-appb-000003
式中，n pm表示可观节点的数量，n p表示电网节点总数。 In the formula, n pm represents the number of considerable nodes, and n p represents the total number of grid nodes.
进一步地，所述感知力对应的二级评价指标中，所述平均传输延时A 4的计算表达式为： Further, in the secondary evaluation index corresponding to the perception, the calculation expression of the average transmission delay A4 is:
Figure PCTCN2021142298-appb-000004
Figure PCTCN2021142298-appb-000004
式中，t mi表示电表i采集量测量的时刻，t ui表示电表i量测数据更新至数据库的时刻，n m表示电网区域内的总电表数； In the formula, t mi represents the time when meter i collects and measures, t ui represents the time when the measurement data of electric meter i is updated to the database, and n m represents the total number of electric meters in the grid area;
所述态势可视度A 5的计算表达式为： The calculation expression of the situational visibility A5 is:
Figure PCTCN2021142298-appb-000005
Figure PCTCN2021142298-appb-000005
式中，n为态势图划分的区块数量，N i为区块i中的节点数量，
Figure PCTCN2021142298-appb-000006
为N i的算术平均值； In the formula, n is the number of blocks divided by the situation graph, N i is the number of nodes in block i,
Figure PCTCN2021142298-appb-000006
is the arithmetic mean of N i ;
所述配电自动化系统运行指标A 6的计算表达式为： The calculation expression of the operation index A6 of the distribution automation system is:
A 6＝α aor×P aor+α rs×P rs+α rc×P rc+α fac×P fac A 6 ＝α aor ×P aor +α rs ×P rs +α rc ×P rc +α fac ×P fac
式中，P aor表示配电自动化终端平均在线率，P rs表示遥控成功率，P rc表示遥信动作正确率，P fac表示馈线自动化成功率，α aor、α rs、α rc、α fac为各项指标对应权重，α aor+α rs+α rc+α fac＝1。 In the formula, P aor represents the average online rate of distribution automation terminals, P rs represents the success rate of remote control, P rc represents the correct rate of remote signaling action, P fac represents the success rate of feeder automation, α aor , α rs , α rc , and α fac are Each index corresponds to the weight, α aor + α rs + α rc + α fac =1.
进一步地，所述协同力对应的二级评价指标中，所述配电线路联络率E 1的计算表达式为： Further, in the secondary evaluation index corresponding to the synergy force, the calculation expression of the connection ratio E1 of the distribution line is:
Figure PCTCN2021142298-appb-000007
Figure PCTCN2021142298-appb-000007
式中，n l,H为区域中35～110kV高压线路总条数，n tl,H为区域中35～110kV高压联络线路条数，n l,L为区域中10(20)kV低压线路总条数，n tl,L为区域中10(20)kV低压联络线路条数，α l,H、α l,L分别为高压线路和低压线路指标权重，α l,H+α l,L＝1； In the formula, n l,H is the total number of 35-110kV high-voltage lines in the area, n tl,H is the number of 35-110kV high-voltage connection lines in the area, n l,L is the total number of 10(20)kV low-voltage lines in the area The number of lines, n tl,L is the number of 10(20)kV low-voltage connection lines in the area, α l,H , α l,L are the index weights of high-voltage lines and low-voltage lines respectively, α l,H +α l,L = 1;
所述配网转供率E 2的计算表达式为： The calculation expression of the distribution network transfer rate E2 is:
Figure PCTCN2021142298-appb-000008
Figure PCTCN2021142298-appb-000008
式中，n l,tl为配网范围内可转供线路条数，n l为线路总条数。 In the formula, n l, tl are the number of transferable lines within the scope of the distribution network, and n l is the total number of lines.
进一步地，所述协同力对应的二级评价指标中，所述可协调柔性负荷比例E 3的计算表达式为： Further, in the secondary evaluation index corresponding to the synergy force, the calculation expression of the coordinated flexible load ratio E3 is:
Figure PCTCN2021142298-appb-000009
Figure PCTCN2021142298-appb-000009
式中，S FL为可协调柔性负荷峰值，S L,max为年网供最大负荷； In the formula, S FL is the peak value of the coordinated flexible load, and S L,max is the maximum load of the annual network supply;
所述本地清洁能源消纳率E 4的计算表达式为： The calculation expression of the local clean energy consumption rate E4 is:
Figure PCTCN2021142298-appb-000010
Figure PCTCN2021142298-appb-000010
式中，P oi为区域外净受入电量，P oa为区域外协议电量，P co为本地清洁能源上网电量，P cg为本地清洁能源发电量。 In the formula, P oi is the net electricity received outside the region, P oa is the agreed electricity outside the region, P co is the on-grid electricity of local clean energy, and P cg is the power generation of local clean energy.
进一步地，所述学习力对应的二级评价指标中，所述态势预测数据与实际数据误差期望F 1的计算表达式为： Further, in the secondary evaluation index corresponding to the learning ability, the calculation expression of the error expectation F1 between the situation prediction data and the actual data is:
Figure PCTCN2021142298-appb-000011
Figure PCTCN2021142298-appb-000011
式中，T为量测的总时长，N z,t为t时刻感知系统预测的量测总数，
Figure PCTCN2021142298-appb-000012
为t时刻感知系统得到的第i项 量测预估值，
Figure PCTCN2021142298-appb-000013
为t时刻第i项量测对应的系统状态真值； In the formula, T is the total duration of measurement, N z,t is the total number of measurements predicted by the sensing system at time t,
Figure PCTCN2021142298-appb-000012
is the predicted value of the i-th measurement obtained by the perception system at time t,
Figure PCTCN2021142298-appb-000013
Measure the true value of the corresponding system state for the i-th item at time t;
所述灾后感知系统可修复漏洞比例F 2的计算表达式为： The calculation expression of the repairable vulnerability ratio F2 of the post-disaster awareness system is:
Figure PCTCN2021142298-appb-000014
Figure PCTCN2021142298-appb-000014
式中，n vf为感知系统灾后发现漏洞总数，n vr为感知系统灾后可修复漏洞数。 In the formula, n vf is the total number of vulnerabilities found in the perception system after the disaster, and n vr is the number of repairable vulnerabilities in the perception system after the disaster.
进一步地，所述应变力对应的二级评价指标包括电压暂变率、潮流越限率、电压谐波畸变率、频率偏差率、配电需要率、N-1校验通过率、有功备用率和拓扑完整度中的一个或多个。Further, the secondary evaluation indicators corresponding to the strain force include voltage transient rate, power flow overrun rate, voltage harmonic distortion rate, frequency deviation rate, power distribution demand rate, N-1 verification pass rate, active power reserve rate One or more of and topological integrity.
进一步地，所述电压暂变率B 1的计算表达式为： Further, the calculation expression of the voltage transient rate B1 is:
Figure PCTCN2021142298-appb-000015
Figure PCTCN2021142298-appb-000015
Figure PCTCN2021142298-appb-000016
Figure PCTCN2021142298-appb-000016
式中，n p为电压暂变次数，
Figure PCTCN2021142298-appb-000017
为节点i当前暂态时刻的电压暂变量，V i,max为节点i的暂态上限电压，V i,min为节点i的暂态下限电压，V i(t)指节点i当前暂态时刻的电压，T为统计周期； where n p is the number of voltage transients,
Figure PCTCN2021142298-appb-000017
is the voltage transient variable at the current transient moment of node i, V i,max is the transient upper limit voltage of node i, V i,min is the transient lower limit voltage of node i, V i (t) refers to the current transient moment of node i voltage, T is the statistical period;
所述潮流越限率B 2的计算表达式为： The calculation expression of the power flow limit rate B2 is:
Figure PCTCN2021142298-appb-000018
Figure PCTCN2021142298-appb-000018
Figure PCTCN2021142298-appb-000019
Figure PCTCN2021142298-appb-000019
式中，
Figure PCTCN2021142298-appb-000020
为支路i在t时刻的潮流越限量，S i,max为支路i的额定潮流上限，S i(t)为支路i在t时刻的潮流大小，n l为电网支路总数； In the formula,
Figure PCTCN2021142298-appb-000020
is the power flow limit of branch i at time t, S i,max is the rated power flow upper limit of branch i, S i (t) is the power flow of branch i at time t, and n l is the total number of power grid branches;
所述电压谐波畸变率B 3的计算表达式为： The calculation expression of the voltage harmonic distortion rate B3 is:
Figure PCTCN2021142298-appb-000021
Figure PCTCN2021142298-appb-000021
式中，V 1,i为节点i的基波电压有效值，V k,i为节点i的第k次谐波电压有效值，n p为总节点数； In the formula, V 1,i is the effective value of the fundamental wave voltage of node i, V k,i is the effective value of the kth harmonic voltage of node i, and n p is the total number of nodes;
所述频率偏差率B 4的计算表达式为： The calculation expression of the frequency deviation rate B4 is:
Figure PCTCN2021142298-appb-000022
Figure PCTCN2021142298-appb-000022
式中，f为系统当前频率，f N为额定频率，Δf th为频率偏差限值。 In the formula, f is the current frequency of the system, f N is the rated frequency, and Δf th is the frequency deviation limit.
进一步地，所述配电需要率B 5的计算表达式为： Further, the calculation expression of the power distribution demand rate B5 is:
Figure PCTCN2021142298-appb-000023
Figure PCTCN2021142298-appb-000023
式中，P a为韧性电网用户实际用电总功率，P N为韧性电网用户总额定频率； In the formula, P a is the total power actually consumed by users of the resilient grid, and P N is the total rated frequency of users of the resilient grid;
所述N-1校验通过率B 6的计算表达式为： The calculation expression of the N-1 verification pass rate B6 is:
Figure PCTCN2021142298-appb-000024
Figure PCTCN2021142298-appb-000024
式中，n t为电网范围内变电站总数，n t(N-1)为通过N-1校验的变电站数，n l为电网范围内线路总数，n l(N-1)为通过N-1校验的线路数，α t、α l分别为变电站和线路指标权重，α t+α l＝1； In the formula, n t is the total number of substations within the power grid, n t(N-1) is the number of substations passing N-1 verification, n l is the total number of lines within the power grid, and n l(N-1) is the number of substations passing N-1 1 The number of lines to be verified, α t and α l are the index weights of substation and line respectively, α t + α l = 1;
所述有功备用率B 7的计算表达式为： The calculation expression of described active power reserve ratio B7 is:
Figure PCTCN2021142298-appb-000025
Figure PCTCN2021142298-appb-000025
式中，P r为电网有功备用容量，P r.lim为电网有功备用容量限值； In the formula, P r is the active power reserve capacity of the power grid, and P r.lim is the limit value of the power grid active power reserve capacity;
所述拓扑完整度B 8的计算表达式为： The calculation expression of the topological integrity B8 is:
Figure PCTCN2021142298-appb-000026
Figure PCTCN2021142298-appb-000026
式中，s i(t)为时刻t下线路i的运行状态，当线路i正常运行时，s i(t)＝1，当线路i停运时，s i(t)＝0，T为统计周期，n l为总线路数。 In the formula, s i (t) is the operating state of line i at time t, when line i is in normal operation, s i (t) = 1, when line i is out of service, s i (t) = 0, T is Statistical cycle, n l is the total number of lines.
进一步地，所述防御力对应的二级评价指标包括性能指数、配电容载比和电网故障率中的一个或多个。Further, the secondary evaluation index corresponding to the defense force includes one or more of performance index, distribution capacity-to-load ratio, and grid failure rate.
进一步地，所述性能指数C 1的计算表达式为： Further, the calculation expression of the performance index C1 is:
Figure PCTCN2021142298-appb-000027
Figure PCTCN2021142298-appb-000027
式中，P o为灾害前原始电网容量，P d为采取主动防御措施后的电网容量，P low为电网性能降至最低水平时的容量，t low为电网性能降至最低水平时的时间，t d为采取主动防御措施的时间； In the formula, P o is the original grid capacity before the disaster, P d is the grid capacity after taking active defense measures, P low is the capacity when the grid performance drops to the lowest level, and t low is the time when the grid performance drops to the lowest level, t d is the time for taking active defense measures;
所述配网容载比C 2的计算表达式为： The calculation expression of the distribution network capacity load ratio C2 is:
Figure PCTCN2021142298-appb-000028
Figure PCTCN2021142298-appb-000028
式中，S T为配网变电设备总容量，S L,max为年网供最大负荷； In the formula, S T is the total capacity of distribution network substation equipment, S L,max is the maximum load of annual network supply;
所述电网故障率C 3的计算表达式为： The calculation expression of the grid failure rate C3 is:
Figure PCTCN2021142298-appb-000029
Figure PCTCN2021142298-appb-000029
式中，n pe为电网内电力设备总数，p fault,i为设备i的故障概率。 In the formula, n pe is the total number of power equipment in the grid, and p fault,i is the failure probability of equipment i.
进一步地，所述恢复力对应的二级评价指标包括用户平均停电时间、故障自愈率、黑启动成功率和系统平均预安排停电时间中的一个或多个。Further, the secondary evaluation index corresponding to the resilience includes one or more of the average power outage time of users, the fault self-healing rate, the success rate of black start, and the average pre-arranged power outage time of the system.
进一步地，所述用户平均停电时间D 1的计算表达式为： Further, the calculation expression of the user average power outage time D1 is:
Figure PCTCN2021142298-appb-000030
Figure PCTCN2021142298-appb-000030
式中，t cut为第i次故障停电持续时间，n ucut,i为第i次故障停电用户数，n u为电网总用户数； In the formula, t cut is the power outage duration of the i-th fault, n ucut,i is the number of users of the i-th fault power outage, and n u is the total number of users of the power grid;
所述故障自愈率D 2的计算表达式为： The calculation expression of the fault self-healing rate D2 is:
Figure PCTCN2021142298-appb-000031
Figure PCTCN2021142298-appb-000031
式中，n ush,i为第i次故障自愈用户数，n ufault,i为第i次故障影响的总用户数； In the formula, n ush,i is the number of self-healing users of the i-th fault, and n ufault,i is the total number of users affected by the i-th fault;
所述黑启动成功率D 3的计算表达式为： The calculation expression of described black start success rate D3 is:
Figure PCTCN2021142298-appb-000032
Figure PCTCN2021142298-appb-000032
式中，n ubs,i为第i次故障通过黑启动恢复供电的用户数，n ufault,i为第i次故障影响的总用户数。 In the formula, n ubs,i is the number of users whose power supply is restored through black start for the i-th fault, and n ufault,i is the total number of users affected by the i-th fault.
进一步地，所述系统平均预安排停电时间D 4的计算表达式为： Further, the calculation expression of the average prearranged power outage time D4 of the system is:
Figure PCTCN2021142298-appb-000033
Figure PCTCN2021142298-appb-000033
式中，t pc,i为第i次预安排停电时间，n upc,i为第i次预安排停电用户数，n u为电网总用户数。 In the formula, t pc,i is the i-th pre-scheduled power outage time, n upc,i is the number of pre-scheduled power outage users for the i-th time, and n u is the total number of power grid users.
进一步地，所述二级评价指标和一级评价指标的权重的设定过程均包括以下步骤：Further, the setting process of the weight of the secondary evaluation index and the primary evaluation index includes the following steps:
主观赋权步骤：对各项指标进行主观赋权；Subjective weighting step: carry out subjective weighting on each indicator;
客观赋权步骤：对各项指标进行客观赋权；Objective empowerment step: objectively empower each indicator;
综合权重优化步骤：获取所述主观赋权步骤和客观赋权步骤中各赋权方法得到的权重向量；从而计算各赋权方法整体的集合权重，所述集合权重的计算表达式为：Comprehensive weight optimization step: obtaining the weight vector obtained by each weighting method in the subjective weighting step and the objective weighting step; thereby calculating the overall set weight of each weighting method, and the calculation expression of the set weight is:
Figure PCTCN2021142298-appb-000034
Figure PCTCN2021142298-appb-000034
式中，M为赋权方法的总数，u m＝(u m1,u m2,…,u mN)为第m个赋权方法的权重向量，u mn为第m个赋权方法获得的第n个指标的权重，N为指标的总数，d n为集合权重； In the formula, M is the total number of weighting methods, u m =(u m1 ,u m2 ,…,u mN ) is the weight vector of the mth weighting method, u mn is the nth weighting method obtained by the mth weighting method The weight of indicators, N is the total number of indicators, d n is the set weight;
计算每种赋权方法结果与所述集合权重间的相对熵，该相对熵的计算表达式为：Calculate the relative entropy between the result of each weighting method and the set weight, the calculation expression of the relative entropy is:
Figure PCTCN2021142298-appb-000035
Figure PCTCN2021142298-appb-000035
式中，h(u m,d)为第m个赋权方法的权重向量与集合权重间的相对熵； In the formula, h(u m ,d) is the relative entropy between the weight vector of the mth weighting method and the set weight;
根据所述相对熵，计算每种赋权方法的偏好系数，该偏好系数的计算表达式为：According to the relative entropy, calculate the preference coefficient of each weighting method, the calculation expression of the preference coefficient is:
Figure PCTCN2021142298-appb-000036
Figure PCTCN2021142298-appb-000036
式中，a m为第m个赋权方法的偏好系数； In the formula, a m is the preference coefficient of the mth weighting method;
根据所述偏好系数计算各指标的综合指标权重系数，该综合指标权重系数的计算表达式为：The comprehensive index weight coefficient of each index is calculated according to the preference coefficient, and the calculation expression of the comprehensive index weight coefficient is:
Figure PCTCN2021142298-appb-000037
Figure PCTCN2021142298-appb-000037
式中，w n为第n个指标的综合指标权重系数。 In the formula, w n is the comprehensive index weight coefficient of the nth index.
进一步地，所述主观赋权步骤包括：采用二项系数法对各项指标进行主观赋权，所述二项系数法包括以下步骤：Further, the subjective weighting step includes: using the binomial coefficient method to subjectively weight each index, and the binomial coefficient method includes the following steps:
由M位专家对共N项评估指标进行两两对比，独立得到指标集的重要度排序O m，取各专家排序平均值得到第n项指标的平均重要度排序，该第n项指标的平均重要度排序的计算表达式为： M experts make a pairwise comparison of a total of N evaluation indicators, and independently obtain the importance ranking O m of the index set, and take the average ranking of each expert to obtain the average importance ranking of the nth index, and the average of the nth index The calculation expression for importance ranking is:
Figure PCTCN2021142298-appb-000038
Figure PCTCN2021142298-appb-000038
式中，O(x n)为第n项指标的平均重要度排序，O m(n)为第m个对第n项指标的重要度排序； In the formula, O(x n ) is the average importance ranking of the nth index, and O m (n) is the importance ranking of the mth index to the nth index;
按照平均重要度排序从小到大的顺序重新排列N项评估指标，得到新的指标序列：Rearrange the N evaluation indicators according to the order of average importance from small to large, and get a new index sequence:
Figure PCTCN2021142298-appb-000039
Figure PCTCN2021142298-appb-000039
式中，x 1,x 2,…,x N为排序后的评估指标； In the formula, x 1 , x 2 ,…, x N are the sorted evaluation indicators;
做出指标集的对称排序：Make a symmetric ordering of an index set:
x N,…,x 2,x 1,x 3,…,x N-1 x N ,…,x 2 ,x 1 ,x 3 ,…,x N-1
按对称排序指标集再次从左到右为各指标编号，记作i，即可计算得到各指标主观权重，所述各指标主观权重的计算表达式为：Sorting index sets according to symmetry again numbers each index from left to right, denoted as i, then the subjective weight of each index can be calculated, and the calculation expression of the subjective weight of each index is:
Figure PCTCN2021142298-appb-000040
Figure PCTCN2021142298-appb-000040
式中，u i为指标编号为i的指标的主观权重，
Figure PCTCN2021142298-appb-000041
为指标排列组合的计算结果。 In the formula, u i is the subjective weight of the indicator whose index number is i,
Figure PCTCN2021142298-appb-000041
Computational results for indicator permutations.
进一步地，所述客观赋权步骤执行前还包括：对各指标进行归一化处理，该归一化处理具体为：Further, before the execution of the objective weighting step, it also includes: performing normalization processing on each index, and the normalization processing is specifically:
效益型指标的归一化处理表达式为：The normalized processing expression of the benefit index is:
Figure PCTCN2021142298-appb-000042
Figure PCTCN2021142298-appb-000042
式中，x mn为第m个待选方案的第n项指标实际计算数值，y mn′为第m个待选方案的第n项指标的效益型指标归一化值，x n,min为第n项指标的最小值，x n,max为第n项指标的最大值，所述待选方案为采用所述指标获得的各项实际指标值； In the formula, x mn is the actual calculated value of the nth index of the mth candidate, y mn ′ is the normalized value of the benefit index of the nth index of the mth candidate, and x n,min is The minimum value of the nth item index, x n, max is the maximum value of the nth item index, and the described candidate scheme is each actual index value obtained by adopting the described index;
成本型指标的归一化处理表达式为：The normalized processing expression of the cost index is:
Figure PCTCN2021142298-appb-000043
Figure PCTCN2021142298-appb-000043
式中，y mn″为第m个客观赋权方案的第n项指标的成本型指标归一化值。 In the formula, y mn ″ is the normalized value of the cost index of the nth index of the mth objective weighting scheme.
进一步地，所述客观赋权步骤包括：采用反熵权法对各项指标进行客观赋权，所述反熵权法的计算过程包括：Further, the objective weighting step includes: using the anti-entropy weight method to carry out objective weighting on various indicators, and the calculation process of the anti-entropy weight method includes:
计算各指标的反熵值h n，该反熵值h n的计算表达式为： Calculate the anti-entropy value h n of each index, the calculation expression of the anti-entropy value h n is:
Figure PCTCN2021142298-appb-000044
Figure PCTCN2021142298-appb-000044
Figure PCTCN2021142298-appb-000045
Figure PCTCN2021142298-appb-000045
式中，y mn为第m个客观赋权方案的第n项指标的指标归一化值，M为待选方案的总数； In the formula, y mn is the index normalization value of the nth item index of the mth objective weighting scheme, and M is the total number of alternative schemes;
根据所述反熵值进一步确定各指标权重，所述指标权重的计算表达式为：Each index weight is further determined according to the anti-entropy value, and the calculation expression of the index weight is:
Figure PCTCN2021142298-appb-000046
Figure PCTCN2021142298-appb-000046
式中，u n为第n项指标的指标权重，N为指标的总数。 In the formula, u n is the indicator weight of the nth indicator, and N is the total number of indicators.
进一步地，所述客观赋权步骤包括：采用CRITIC(Criteria Importance Through Intercriteria Correlation)法对各项指标进行客观赋权，所述CRITIC法的计算过程包括：Further, the objective weighting step includes: adopting the CRITIC (Criteria Importance Through Intercriteria Correlation) method to carry out objective weighting to each index, and the calculation process of the CRITIC method includes:
计算各指标的冗余信息熵p n，该冗余信息熵p n的计算表达式为： Calculate the redundant information entropy p n of each index, the calculation expression of the redundant information entropy p n is:
Figure PCTCN2021142298-appb-000047
Figure PCTCN2021142298-appb-000047
Figure PCTCN2021142298-appb-000048
Figure PCTCN2021142298-appb-000048
式中，p n为第n项指标的冗余信息熵，y mn为第m个客观赋权方案的第n项指标的指标归一化值，M为待选方案的总数； In the formula, p n is the redundant information entropy of the nth item index, y mn is the index normalization value of the nth item index of the mth objective weighting scheme, and M is the total number of alternative schemes;
利用归一化矩阵计算各列间协方差和指标的变异系数s n，从而计算各指标间的相关系数，所述各指标间的相关系数的计算表达式为： Use the normalized matrix to calculate the covariance between columns and the coefficient of variation sn of the index, so as to calculate the correlation coefficient between each index. The calculation expression of the correlation coefficient between each index is:
Figure PCTCN2021142298-appb-000049
Figure PCTCN2021142298-appb-000049
Figure PCTCN2021142298-appb-000050
Figure PCTCN2021142298-appb-000050
Figure PCTCN2021142298-appb-000051
Figure PCTCN2021142298-appb-000051
式中，
Figure PCTCN2021142298-appb-000052
为第n项指标的归一化值，s n为第n项指标的变异系数，N为指标的总数，
Figure PCTCN2021142298-appb-000053
为第n项和第n *项的相关系数，
Figure PCTCN2021142298-appb-000054
为第n *项的指标值，
Figure PCTCN2021142298-appb-000055
为指标值y n和
Figure PCTCN2021142298-appb-000056
间的协方差，
Figure PCTCN2021142298-appb-000057
为第n *项的变异系数； In the formula,
Figure PCTCN2021142298-appb-000052
is the normalized value of the nth index, s n is the variation coefficient of the nth index, N is the total number of indexes,
Figure PCTCN2021142298-appb-000053
is the correlation coefficient between the nth item and the n * th item,
Figure PCTCN2021142298-appb-000054
is the index value of the n * th item,
Figure PCTCN2021142298-appb-000055
is the index value y n and
Figure PCTCN2021142298-appb-000056
The covariance between
Figure PCTCN2021142298-appb-000057
is the coefficient of variation of the n * th item;
评估各指标所包含的信息量，该信息量的计算表达式为：Evaluate the amount of information contained in each index, the calculation expression of the amount of information is:
Figure PCTCN2021142298-appb-000058
Figure PCTCN2021142298-appb-000058
式中，i n为第n项指标的信息量； In the formula, i n is the amount of information of the nth index;
根据信息量确定指标权重，该指标权重的计算表达式为：The indicator weight is determined according to the amount of information, and the calculation expression of the indicator weight is:
Figure PCTCN2021142298-appb-000059
Figure PCTCN2021142298-appb-000059
式中，u n为第n项指标的指标权重。 In the formula, u n is the index weight of the nth index.
本发明还提供一种配电网的韧性综合评估系统，包括存储器和处理器，所述存储器存储有计算机程序，处理器调用所述计算机程序执行如上所述的方法的步骤。The present invention also provides a comprehensive evaluation system for the resilience of distribution networks, including a memory and a processor, the memory stores a computer program, and the processor invokes the computer program to execute the steps of the above-mentioned method.
与现有技术相比，本发明具有以下优点：Compared with the prior art, the present invention has the following advantages:
(1)本发明基于韧性电网特点，从感知力、应变力、防御力、恢复力、协同力、学习力6个宏观韧性衡量维度，构建了包括27个微观指标的配电网的韧性综合评价指标体系，尤其是感知力、协同力和学习力的二级指标的设置，为本发明创新设定和提出，可以实现韧性需求下配网的态势感知、扰动应对及自我提升等能力更为全面的综合评估；本发明针对韧性电网关键特征的六个范畴，聚焦配网态势感知、扰动应对及自我提升能力三个功能，能够建立韧性需求下更为全面、精细化的综合评估体系，提升评估结果的准确性和可靠性。(1) Based on the characteristics of the resilient power grid, the present invention constructs a comprehensive evaluation of the resilience of the distribution network including 27 micro indicators from the six macroscopic resilience measurement dimensions of perception, strain, defense, resilience, coordination, and learning The indicator system, especially the setting of the secondary indicators of perception, synergy, and learning ability, is set and proposed for the innovation of the present invention, which can realize the situation awareness, disturbance response, and self-improvement of the distribution network under the demand of resilience to be more comprehensive. comprehensive evaluation; the present invention focuses on the six categories of key characteristics of the resilient power grid, focusing on the three functions of distribution network situation awareness, disturbance response and self-improvement capabilities, and can establish a more comprehensive and refined comprehensive evaluation system under the demand for resilience to improve the evaluation Accuracy and reliability of results.
(2)本发明采用基于相对熵的综合权重优化方式，结合二项系数法、反熵权法、相关性权重法对指标体系进行综合赋权，可以实现主客观结合的权重计算，提升评估结果的准确性和可靠性。(2) The present invention adopts a comprehensive weight optimization method based on relative entropy, combined with the binomial coefficient method, anti-entropy weight method, and correlation weight method to carry out comprehensive weighting on the index system, which can realize subjective and objective weight calculations and improve evaluation results accuracy and reliability.
(3)本发明对于感知力的评估主要考虑其硬件配置及运行水平和对系统状态的把握程度，感知力的具体指标分别具有如下技术效果：(3) The present invention mainly considers its hardware configuration and operating level and the grasping degree to the system state for the assessment of perception, and the specific indicators of perception have the following technical effects respectively:
智能电表覆盖率：智能电表作为高级量测体系的重要组成部分，是实现态势感知系统测量、存储、计算电力量测量并与数据中心双向通讯的基本终端设备，其覆盖率反映了韧性电网基础感知水平；Smart meter coverage: As an important part of the advanced measurement system, the smart meter is the basic terminal equipment that realizes the measurement, storage, and calculation of power measurement by the situation awareness system and the two-way communication with the data center. Its coverage reflects the basic perception of the resilient grid. level;
薄弱节点可观度：当高风险事件发生，薄弱节点有更大概率出现电力性能的下降。对薄弱节点实时状态的把握程度即可反映韧性电网感知系统应对潜在灾害，及时切除隐患防止故障进一步扩大的能力；Weak node observability: When high-risk events occur, weak nodes have a greater probability of power performance degradation. The degree of grasp of the real-time status of weak nodes can reflect the ability of the resilient power grid perception system to deal with potential disasters, remove hidden dangers in time, and prevent further expansion of faults;
电网量测冗余度：不同于薄弱节点可观度主要体现灾害状态下电网感知系统的应对能力，电网量测冗余度反映了韧性电网在正常状态下，感知系统能否全面把握电网运行状态并协助其他系统做出决策，可作为薄弱节点可观度的补充；Grid measurement redundancy: Different from the observability of weak nodes, which mainly reflects the response ability of the power grid sensing system under disaster conditions, the power grid measurement redundancy reflects whether the sensing system can fully grasp the operating status of the power grid and Assist other systems to make decisions, which can be used as a supplement to the observability of weak nodes;
平均传输延时：平均传输延时定义为韧性电网运行数据在感知系统中传输并更新至数据库所需的平均用时，体现了韧性电网感知系统的实时性需求；Average transmission delay: The average transmission delay is defined as the average time required for the resilient grid operation data to be transmitted in the sensing system and updated to the database, which reflects the real-time requirements of the resilient grid sensing system;
态势可视度：态势可视度反映了感知系统的可视化水平，便利清晰的态势信息有利于运行管理人员在应对灾害事故时迅速辨析电力事件并做出相应决策；通过节点分布均匀度评估态势图可视化水平，节点分布均匀度越小，表明样本数据分布越均匀，可视化程度越高；Situational visibility: Situational visibility reflects the visualization level of the perception system. Convenient and clear situational information is helpful for operation managers to quickly identify and analyze power events and make corresponding decisions when responding to disasters; evaluate the situational map through the uniformity of node distribution Visualization level, the smaller the uniformity of node distribution, the more uniform the distribution of sample data and the higher the degree of visualization;
配电自动化系统运行指标：配电自动化系统作为电网数据采集与监视系统、地理信息系统、需求侧管理等系统的集合，综合了电力数据监视分析与远程控制等功能；与此前若干系统配置指标不同，配电自动化系统运行指标主要反映了韧性电网的决策执行准确率与执行效率的感知结果，属于实时动态指标。Operation index of distribution automation system: as a collection of power grid data collection and monitoring system, geographic information system, demand side management and other systems, distribution automation system integrates functions such as power data monitoring analysis and remote control; it is different from previous system configuration indicators , the operation index of the distribution automation system mainly reflects the perceived results of the decision-making execution accuracy and execution efficiency of the resilient power grid, which is a real-time dynamic index.
(4)本发明设置的协同力指标表征韧性电网合理高效利用内外部资源，共同集中力量抵御扰动事件的能力，协同力相关指标可用于提升和反映配电网对内外部防御资源、多维系统信息等的把控能力；协同力的具体指标分别具有如下技术效果：(4) The synergy index set by the present invention represents the ability of the resilient power grid to use internal and external resources reasonably and efficiently, and jointly concentrate forces to resist disturbance events. The synergy-related indicators can be used to improve and reflect the internal and external defense resources and multi-dimensional system information of the distribution network and other control capabilities; the specific indicators of synergy have the following technical effects:
配电线路联络率：作为最直观和基础的联络方式，配电线路的直接联络为区域内外间物理系统的调度配合提供了灵活性，同时其耦合元件的增加也为配电网提供了更高的量测冗余度；Distribution line contact rate: As the most intuitive and basic contact method, the direct connection of distribution lines provides flexibility for the dispatching and cooperation of physical systems inside and outside the region, and the increase of its coupling elements also provides higher measurement redundancy;
可协调柔性负荷比例：柔性负荷作为主动配电网的重要组成，承担着维持电力电量平衡和灾害协同恢复的责任；可协调柔性负荷比例决定了韧性电网协同抗扰的峰值能力，反映了柔性负荷对电网管理的协同作用Coordinated flexible load ratio: As an important component of the active distribution network, flexible loads are responsible for maintaining power balance and coordinated recovery from disasters; the coordinated flexible load ratio determines the peak capacity of the resilient grid’s collaborative anti-disturbance, reflecting the flexible load Synergies for grid management
配网转供率：线路转供可有效减少韧性电网在局部故障情况下的失负荷数量，发挥系统更大程度的协同应灾能力，同时也为配电网风险态势评估和决策效果模拟提供了更大灵活度；Distribution network transfer rate: line transfer can effectively reduce the number of lost loads in the resilient power grid under partial fault conditions, and exert a greater degree of coordinated disaster response capabilities of the system. It also provides a basis for distribution network risk situation assessment and decision-making effect simulation Greater flexibility;
本地清洁能源消纳率：清洁能源的消纳数量可综合体现韧性电网协同效果，与可协调柔性负荷比例不同，其动态表征了区域内外的电力电量协同平衡水平和灵活抗扰能力。Local clean energy consumption rate: The amount of clean energy consumption can comprehensively reflect the synergistic effect of the resilient grid, which is different from the coordinated flexible load ratio, which dynamically represents the coordinated balance level of power and electricity inside and outside the region and the flexible anti-disturbance capability.
(5)本发明设置的学习力作为其余特征的共同支撑，表征韧性电网从历史经验中自我修正完善和结合新技术提升革新的能力，可用于反映韧性配电网自主纠错和不断完善的能力；学习力的具体指标分别具有如下技术效果：(5) The learning power set by the present invention serves as a common support for the rest of the features, which represents the ability of the resilient power grid to self-correct and improve from historical experience and combine new technologies to improve innovation, and can be used to reflect the ability of the resilient distribution network to self-correct and continuously improve ; The specific indicators of learning ability have the following technical effects respectively:
态势预测数据与实际数据误差期望：结合历史运行数据和事故后风险态势复盘分析，可得到韧性电网各项预测数据与实际数据的误差，其误差期望及变化趋势可有效反映配电网的自我修正和自主完善能力；Error expectation between situation prediction data and actual data: Combined with historical operation data and post-accident risk situation review analysis, the error between various prediction data and actual data of the resilient power grid can be obtained, and its error expectation and change trend can effectively reflect the self-distribution network Correction and self-improvement capabilities;
灾后感知系统可修复漏洞比例：灾后感知系统可修复的漏洞比例直观反映了韧性电网系统的漏洞辨识、纠错及自学习能力。The proportion of vulnerabilities that can be repaired by the post-disaster perception system: The proportion of vulnerabilities that can be repaired by the post-disaster perception system directly reflects the vulnerability identification, error correction and self-learning capabilities of the resilient grid system.
附图说明Description of drawings
图1为本发明实施例中提供的一种二项系数法的流程示意图；Fig. 1 is the schematic flow chart of a kind of binomial coefficient method provided in the embodiment of the present invention;
图2为本发明实施例中提供的一种反熵权法的流程示意图；Fig. 2 is a schematic flow chart of an anti-entropy weight method provided in an embodiment of the present invention;
图3为本发明实施例中提供的一种CRITIC法的流程示意图；Fig. 3 is a schematic flow chart of a CRITIC method provided in an embodiment of the present invention;
图4为本发明实施例中提供的一种基于相对熵的综合权重优化流程示意图；FIG. 4 is a schematic diagram of a comprehensive weight optimization process based on relative entropy provided in an embodiment of the present invention;
图5为本发明实施例中提供的一种配电网的韧性综合评估流程示意图。Fig. 5 is a schematic flow diagram of a comprehensive resilience assessment process of a distribution network provided in an embodiment of the present invention.
具体实施方式Detailed ways
为使本发明实施例的目的、技术方案和优点更加清楚，下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例是本发明一部分实施例，而不是全部的实施例。通常在此处附图中描述和示出的本发明实施例的组件可以以各种不同的配置来布置和设计。In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of embodiments of the present invention, but not all embodiments. The components of the embodiments of the invention generally described and illustrated in the figures herein may be arranged and designed in a variety of different configurations.
因此，以下对在附图中提供的本发明的实施例的详细描述并非旨在限制要求保护的本发明的范围，而是仅仅表示本发明的选定实施例。基于本发明中的实施例，本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。Accordingly, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.
实施例1Example 1
本实施例提供一种配电网的韧性综合评估方法，包括以下步骤：This embodiment provides a method for comprehensively evaluating resilience of a distribution network, including the following steps:
获取配电网参数，根据预设的配电网韧性综合评价体系，进行评估；配电网韧性综合评价体系包括一级评价指标和二级评价指标，每个一级评价指标均设有对应的二级评价指标；Obtain distribution network parameters and evaluate according to the preset distribution network resilience comprehensive evaluation system; distribution network resilience comprehensive evaluation system includes first-level evaluation indicators and second-level evaluation indicators, and each first-level evaluation index has a corresponding Secondary evaluation index;
配电网韧性综合评价体系的一级评价指标包括感知力、应变力、防御力、恢复力、协同力和学习力；The first-level evaluation indicators of the distribution network resilience comprehensive evaluation system include perception, response, defense, resilience, coordination and learning;
感知力对应的二级评价指标包括智能电表覆盖率、薄弱节点可观度、电网量测冗余度、平均传输延时、态势可视度和配电自动化系统运行指标中的一个或多个；其中，智能电表覆盖率、薄弱节点可观度和电网量测冗余度用于体现配网边缘侧感知水平；平均传输延时、态势可视度和配电自动化系统运行指标用于体现配网调控 中心感知水平；The secondary evaluation indicators corresponding to perception include one or more of smart meter coverage, weak node observability, power grid measurement redundancy, average transmission delay, situation visibility and distribution automation system operation indicators; , smart meter coverage, weak node observability and power grid measurement redundancy are used to reflect the perception level of the edge side of the distribution network; average transmission delay, situation visibility and distribution automation system operation indicators are used to reflect the distribution network control center perception level;
应变力对应的二级评价指标包括电压暂变率、潮流越限率、电压谐波畸变率、频率偏差率、配电需要率、N-1校验通过率、有功备用率和拓扑完整度中的一个或多个；其中，电压暂变率、潮流越限率、电压谐波畸变率和频率偏差率用于体现配电网运行过程电气量参数指标；配电需要率、N-1校验通过率、有功备用率和拓扑完整度用于体现配电网的宏观规划指标；The secondary evaluation indicators corresponding to strain stress include voltage transient rate, power flow exceeding rate, voltage harmonic distortion rate, frequency deviation rate, power distribution demand rate, N-1 verification pass rate, active power reserve rate and topology integrity One or more of them; Among them, the voltage transient rate, the power flow limit rate, the voltage harmonic distortion rate and the frequency deviation rate are used to reflect the electrical quantity parameter indicators of the distribution network operation process; the distribution demand rate, N-1 verification Through rate, active power reserve rate and topology integrity are used to reflect the macro planning indicators of distribution network;
防御力对应的二级评价指标包括性能指数、配电容载比和电网故障率中的一个或多个；The secondary evaluation indicators corresponding to the defense force include one or more of performance index, distribution capacity load ratio and grid failure rate;
恢复力对应的二级评价指标包括用户平均停电时间、故障自愈率、黑启动成功率和系统平均预安排停电时间中的一个或多个；其中，系统平均预安排停电时间用于体现配电网的事故前预警检修水平；用户平均停电时间、故障自愈率和黑启动成功率用于体现配电网的事故后恢复水平；The secondary evaluation indicators corresponding to the resilience include one or more of the user average power outage time, fault self-healing rate, black start success rate, and system average pre-scheduled power outage time; among them, the system’s average pre-scheduled power outage time is used to reflect the power distribution The pre-accident warning and maintenance level of the distribution network; the average power outage time of users, the fault self-healing rate and the black start success rate are used to reflect the post-accident recovery level of the distribution network;
协同力对应的二级评价指标包括配电线路联络率、可协调柔性负荷比例、配网转供率和本地清洁能源消纳率中的一个或多个；其中，配电线路联络率和配网转供率用于体现配电网的物理线路协同水平；可协调柔性负荷比例和本地清洁能源消纳率用于体现配电网的柔性资源协同水平。The secondary evaluation indicators corresponding to synergy include one or more of distribution line connection rate, coordinated flexible load ratio, distribution network transfer rate and local clean energy consumption rate; among them, distribution line connection rate and distribution network The transfer rate is used to reflect the physical line coordination level of the distribution network; the coordinated flexible load ratio and the local clean energy consumption rate are used to reflect the flexible resource coordination level of the distribution network.
学习力对应的二级评价指标包括态势预测数据与实际数据误差期望和灾后感知系统可修复漏洞比例中的一个或多个；The secondary evaluation indicators corresponding to the learning ability include one or more of the error expectation between the situation prediction data and the actual data and the ratio of repairable loopholes in the post-disaster perception system;
基于各个二级评价指标的评估结果，根据预设的各个二级评价指标的权重以及各个一级评价指标的权重，进行综合计算，获取配电网的韧性综合评估结果。Based on the evaluation results of each secondary evaluation index, according to the preset weight of each secondary evaluation index and the weight of each first-level evaluation index, a comprehensive calculation is performed to obtain the comprehensive evaluation result of the resilience of the distribution network.
上述感知力、应变力、防御力、恢复力、协同力和学习力对应的二级评价指标的数量不作限定，可在上述提供的二级评价指标中任意选取，优选为采用本实施例提供的所有对应的二级评价指标，下面对一种最优的实施方式进行具体描述。The number of secondary evaluation indicators corresponding to the above-mentioned perception, strain, defense, resilience, synergy and learning ability is not limited, and can be arbitrarily selected from the above-mentioned secondary evaluation indicators, preferably using the one provided by this embodiment. For all the corresponding secondary evaluation indicators, an optimal implementation manner will be described in detail below.
一、配电网韧性综合评价体系构建1. Construction of distribution network resilience comprehensive evaluation system
基于韧性电网各关键特征间关系和微观评估指标选取原则，从感知力、应变力、防御力、恢复力、协同力、学习力六个维度综合评估配电网的实际韧性水平，建立了配电网韧性综合评价指标体系如表1所示。Based on the relationship between the key characteristics of the resilient grid and the selection principles of micro-evaluation indicators, the actual resilience level of the distribution network is comprehensively evaluated from the six dimensions of perception, strain, defense, resilience, coordination, and learning, and the power distribution system is established. The comprehensive evaluation index system of network toughness is shown in Table 1.
表1配网韧性综合评价指标体系Table 1 Distribution network resilience comprehensive evaluation index system
Figure PCTCN2021142298-appb-000060
Figure PCTCN2021142298-appb-000060
下面对各二级评价指标进行具体介绍：The following is a detailed introduction to each secondary evaluation index:
1、感知力1. Perception
依据数据获取的便捷性和实用性原则，对于感知力的评估主要考虑其硬件配置及运行水平和对系统状态的把握程度。算法效率、风险态势预测等在直接量化评估时存在一定困难的韧性电网感知力水平相关指标，将由后续其他维度的指标来间接反映。According to the principles of convenience and practicability of data acquisition, the evaluation of perception mainly considers its hardware configuration and operation level and the degree of grasp of the system state. Algorithmic efficiency, risk situation prediction, and other related indicators of the resilience level of the power grid that are difficult to evaluate directly will be indirectly reflected by subsequent indicators of other dimensions.
1)智能电表覆盖率1) Smart meter coverage
智能电表作为高级量测体系的重要组成部分，是实现态势感知系统测量、存储、计算电力量测量并与数据中心双向通讯的基本终端设备，其覆盖率反映了韧性电网基础感知水平，计算公式如下：As an important part of the advanced measurement system, the smart meter is the basic terminal equipment that realizes the measurement, storage and calculation of the power measurement of the situation awareness system and the two-way communication with the data center. Its coverage reflects the basic perception level of the resilient grid. The calculation formula is as follows :
Figure PCTCN2021142298-appb-000061
Figure PCTCN2021142298-appb-000061
式中，n sm表示电网区域内的智能电表数量，n m表示电网区域内的总电表数。 In the formula, n sm represents the number of smart meters in the grid area, and n m represents the total number of meters in the grid area.
2)薄弱节点可观度2) Observability of weak nodes
当高风险事件发生，薄弱节点有更大概率出现电力性能的下降。对薄弱节点实时状态的把握程度即可反映韧性电网感知系统应对潜在灾害，及时切除隐患防止故障进一步扩大的能力。依据负荷-系统短路容量比判别节点薄弱程度，负荷-系统短路容量比计算公式如下：When high-risk events occur, weak nodes have a greater probability of power performance degradation. The degree of grasp of the real-time status of weak nodes can reflect the ability of the resilient grid perception system to deal with potential disasters, remove hidden dangers in time, and prevent further expansion of faults. According to the load-system short-circuit capacity ratio to judge the node weakness, the calculation formula of the load-system short-circuit capacity ratio is as follows:
Figure PCTCN2021142298-appb-000062
Figure PCTCN2021142298-appb-000062
式中，E Pi、Z Pi为节点处电网戴维宁等效电路参数，U Li、Z Li为节点处负荷戴维宁等效电路参数。负荷-系统短路容量比越大，节点可承受的电压裕度越小，当该指标高于预先设定的阈值，即认为该节点为薄弱节点。当节点的电压相量可直接量测或由计算得出，则该节点可观。薄弱节点可观度计算公式如下： In the formula, E Pi and Z Pi are the Thevenin equivalent circuit parameters of the power grid at the node, and U Li and Z Li are the Thevenin equivalent circuit parameters of the load at the node. The larger the load-system short-circuit capacity ratio, the smaller the voltage margin the node can withstand. When the index is higher than the preset threshold, the node is considered to be a weak node. A node is substantial when its voltage phasor can be measured directly or calculated. The formula for calculating the observability of weak nodes is as follows:
Figure PCTCN2021142298-appb-000063
Figure PCTCN2021142298-appb-000063
式中，n wm表示可观薄弱节点的数量，n w表示薄弱节点总数。 In the formula, n wm represents the number of considerable weak nodes, and n w represents the total number of weak nodes.
3)电网量测冗余度3) Grid measurement redundancy
不同于薄弱节点可观度主要体现灾害状态下电网感知系统的应对能力，电网量测冗余度反映了韧性电网在正常状态下，感知系统能否全面把握电网运行状态并协助其他系统做出决策，可作为薄弱节点可观度的补充。电网量测冗余度计算公式如下：Different from the observability of weak nodes, which mainly reflects the coping ability of the grid sensing system under disaster conditions, the grid measurement redundancy reflects whether the sensing system can fully grasp the operating status of the grid and assist other systems to make decisions under the normal state of the resilient grid. Can be used as a supplement to the observability of weak nodes. The grid measurement redundancy calculation formula is as follows:
Figure PCTCN2021142298-appb-000064
Figure PCTCN2021142298-appb-000064
式中，n pm表示可观节点的数量，n p表示电网节点总数。 In the formula, n pm represents the number of considerable nodes, and n p represents the total number of grid nodes.
4)平均传输延时4) Average transmission delay
平均传输延时定义为韧性电网运行数据在感知系统中传输并更新至数据库所需的平均用时，体现了韧性电网感知系统的实时性需求。计算公式如下：The average transmission delay is defined as the average time required for the resilient grid operation data to be transmitted in the sensing system and updated to the database, reflecting the real-time requirements of the resilient grid sensing system. Calculated as follows:
Figure PCTCN2021142298-appb-000065
Figure PCTCN2021142298-appb-000065
式中，t mi表示电表i采集量测量的时刻，t ui表示电表i量测数据更新至数据库的时刻。 In the formula, t mi represents the time when the meter i collects and measures, and t ui represents the time when the measurement data of the electric meter i is updated to the database.
5)态势可视度5) Situation visibility
态势可视度反映了感知系统的可视化水平，便利清晰的态势信息有利于运行管理人员在应对灾害事故时迅速辨析电力事件并做出相应决策。通过节点分布均匀度评估态势图可视化水平，节点分布均匀度越小，表明样本数据分布越均匀，可视化程度越高。具体计算公式如下：Situational visibility reflects the visualization level of the perception system. Convenient and clear situational information is helpful for operation managers to quickly identify and analyze power events and make corresponding decisions when responding to disasters. The visualization level of the situation map is evaluated by the uniformity of node distribution. The smaller the uniformity of node distribution, the more uniform the distribution of sample data and the higher the degree of visualization. The specific calculation formula is as follows:
Figure PCTCN2021142298-appb-000066
Figure PCTCN2021142298-appb-000066
式中，n为态势图划分的区块数量，N i为区块i中的节点数量，
Figure PCTCN2021142298-appb-000067
为N i的算术平均值。 In the formula, n is the number of blocks divided by the situation graph, N i is the number of nodes in block i,
Figure PCTCN2021142298-appb-000067
is the arithmetic mean of N i .
6)配电自动化系统运行指标6) Distribution automation system operating indicators
配电自动化系统作为电网数据采集与监视系统、地理信息系统、需求侧管理等系统的集合，综合了电力数据监视分析与远程控制等功能。与此前若干系统配置指标不同，配电自动化系统运行指标主要反映了韧性电网的决策执行准确率与执行效率的感知结果，属于实时动态指标，包括了配电自动化终端平均在线率、遥控成功率、遥信动作正确率、馈线自动化成功率四个子项，As a collection of power grid data acquisition and monitoring systems, geographic information systems, and demand-side management systems, the distribution automation system integrates functions such as power data monitoring, analysis, and remote control. Different from several previous system configuration indicators, the distribution automation system operation indicators mainly reflect the perception results of the decision-making execution accuracy and execution efficiency of the resilient power grid. They are real-time dynamic indicators, including the average online rate of distribution automation terminals, remote control success rate, The four sub-items are the correct rate of remote signaling action and the success rate of feeder automation.
配电自动化系统运行指标A 6的计算表达式为： The calculation expression of distribution automation system operation index A6 is:
A 6＝α aor×P aor+α rs×P rs+α rc×P rc+α fac×P fac A 6 ＝α aor ×P aor +α rs ×P rs +α rc ×P rc +α fac ×P fac
式中，P aor表示配电自动化终端平均在线率，P rs表示遥控成功率，P rc表示遥信动作正确率，P fac表示馈线自动化成功率，α aor、α rs、α rc、α fac为各项指标对应权重，α aor+α rs+α rc+α fac＝1； In the formula, P aor represents the average online rate of distribution automation terminals, P rs represents the success rate of remote control, P rc represents the correct rate of remote signaling action, P fac represents the success rate of feeder automation, α aor , α rs , α rc , and α fac are Each indicator corresponds to the weight, α aor + α rs + α rc + α fac = 1;
优选地，本实施例给出配电自动化系统运行指标A 6的最优权重配置的具体计算公式如下： Preferably, this embodiment provides the specific calculation formula of the optimal weight configuration of the distribution automation system operation index A6 as follows:
A 6＝0.25×P aor+0.25×P rs+0.2×P rc+0.3×P fac        (7) A 6 ＝0.25×P aor +0.25×P rs +0.2×P rc +0.3×P fac (7)
式中，P aor表示配电自动化终端平均在线率，P rs表示遥控成功率，P rc表示遥信动作正确率，P fac表示馈线自动化成功率。 In the formula, P aor represents the average online rate of distribution automation terminals, P rs represents the success rate of remote control, P rc represents the correct rate of remote signaling actions, and P fac represents the success rate of feeder automation.
配电自动化系统运行指标A 6中的系数可以根据实际情况进行调整，不做具体限定，本实施例提供的是配电自动化系统运行指标A 6的最优系数。 The coefficients in the distribution automation system operation index A6 can be adjusted according to the actual situation and are not specifically limited. This embodiment provides the optimal coefficient of the distribution automation system operation index A6 .
2、应变力2. Strain force
应变力体现韧性电网在极端事件发生前抵抗扰动，维持自身性能，以及制定风险预案的能力。应变力相关指标可用于反映电网在日常运行决策中的可靠性、高效性以及风险预测和事故前部署效能。Resilience reflects the ability of a resilient grid to resist disturbances, maintain its own performance, and formulate risk plans before extreme events occur. Resilience-related indicators can be used to reflect the reliability, efficiency, risk prediction and pre-accident deployment effectiveness of the power grid in daily operation decisions.
1)电压暂变率1) Voltage transient rate
电压暂变率主要用于反映电网正常运行中发生电压暂降(或暂升)的频率和幅度，较低的电压暂变率体现了系统较强的暂态稳定性和抗干扰能力，也反映了电网对于暂态扰动的监测和预警能力。电压暂变率计算公式如下：The voltage transient rate is mainly used to reflect the frequency and magnitude of voltage sags (or swells) in the normal operation of the power grid. The lower voltage transient rate reflects the strong transient stability and anti-interference ability of the system, and also reflects the It improves the monitoring and early warning capabilities of the power grid for transient disturbances. The calculation formula of voltage transient rate is as follows:
Figure PCTCN2021142298-appb-000068
Figure PCTCN2021142298-appb-000068
Figure PCTCN2021142298-appb-000069
Figure PCTCN2021142298-appb-000069
式中，n p为电压暂变次数，
Figure PCTCN2021142298-appb-000070
为节点i当前暂态时刻的电压暂变量，V i,max为节点i的暂态上限电压，V i,min为节点i的暂态下限电压，V i(t)指节点i当前暂态时刻的电压，T为统计周期。 where n p is the number of voltage transients,
Figure PCTCN2021142298-appb-000070
is the voltage transient variable at the current transient moment of node i, V i,max is the transient upper limit voltage of node i, V i,min is the transient lower limit voltage of node i, V i (t) refers to the current transient moment of node i The voltage, T is the statistical period.
2)潮流越限率2) Flow rate of limit violation
频繁的潮流越限会降低电网的抗干扰能力，不利于灾害前的风险管控。维持较低的潮流越限频度，体现了韧性电网的实时潮流监测和风险态势预估能力。潮流越限率计算公式如下：Frequent power flow violations will reduce the anti-interference ability of the power grid, which is not conducive to risk management and control before disasters. Maintaining a low frequency of power flow violations reflects the real-time power flow monitoring and risk situation prediction capabilities of the resilient grid. The calculation formula of power flow limit rate is as follows:
Figure PCTCN2021142298-appb-000071
Figure PCTCN2021142298-appb-000071
Figure PCTCN2021142298-appb-000072
Figure PCTCN2021142298-appb-000072
式中，
Figure PCTCN2021142298-appb-000073
为支路i在t时刻的潮流越限量，S i,max为支路i的额定潮流上限，S i(t)为支路i在t时刻的潮流大小，n l为电网支路总数。 In the formula,
Figure PCTCN2021142298-appb-000073
is the power flow limit of branch i at time t, S i,max is the rated power flow upper limit of branch i, S i (t) is the power flow of branch i at time t, and n l is the total number of power grid branches.
3)电压谐波畸变率3) Voltage harmonic distortion rate
电压的谐波畸变降低了电网范围内的供电质量，过大的畸变甚至会引发变压器和电力线路发热故障。较低的电压谐波畸变率符合韧性城市用户对于高电能质量的要求，也有利于事故前的小扰动抑制，反映了配电网的电能质量监控能力。电压谐波畸变率计算公式如下：Harmonic distortion of voltage reduces the quality of power supply within the grid range, and excessive distortion may even cause heating faults in transformers and power lines. The lower voltage harmonic distortion rate meets the requirements of resilient urban users for high power quality, and is also conducive to the suppression of small disturbances before accidents, reflecting the power quality monitoring capabilities of the distribution network. The calculation formula of voltage harmonic distortion rate is as follows:
Figure PCTCN2021142298-appb-000074
Figure PCTCN2021142298-appb-000074
式中，V 1,i为节点i的基波电压有效值，V k,i为节点i的第k次谐波电压有效值，n p为总节点数。 In the formula, V 1,i is the effective value of the fundamental wave voltage of node i, V k,i is the effective value of the kth harmonic voltage of node i, and n p is the total number of nodes.
4)频率偏差率4) Frequency deviation rate
频率偏差率属于电网稳态电能指标，体现了系统有功安全性能，潮流监测和负荷预测调配等技术有利于降低韧性电网的频率偏差。频率偏差率的计算公式如下：The frequency deviation rate belongs to the steady-state power index of the power grid, which reflects the active safety performance of the system. Technologies such as power flow monitoring and load forecasting and deployment are conducive to reducing the frequency deviation of the resilient power grid. The calculation formula of frequency deviation rate is as follows:
Figure PCTCN2021142298-appb-000075
Figure PCTCN2021142298-appb-000075
式中，f为系统当前频率，f N为额定频率，Δf th为频率偏差限值0.2Hz。 In the formula, f is the current frequency of the system, f N is the rated frequency, and Δf th is the frequency deviation limit of 0.2 Hz.
5)配电需要率5) Power distribution demand rate
配电需要率定义为韧性电网中用户实际运行功率与额定功率的比值，该数值体现了韧性电网中电力资源配置的合理性与经济性，同时反映了电网在柔性负荷调度和资源调配上的能力。配电需要率计算公式如下：The power distribution demand rate is defined as the ratio of the actual operating power of the user to the rated power in the resilient grid. This value reflects the rationality and economy of power resource allocation in the resilient grid, and also reflects the grid's ability in flexible load scheduling and resource allocation. . The formula for calculating the power distribution demand rate is as follows:
Figure PCTCN2021142298-appb-000076
Figure PCTCN2021142298-appb-000076
式中，P a为韧性电网用户实际用电总功率，P N为韧性电网用户总额定频率。 In the formula, P a is the actual total power consumption of the resilient grid users, and P N is the total rated frequency of the resilient grid users.
6)N-1校验通过率6) N-1 verification pass rate
N-1通过率包括了电网范围内的变电站N-1通过率和输电线路N-1通过率，作为表征电网可靠性和风险预警能力最直观的指标，其同时反映了韧性电网感知风险态势和模拟预想事故的能力。The N-1 pass rate includes the N-1 pass rate of substations and transmission lines within the power grid. As the most intuitive indicator to characterize the reliability and risk warning capabilities of the power grid, it also reflects the perceived risk situation of the resilient power grid and Ability to simulate anticipated accidents.
N-1校验通过率B 6的计算表达式为： The calculation expression of N-1 verification pass rate B 6 is:
Figure PCTCN2021142298-appb-000077
Figure PCTCN2021142298-appb-000077
式中，n t为电网范围内变电站总数，n t(N-1)为通过N-1校验的变电站数，n l为电网范围内线路总数，n l(N-1)为通过N-1校验的线路数，α t、α l分别为变电站和线路指标权重，α t+α l＝1； In the formula, n t is the total number of substations within the power grid, n t(N-1) is the number of substations passing N-1 verification, n l is the total number of lines within the power grid, and n l(N-1) is the number of substations passing N-1 1 The number of lines to be verified, α t and α l are the index weights of substation and line respectively, α t + α l = 1;
优选地，本实施例给出N-1校验通过率的最优权重配置的计算公式如下：Preferably, this embodiment provides the calculation formula for the optimal weight configuration of the N-1 verification pass rate as follows:
Figure PCTCN2021142298-appb-000078
Figure PCTCN2021142298-appb-000078
式中，n t为电网范围内变电站总数，n t(N-1)为通过N-1校验的变电站数，n l为电网范围内线路总数，n l(N-1)为通过N-1校验的线路数。 In the formula, n t is the total number of substations within the power grid, n t(N-1) is the number of substations passing N-1 verification, n l is the total number of lines within the power grid, and n l(N-1) is the number of substations passing N-1 1 The number of lines to check.
7)有功备用率7) Active power reserve ratio
与配电需要率不同，有功备用率更多关注应急资源的预先布置，适量的有功备用有利于在风险事故中维持系统性能，减少灾害带来的损失，且满足系统正常运行的经济性。具体计算公式如下：Different from the power distribution demand rate, the active power reserve rate pays more attention to the pre-arrangement of emergency resources. An appropriate amount of active power reserve is conducive to maintaining system performance in risky accidents, reducing losses caused by disasters, and meeting the economy of normal system operation. The specific calculation formula is as follows:
Figure PCTCN2021142298-appb-000079
Figure PCTCN2021142298-appb-000079
式中，P r为电网有功备用容量，P r.lim为电网有功备用容量限值，一般取0.1倍系统最大负荷。 In the formula, P r is the active power reserve capacity of the grid, and P r.lim is the limit value of the active power reserve capacity of the power grid, which is generally taken as 0.1 times the maximum load of the system.
8)拓扑完整度8) Topological integrity
电网拓扑结构的完整性极大影响其应对灾害时的脆弱程度，减少停运线路的数量和停运时间有利于构建更加坚强可靠的韧性电网。拓扑完整度的计算公式如下：The integrity of the power grid topology greatly affects its vulnerability to disasters. Reducing the number of outage lines and the outage time is conducive to building a stronger and more reliable resilient power grid. The calculation formula of topological integrity is as follows:
Figure PCTCN2021142298-appb-000080
Figure PCTCN2021142298-appb-000080
式中，s i(t)为时刻t下线路i的运行状态，当线路i正常运行时，s i(t)＝1，当线路i停运时，s i(t)＝0，T为统计周期，n l为总线路数。 In the formula, s i (t) is the operating state of line i at time t, when line i is in normal operation, s i (t) = 1, when line i is out of service, s i (t) = 0, T is Statistical cycle, n l is the total number of lines.
3、防御力3. Defense
防御力关注韧性电网在极端事件发生过程中，系统利用内外防御资源主动抵御灾害破坏，降低事件整体影响的能力。防御力相关指标可用于反映电网在极端条件下的运作效能和多变状态下的响应速率。Defensive power focuses on the ability of the resilient power grid to use internal and external defense resources to actively resist disaster damage and reduce the overall impact of events during the occurrence of extreme events. The defense-related indicators can be used to reflect the operational efficiency of the power grid under extreme conditions and the response rate under variable conditions.
1)性能指数1) Performance index
韧性评估中，可用性能曲线刻画韧性电网在极端事件过程中的动态变化，选取电网容量作为性能指标。In the resilience assessment, the availability performance curve describes the dynamic changes of the resilient grid during extreme events, and the grid capacity is selected as the performance index.
定义性能指数为主动防御速度与主动防御效果等因素的乘积，该指标同时反映了灾害发生过程中感知力的实时响应能力、灾害态势发展预测能力和防御资源评估能力，具体计算公式如下：The performance index is defined as the product of factors such as active defense speed and active defense effect. This index simultaneously reflects the real-time response ability of perception during the disaster occurrence process, the ability to predict the development of disaster situation, and the ability to evaluate defense resources. The specific calculation formula is as follows:
Figure PCTCN2021142298-appb-000081
Figure PCTCN2021142298-appb-000081
式中，P o为灾害前原始电网容量，P d为采取主动防御措施后的电网容量，P low为电网性能降至最低水平时的容量，t low为电网性能降至最低水平时的时间，t d为采取主动防御措施的时间。 In the formula, P o is the original grid capacity before the disaster, P d is the grid capacity after taking active defense measures, P low is the capacity when the grid performance drops to the lowest level, and t low is the time when the grid performance drops to the lowest level, t d is the time to take active defense measures.
2)配网容载比2) Distribution network capacity load ratio
配网容载比定义为配网区域内变电设备总容量与年最大负荷之比。一定的变压器备用容量有利于提高电网在灾害发生过程中的适应性，给防御资源调度带来更大的灵活性；同时，过大的容载比不仅增加了韧性电网的投资成本和建设周期，还降低了电网运行的经济性。如何在满足可靠性的同时降低配网容载比，就依赖于配电网更为精确的负荷预测和运行控制技术。配网容载比计算公式如下：The distribution network capacity-load ratio is defined as the ratio of the total capacity of substation equipment in the distribution network area to the annual maximum load. A certain transformer reserve capacity is conducive to improving the adaptability of the power grid in the process of disasters and bringing greater flexibility to the deployment of defense resources; at the same time, an excessive capacity-to-load ratio not only increases the investment cost and construction period of the resilient power grid, It also reduces the economics of grid operation. How to reduce the capacity-load ratio of the distribution network while satisfying reliability depends on more accurate load forecasting and operation control technology of the distribution network. The calculation formula of distribution network capacity load ratio is as follows:
Figure PCTCN2021142298-appb-000082
Figure PCTCN2021142298-appb-000082
式中，S T为配网变电设备总容量，S L,max为年网供最大负荷。 In the formula, S T is the total capacity of distribution network substation equipment, S L,max is the maximum load of annual network supply.
3)电网故障率3) Grid failure rate
为尽可能减小灾害事件导致的系统性能降低和扰动范围，需要防止大面积连锁故障的产生。利用监测预警等功能减小电网各元件的故障概率，可提高韧性电网在高风险事件中的抗击打能力。考虑各元件作用的电网故障率计算公式如下：In order to minimize the system performance degradation and disturbance range caused by disaster events, it is necessary to prevent the occurrence of large-scale cascading failures. Using functions such as monitoring and early warning to reduce the failure probability of each component of the power grid can improve the resilience of the resilient power grid in high-risk events. The calculation formula of grid failure rate considering the effect of each component is as follows:
Figure PCTCN2021142298-appb-000083
Figure PCTCN2021142298-appb-000083
式中，n pe为电网内电力设备总数，p fault,i为设备i的故障概率，可由历史数据结合态势预测技术得到。 In the formula, n pe is the total number of power equipment in the power grid, and p fault,i is the failure probability of equipment i, which can be obtained from historical data combined with situation prediction technology.
4、恢复力4. Resilience
恢复力考虑事故后电网性能的应急保障和逐步修复，时效性是恢复力最为重要的一个考量因素。恢复力相关指标可用于反映电网的故障定位、维护检修、远端控制和决策模拟评估等能力。Resilience considers the emergency guarantee and gradual restoration of power grid performance after an accident, and timeliness is the most important consideration for resilience. Resilience-related indicators can be used to reflect the power grid's capabilities in fault location, maintenance and repair, remote control, and decision-making simulation evaluation.
1)用户平均停电时间1) The average power outage time of users
停电时间是最直观反映韧性电网遭受扰动后恢复力水平的指标，故障定位、故障数据记录以及扰动因素分析等技术可有效降低平均停电时间。用户平均停电时间计算公式如下：Power outage time is the most intuitive indicator to reflect the resilience level of the resilient grid after a disturbance. Technologies such as fault location, fault data recording, and disturbance factor analysis can effectively reduce the average power outage time. The formula for calculating the average outage time of users is as follows:
Figure PCTCN2021142298-appb-000084
Figure PCTCN2021142298-appb-000084
式中，t cut为第i次故障停电持续时间，n ucut,i为第i次故障停电用户数，n u为电网总用户数。 In the formula, t cut is the power outage duration of the i-th fault, n ucut,i is the number of users in the i-th fault outage, and n u is the total number of users in the power grid.
2)故障自愈率2) Fault self-healing rate
故障自愈主要体现在电网面对较小扰动或极端事件初期时的自我修复能力，其周期包括监测预警、诊断分析和自动修复三个层次。高水平的韧性电网可在故障仍处于“势”的阶段告警并诊断其诱发因素，利用远端控制实现故障自愈尝试。故障自愈率计算公式如下：Fault self-healing is mainly reflected in the self-healing ability of the power grid in the face of small disturbances or the initial stage of extreme events, and its cycle includes three levels of monitoring and early warning, diagnosis and analysis, and automatic repair. A high-level resilient power grid can give an alarm and diagnose its triggering factors when the fault is still in the "potential" stage, and use remote control to achieve fault self-healing attempts. The formula for calculating the fault self-healing rate is as follows:
Figure PCTCN2021142298-appb-000085
Figure PCTCN2021142298-appb-000085
式中，n ush,i为第i次故障自愈用户数，n ufault,i为第i次故障影响的总用户数。 In the formula, n ush,i is the number of self-healing users of the i-th fault, and n ufault,i is the total number of users affected by the i-th fault.
3)黑启动成功率3) Black boot success rate
黑启动作为极端事件发生后应急保障的关键措施，其最优方案的制定很大程度依赖于配电网对故障集下系统状态的估计，以及方案在孪生系统等模拟环境下的运行效果。黑启动成功率可有效反映韧性电网灾后初步恢复能力，其计算公式如下：Black start is a key measure for emergency protection after extreme events. The formulation of its optimal scheme largely depends on the estimation of the system state under the fault set by the distribution network and the operation effect of the scheme in the simulation environment such as the twin system. The black start success rate can effectively reflect the initial post-disaster recovery ability of the resilient grid, and its calculation formula is as follows:
Figure PCTCN2021142298-appb-000086
Figure PCTCN2021142298-appb-000086
式中，n ubs,i为第i次故障通过黑启动恢复供电的用户数。 In the formula, n ubs,i is the number of users whose power supply is restored through black start for the i-th fault.
4)系统平均预安排停电时间4) The average pre-scheduled outage time of the system
预安排停电指电力部门有计划对相关区域进行停电检修或扩容等处理，适用于短时间不引起损害的可延迟故障修复。预停电主要依据失效率、故障率等指标进行判定。系统平均预安排停电时间计算公式如下：Pre-arranged power outages refer to the planned outage maintenance or capacity expansion of relevant areas by the power department, which is suitable for delayable fault repairs that do not cause damage in a short period of time. Pre-blackout is mainly judged based on indicators such as failure rate and failure rate. The formula for calculating the average pre-scheduled outage time of the system is as follows:
Figure PCTCN2021142298-appb-000087
Figure PCTCN2021142298-appb-000087
式中，t pc,i为第i次预安排停电时间，n upc,i为第i次预安排停电用户数。 In the formula, t pc,i is the i-th pre-scheduled power outage time, n upc,i is the number of i-th pre-scheduled power outage users.
5、协同力5. Synergy
协同力表征韧性电网合理高效利用内外部资源，共同集中力量抵御扰动事件的能力，与感知力一样，其作为基础特征为三大核心特征服务。协同力相关指标可用于提升和反映配电网对内外部防御资源、多维系统信息等的把控能力。Synergy represents the ability of the resilient grid to rationally and efficiently utilize internal and external resources, and jointly concentrate forces to resist disturbance events. Like perception, it serves as a basic feature for the three core features. The indicators related to synergy can be used to improve and reflect the ability of the distribution network to control internal and external defense resources and multi-dimensional system information.
1)配电线路联络率1) Contact ratio of distribution lines
作为最直观和基础的联络方式，配电线路的直接联络为区域内外间物理系统的调度配合提供了灵活性，同时其耦合元件的增加也为配电网提供了更高的量测冗余度。As the most intuitive and basic communication method, the direct connection of distribution lines provides flexibility for the scheduling and cooperation of physical systems inside and outside the region, and the increase of its coupling elements also provides higher measurement redundancy for the distribution network .
配电线路联络率E 1的计算表达式为： The calculation expression of distribution line connection rate E1 is:
Figure PCTCN2021142298-appb-000088
Figure PCTCN2021142298-appb-000088
式中，n l,H为区域中35～110kV高压线路总条数，n tl,H为区域中35～110kV高压联络线路条数，n l,L为区域中10(20)kV低压线路总条数，n tl,L为区域中10(20)kV低压联络线路条数，α l,H、α l,L分别为高压线路和低压线路指标权重，α l,H+α l,L＝1； In the formula, n l,H is the total number of 35-110kV high-voltage lines in the area, n tl,H is the number of 35-110kV high-voltage connection lines in the area, n l,L is the total number of 10(20)kV low-voltage lines in the area The number of lines, n tl,L is the number of 10(20)kV low-voltage connection lines in the area, α l,H , α l,L are the index weights of high-voltage lines and low-voltage lines respectively, α l,H +α l,L = 1;
优选地，本实施例给出配电网联络率最优权重配置的计算公式如下：Preferably, this embodiment provides the calculation formula for the optimal weight configuration of the distribution network connection ratio as follows:
Figure PCTCN2021142298-appb-000089
Figure PCTCN2021142298-appb-000089
式中，n l,H为区域中35～110kV高压线路总条数，n tl,H为区域中35～110kV高压联络线路条数，n l,L为区域中10(20)kV低压线路总条数，n tl,L为区域中10(20)kV低压联络线路条数。 In the formula, n l,H is the total number of 35-110kV high-voltage lines in the area, n tl,H is the number of 35-110kV high-voltage connection lines in the area, n l,L is the total number of 10(20)kV low-voltage lines in the area The number of lines, n tl,L is the number of 10(20)kV low-voltage contact lines in the area.
配电网联络率的计算公式中的系数可以根据实际情况进行调整，不做具体限定，本实施例提供的是配电网联络率的计算公式的最优系数。The coefficients in the formula for calculating the connection ratio of the distribution network can be adjusted according to actual conditions, and are not specifically limited. This embodiment provides the optimal coefficient of the formula for calculating the connection ratio of the distribution network.
2)配网转供率2) Distribution network transfer rate
线路转供可有效减少韧性电网在局部故障情况下的失负荷数量，发挥系统更大程度的协同应灾能力，同时也为配电网风险态势评估和决策效果模拟提供了更大灵活度。配网转供率计算公式如下：Line transfer can effectively reduce the number of lost loads in the case of partial faults in resilient power grids, give play to a greater degree of coordinated disaster response capabilities of the system, and also provide greater flexibility for distribution network risk situation assessment and decision-making effect simulation. The formula for calculating the distribution network transfer rate is as follows:
Figure PCTCN2021142298-appb-000090
Figure PCTCN2021142298-appb-000090
3)可协调柔性负荷比例3) Flexible load ratio can be coordinated
柔性负荷作为主动配电网的重要组成，承担着维持电力电量平衡和灾害协同恢复的责任。可协调柔性负荷比例决定了韧性电网协同抗扰的峰值能力，反映了柔性负荷对电网管理的协同作用，其计算公式如下：As an important component of the active distribution network, flexible loads are responsible for maintaining power balance and coordinated recovery from disasters. The proportion of coordinated flexible loads determines the peak capacity of the resilient grid’s collaborative anti-disturbance, reflecting the synergistic effect of flexible loads on grid management, and its calculation formula is as follows:
Figure PCTCN2021142298-appb-000091
Figure PCTCN2021142298-appb-000091
式中，S FL为可协调柔性负荷峰值。 In the formula, S FL is the peak value of adjustable flexible load.
式中，n l,tl为配网范围内可转供线路条数。 In the formula, n l, tl are the number of transferable lines within the distribution network range.
4)本地清洁能源消纳率4) Local clean energy consumption rate
清洁能源的消纳数量可综合体现韧性电网协同效果，与可协调柔性负荷比例不同，其动态表征了区域内外的电力电量协同平衡水平和灵活抗扰能力，具体计算公式如下：The amount of clean energy consumed can comprehensively reflect the synergistic effect of the resilient power grid. Different from the proportion of flexible loads that can be coordinated, it dynamically represents the coordinated balance level of power and electricity inside and outside the region and the flexible anti-disturbance capability. The specific calculation formula is as follows:
Figure PCTCN2021142298-appb-000092
Figure PCTCN2021142298-appb-000092
式中，P oi为区域外净受入电量，P oa为区域外协议电量，P co为本地清洁能源上网电量，P cg为本地清洁能源发电量。 In the formula, P oi is the net electricity received outside the region, P oa is the agreed electricity outside the region, P co is the on-grid electricity of local clean energy, and P cg is the power generation of local clean energy.
6、学习力6. Learning ability
学习力作为其余特征的共同支撑，表征韧性电网从历史经验中自我修正完善和结合新技术提升革新的能力。学习力相关指标可用于反映韧性配电网自主纠错和不断完善的能力。Learning ability, as the common support of the other features, represents the ability of the resilient grid to self-correct and improve from historical experience and combine new technologies to promote innovation. Indicators related to learning ability can be used to reflect the ability of autonomous error correction and continuous improvement of resilient distribution network.
1)态势预测数据与实际数据误差期望1) The error expectation between situation prediction data and actual data
结合历史运行数据和事故后风险态势复盘分析，可得到韧性电网各项预测数据与实际数据的误差，其误差期望及变化趋势可有效反映配电网的自我修正和自主完善能力，具体计算公式如下：Combined with the historical operation data and the post-accident risk situation review analysis, the error between the forecast data and the actual data of the resilient power grid can be obtained. The error expectation and change trend can effectively reflect the self-correction and self-improvement capabilities of the distribution network. The specific calculation formula as follows:
Figure PCTCN2021142298-appb-000093
Figure PCTCN2021142298-appb-000093
式中，T为量测的总时长，N z,t为t时刻感知系统预测的量测总数，
Figure PCTCN2021142298-appb-000094
为t时刻感知系统得到的第i项量测预估值，
Figure PCTCN2021142298-appb-000095
为t时刻第i项量测对应的系统状态真值。 In the formula, T is the total duration of measurement, N z,t is the total number of measurements predicted by the sensing system at time t,
Figure PCTCN2021142298-appb-000094
is the predicted value of the i-th measurement obtained by the perception system at time t,
Figure PCTCN2021142298-appb-000095
Measure the true value of the corresponding system state for the i-th item at time t.
2)灾后感知系统可修复漏洞比例2) Proportion of repairable vulnerabilities in the post-disaster perception system
灾后感知系统可修复的漏洞比例直观反映了韧性电网系统的漏洞辨识、纠错及自学习能力，其计算公式如下：The proportion of vulnerabilities that can be repaired by the post-disaster perception system directly reflects the vulnerability identification, error correction and self-learning capabilities of the resilient grid system. The calculation formula is as follows:
Figure PCTCN2021142298-appb-000096
Figure PCTCN2021142298-appb-000096
式中，n vf为感知系统灾后发现漏洞总数，n vr为感知系统灾后可修复漏洞数。 In the formula, n vf is the total number of vulnerabilities found in the perception system after the disaster, and n vr is the number of repairable vulnerabilities in the perception system after the disaster.
二、电网韧性综合评估赋权方法2. Power Grid Resilience Comprehensive Assessment and Empowerment Method
赋权方法按其依据可分为主观赋权法和客观赋权法，单一使用任一类方法均存在片面评估的可能性，因此本发明利用基于相对熵的综合赋权优化方法，优化二项系数法、反熵权法及CRITIC法得到的主客观权重，实现电网韧性综合评价的权重计算。The weighting method can be divided into subjective weighting method and objective weighting method according to its basis, and there is a possibility of one-sided evaluation in the single use of any type of method, so the present invention utilizes the comprehensive weighting optimization method based on relative entropy to optimize the binomial The subjective and objective weights obtained by the coefficient method, the anti-entropy weight method and the CRITIC method realize the weight calculation of the comprehensive evaluation of power grid resilience.
1、主观赋权法1. Subjective empowerment method
如图1所示，本实施例的主观赋权方式采用二项系数法，相比德尔菲法和AHP，二项系数法计算更为简便，且综合考虑各方意见，避免忽视小众观点。二项系数法流程图如图1所示，赋权步骤如下：As shown in Figure 1, the subjective weighting method of this embodiment adopts the binomial coefficient method. Compared with the Delphi method and AHP, the binomial coefficient method is easier to calculate, and comprehensively considers the opinions of all parties to avoid ignoring minority opinions. The flow chart of the binomial coefficient method is shown in Figure 1, and the weighting steps are as follows:
S101：由M位专家对共N项评估指标进行两两对比，独立得到指标集的重要度排序O m，排序值越小表示指标越重要。取各专家排序平均值得到第n项指标的平均重要度排序，公式如下： S101: M experts make a pairwise comparison of a total of N evaluation indicators, and independently obtain the ranking O m of the importance of the index set, and the smaller the ranking value, the more important the index. Take the average ranking of each expert to get the average importance ranking of the nth index, the formula is as follows:
Figure PCTCN2021142298-appb-000097
Figure PCTCN2021142298-appb-000097
S102：按照平均重要度排序从小到大的顺序重新排列N项评估指标，得到新的指标序列：S102: Rearrange the N evaluation indicators according to the order of average importance from small to large to obtain a new index sequence:
Figure PCTCN2021142298-appb-000098
Figure PCTCN2021142298-appb-000098
S103：做出指标集的对称排序，由排列结果计算二项系数：S103: Make a symmetrical sorting of the index set, and calculate the binomial coefficient from the sorting result:
x N,…,x 2,x 1,x 3,…,x N-1        (33) x N ,…,x 2 ,x 1 ,x 3 ,…,x N-1 (33)
S104：按对称排序指标集再次从左到右为各指标编号，记作i。即可根据编号排列结果确定二项系数计算得到各指标主观权重，公式如下：S104: sort the index set symmetrically and number each index again from left to right, denoted as i. The binomial coefficients can be determined according to the serial number results to calculate the subjective weight of each indicator, the formula is as follows:
Figure PCTCN2021142298-appb-000099
Figure PCTCN2021142298-appb-000099
式中，u i为指标编号为i的指标的主观权重，
Figure PCTCN2021142298-appb-000100
为指标排列组合的计算结果。 In the formula, u i is the subjective weight of the indicator whose index number is i,
Figure PCTCN2021142298-appb-000100
Computational results for indicator permutations.
2、客观赋权法2. Objective empowerment method
主观赋权法依赖于评估专家对于评价指标集的主观认知，存在随机偏差与片面性可能，须结合依赖客观数据的客观赋权法综合使用，本发明选用的客观赋权法为反熵权法与CRITIC法。反熵权法基于信息熵的概念，可有效评估指标给决策制定提供的信息质量，且避免了熵权法出现过小赋权的极端情况。同时，考虑到韧性电网中各关键特征高度耦合，因此补充使用适合于高相关性指标赋权的CRITIC法来提高客观赋权的有效性。The subjective weighting method relies on the subjective cognition of evaluation experts on the evaluation index set, and there is a possibility of random deviation and one-sidedness. It must be used in combination with the objective weighting method that relies on objective data. The objective weighting method selected in the present invention is the anti-entropy weighting method with the CRITIC Act. The anti-entropy weight method is based on the concept of information entropy, which can effectively evaluate the quality of information provided by indicators for decision-making, and avoids the extreme situation of too small weighting in the entropy weight method. At the same time, considering that the key features of the resilient grid are highly coupled, the CRITIC method, which is suitable for high correlation index weighting, is supplemented to improve the effectiveness of objective weighting.
假设共M个待选方案，每个方案包括N项评价指标，用x mn表示第m个方案的第n项指标实际计算数值。由于各微观指标实际计算数值范围相差较大，且存在不同量纲，不利于确定其客观权重，因此首先对各指标进行归一化处理，具体公式如下： Assuming that there are M candidate schemes in total, and each scheme includes N evaluation indicators, x mn represents the actual calculated value of the nth indicator of the mth scheme. Since the actual calculation value range of each micro-indicator is quite different, and there are different dimensions, it is not conducive to determine its objective weight. Therefore, each indicator is first normalized, and the specific formula is as follows:
1)效益型指标，即指标值与所评估能力正相关。1) Benefit-type indicators, that is, the index value is positively correlated with the evaluated ability.
Figure PCTCN2021142298-appb-000101
Figure PCTCN2021142298-appb-000101
1)成本型指标，即指标值与所评估能力负相关。1) Cost-type indicators, that is, the indicator value is negatively correlated with the assessed ability.
Figure PCTCN2021142298-appb-000102
Figure PCTCN2021142298-appb-000102
归一化后各指标值y mn均为取值范围为0～1的无量纲常数，且指标值越大，反映方案的该项能力越强。下面将分别介绍反熵权法和CRITIC法的具体权重计算流程。 After normalization, each index value y mn is a dimensionless constant with a range of 0 to 1, and the larger the index value, the stronger the ability to reflect the scheme. The specific weight calculation process of the anti-entropy weight method and the CRITIC method will be introduced below.
3、反熵权法3. Anti-entropy weight method
反熵权法赋权流程图如图2所示，具体步骤如下：The weighting flow chart of the anti-entropy weight method is shown in Figure 2, and the specific steps are as follows:
S201：获取归一化指标；S201: Obtain a normalized index;
S202：计算各指标的反熵值h n，公式如下： S202: Calculate the anti-entropy value h n of each index, the formula is as follows:
Figure PCTCN2021142298-appb-000103
Figure PCTCN2021142298-appb-000103
Figure PCTCN2021142298-appb-000104
Figure PCTCN2021142298-appb-000104
S203：根据反熵值进一步确定各指标权重，公式如下：S203: Further determine the weight of each index according to the anti-entropy value, the formula is as follows:
Figure PCTCN2021142298-appb-000105
Figure PCTCN2021142298-appb-000105
4、CRITIC法4. CRITIC method
CRITIC法赋权流程如图3所示，具体步骤如下：The empowerment process of the CRITIC law is shown in Figure 3, and the specific steps are as follows:
S301：获取归一化指标；S301: Obtain a normalized index;
S302：计算各指标的冗余信息熵p n，公式如下： S302: Calculate the redundant information entropy p n of each index, the formula is as follows:
Figure PCTCN2021142298-appb-000106
Figure PCTCN2021142298-appb-000106
Figure PCTCN2021142298-appb-000107
Figure PCTCN2021142298-appb-000107
S303：利用归一化矩阵各列间协方差和指标的变异系数s n计算各指标间的相关系数，公式如下： S303: Using the covariance among the columns of the normalized matrix and the coefficient of variation s n of the indicators to calculate the correlation coefficient between the indicators, the formula is as follows:
Figure PCTCN2021142298-appb-000108
Figure PCTCN2021142298-appb-000108
Figure PCTCN2021142298-appb-000109
Figure PCTCN2021142298-appb-000109
Figure PCTCN2021142298-appb-000110
Figure PCTCN2021142298-appb-000110
式中，
Figure PCTCN2021142298-appb-000111
为第n项指标的归一化值，s n为第n项指标的变异系数，N为指标的总数，
Figure PCTCN2021142298-appb-000112
为第n项和第n *项的相关系数，
Figure PCTCN2021142298-appb-000113
为第n *项的指标值，
Figure PCTCN2021142298-appb-000114
为指标值y n和
Figure PCTCN2021142298-appb-000115
间的协方差，
Figure PCTCN2021142298-appb-000116
为第n *项的变异系数。 In the formula,
Figure PCTCN2021142298-appb-000111
is the normalized value of the nth index, s n is the variation coefficient of the nth index, N is the total number of indexes,
Figure PCTCN2021142298-appb-000112
is the correlation coefficient between the nth item and the n * th item,
Figure PCTCN2021142298-appb-000113
is the index value of the n * th item,
Figure PCTCN2021142298-appb-000114
is the index value y n and
Figure PCTCN2021142298-appb-000115
The covariance between
Figure PCTCN2021142298-appb-000116
is the coefficient of variation of the n * th term.
S304：评估各指标所包含的信息量，公式如下：S304: Evaluate the amount of information contained in each indicator, the formula is as follows:
Figure PCTCN2021142298-appb-000117
Figure PCTCN2021142298-appb-000117
S305：根据信息量确定指标权重：S305: Determine the index weight according to the amount of information:
Figure PCTCN2021142298-appb-000118
Figure PCTCN2021142298-appb-000118
5、综合权重优化5. Comprehensive weight optimization
在得到主客观各赋权结果后，考虑基于相对熵的主客观偏好系数确定方式，基于相对熵的综合权重优化流程如图4所示，其优化步骤如下：After obtaining the subjective and objective weighting results, consider the method of determining the subjective and objective preference coefficients based on relative entropy. The comprehensive weight optimization process based on relative entropy is shown in Figure 4. The optimization steps are as follows:
S401：对M种赋权方式得到的各权重向量u m＝(u m1,u m2,…,u mN)，基于相对熵的原理根据各权重向量通过优化模型求取集合权重，集合权重为求取综合权重过程中的一个中间变量。 S401: For each weight vector u m = (u m1 , u m2 ,..., u mN ) obtained by M kinds of weighting methods, based on the principle of relative entropy, the set weight is obtained through the optimization model according to each weight vector, and the set weight is calculated as An intermediate variable in the process of taking comprehensive weights.
具体优化模型可参见现有技术，如以下模型公式：The specific optimization model can refer to the prior art, such as the following model formula:
Figure PCTCN2021142298-appb-000119
Figure PCTCN2021142298-appb-000119
本实施例直接给出第n个二级评价指标的集合权重d n的计算公式如下： This embodiment directly provides the calculation formula of the set weight d n of the nth secondary evaluation index as follows:
Figure PCTCN2021142298-appb-000120
Figure PCTCN2021142298-appb-000120
S402：计算每种赋权方式结果与集合权重间的相对熵，表征该赋权方法结果与集合权重的接近度，公式如下：S402: Calculate the relative entropy between the result of each weighting method and the set weight, and characterize the closeness between the result of the weighting method and the set weight, the formula is as follows:
Figure PCTCN2021142298-appb-000121
Figure PCTCN2021142298-appb-000121
S403：依据贴近度得到赋权方法的偏好系数，接近度越大，表示该方法在综合权重确定中起到的作用越大，其偏好系数也越高，计算公式如下：S403: Obtain the preference coefficient of the weighting method according to the degree of proximity. The greater the degree of proximity, the greater the role of the method in determining the comprehensive weight, and the higher the preference coefficient. The calculation formula is as follows:
Figure PCTCN2021142298-appb-000122
Figure PCTCN2021142298-appb-000122
S404：根据偏好系数得到结合主客观赋权的综合指标权重系数：S404: According to the preference coefficient, the comprehensive index weight coefficient combined with subjective and objective weighting is obtained:
Figure PCTCN2021142298-appb-000123
Figure PCTCN2021142298-appb-000123
因此，依据上述各节内容，得到配电网韧性综合评价流程如图5所示，具体包括以下步骤：Therefore, based on the contents of the above sections, the comprehensive evaluation process of distribution network resilience is obtained as shown in Figure 5, which specifically includes the following steps:
S1：构建配电网韧性综合评价指标体系；S1: Build a comprehensive evaluation index system for distribution network resilience;
S2：根据配电网的参数数据，计算配电网韧性综合评价指标体系中各项微观指标的指标值；S2: According to the parameter data of the distribution network, calculate the index value of each micro index in the comprehensive evaluation index system of distribution network resilience;
S3：计算各一级评价指标和二级评价指标的主观权重和客观权重；S3: Calculate the subjective weight and objective weight of each first-level evaluation index and second-level evaluation index;
S4：通过综合权重优化各指标的主观权重和客观权重，得到最终权重；S4: Optimizing the subjective weight and objective weight of each indicator through the comprehensive weight to obtain the final weight;
S5：根据和指标的最终权重和计算的指标值，获取最终的评价结果。S5: Obtain the final evaluation result according to the final weight of the index and the calculated index value.
本实施例还提供一种配电网的韧性综合评估系统，包括存储器和处理器，所述存储器存储有计算机程序，处理器调用所述计算机程序执行如上所述的配电网的韧性综合评估方法的步骤。This embodiment also provides a system for comprehensively evaluating resilience of a distribution network, including a memory and a processor, the memory stores a computer program, and the processor invokes the computer program to execute the method for comprehensively evaluating resilience of a distribution network as described above A step of.
以上详细描述了本发明的较佳具体实施例。应当理解，本领域的普通技术人员无需创造性劳动就可以根据本发明的构思做出诸多修改和变化。因此，凡本技术领域中技术人员依本发明的构思在现有技术的基础上通过逻辑分析、推理或者有限的实验可以得到的技术方案，皆应在由权利要求书所确定的保护范围内。The preferred specific embodiments of the present invention have been described in detail above. It should be understood that those skilled in the art can make many modifications and changes according to the concept of the present invention without creative efforts. Therefore, all technical solutions that can be obtained by those skilled in the art based on the concept of the present invention through logical analysis, reasoning or limited experiments on the basis of the prior art shall be within the scope of protection defined by the claims.

Claims (20)

  1. 一种配电网的韧性综合评估方法，其特征在于，包括以下步骤：A method for comprehensively assessing the resilience of a distribution network, characterized in that it comprises the following steps:
    获取配电网参数，根据预设的配电网韧性综合评价体系，进行评估；所述配电网韧性综合评价体系包括一级评价指标和二级评价指标，每个所述一级评价指标均设有对应的二级评价指标；Obtain distribution network parameters, and evaluate according to the preset distribution network resilience comprehensive evaluation system; the distribution network resilience comprehensive evaluation system includes first-level evaluation indicators and second-level evaluation indicators, and each of the first-level evaluation indicators is There are corresponding secondary evaluation indicators;
    所述配电网韧性综合评价体系的一级评价指标包括感知力、应变力、防御力、恢复力、协同力和学习力；The first-level evaluation indicators of the distribution network resilience comprehensive evaluation system include perception, response, defense, resilience, synergy and learning;
    所述感知力对应的二级评价指标包括智能电表覆盖率、薄弱节点可观度、电网量测冗余度、平均传输延时、态势可视度和配电自动化系统运行指标中的一个或多个；The secondary evaluation index corresponding to the perception includes one or more of smart meter coverage, weak node observability, power grid measurement redundancy, average transmission delay, situation visibility and distribution automation system operation index ;
    所述协同力对应的二级评价指标包括配电线路联络率、可协调柔性负荷比例、配网转供率和本地清洁能源消纳率中的一个或多个；The secondary evaluation index corresponding to the synergy includes one or more of distribution line connection rate, coordinated flexible load ratio, distribution network transfer rate and local clean energy consumption rate;
    所述学习力对应的二级评价指标包括态势预测数据与实际数据误差期望和灾后感知系统可修复漏洞比例中的一个或多个；The secondary evaluation index corresponding to the learning ability includes one or more of the error expectation between the situation prediction data and the actual data and the ratio of repairable loopholes in the post-disaster perception system;
    基于各个二级评价指标的评估结果，根据预设的各个二级评价指标的权重以及各个一级评价指标的权重，进行综合计算，获取配电网的韧性综合评估结果。Based on the evaluation results of each secondary evaluation index, according to the preset weight of each secondary evaluation index and the weight of each first-level evaluation index, a comprehensive calculation is performed to obtain the comprehensive evaluation result of the resilience of the distribution network.
  2. 根据权利要求1所述的一种配电网的韧性综合评估方法，其特征在于，所述感知力对应的二级评价指标中，所述智能电表覆盖率A 1的计算表达式为： The method for comprehensively evaluating resilience of a distribution network according to claim 1, wherein, in the secondary evaluation index corresponding to the perception force, the calculation expression of the smart meter coverage A1 is:
    Figure PCTCN2021142298-appb-100001
    Figure PCTCN2021142298-appb-100001
    式中，n sm表示电网区域内的智能电表数量，n m表示电网区域内的总电表数； In the formula, n sm represents the number of smart meters in the grid area, and n m represents the total number of meters in the grid area;
    所述薄弱节点可观度A 2的计算表达式为： The calculation expression of the observability A2 of the weak node is:
    Figure PCTCN2021142298-appb-100002
    Figure PCTCN2021142298-appb-100002
    式中，n wm表示可观薄弱节点的数量，n w表示薄弱节点总数； In the formula, n wm represents the number of considerable weak nodes, and n w represents the total number of weak nodes;
    所述电网量测冗余度A 3的计算表达式为： The calculation expression of the grid measurement redundancy A3 is:
    Figure PCTCN2021142298-appb-100003
    Figure PCTCN2021142298-appb-100003
    式中，n pm表示可观节点的数量，n p表示电网节点总数。 In the formula, n pm represents the number of considerable nodes, and n p represents the total number of grid nodes.
  3. 根据权利要求1所述的一种配电网的韧性综合评估方法，其特征在于，所述感知力对应的二级评价指标中，所述平均传输延时A 4的计算表达式为： The method for comprehensively evaluating the resilience of a distribution network according to claim 1, wherein, in the secondary evaluation index corresponding to the perception force, the calculation expression of the average transmission delay A4 is:
    Figure PCTCN2021142298-appb-100004
    Figure PCTCN2021142298-appb-100004
    式中，t mi表示电表i采集量测量的时刻，t ui表示电表i量测数据更新至数据库的时刻，n m表示电网区域内的总电表数； In the formula, t mi represents the time when meter i collects and measures, t ui represents the time when the measurement data of electric meter i is updated to the database, and n m represents the total number of electric meters in the grid area;
    所述态势可视度A 5的计算表达式为： The calculation expression of the situational visibility A5 is:
    Figure PCTCN2021142298-appb-100005
    Figure PCTCN2021142298-appb-100005
    式中，n为态势图划分的区块数量，N i为区块i中的节点数量，
    Figure PCTCN2021142298-appb-100006
    为N i的算术平均值；     In the formula, n is the number of blocks divided by the situation graph, N i is the number of nodes in block i,
    Figure PCTCN2021142298-appb-100006
    is the arithmetic mean of N i ;
    所述配电自动化系统运行指标A 6的计算表达式为： The calculation expression of the operation index A6 of the distribution automation system is:
    A 6＝α aor×P aor+α rs×P rs+α rc×P rc+α fac×P fac A 6 ＝α aor ×P aor +α rs ×P rs +α rc ×P rc +α fac ×P fac
    式中，P aor表示配电自动化终端平均在线率，P rs表示遥控成功率，P rc表示遥信动作正确率，P fac表示馈线自动化成功率，α aor、α rs、α rc、α fac为各项指标对应权重，α aor+α rs+α rc+α fac＝1。 In the formula, P aor represents the average online rate of distribution automation terminals, P rs represents the success rate of remote control, P rc represents the correct rate of remote signaling action, P fac represents the success rate of feeder automation, α aor , α rs , α rc , and α fac are Each index corresponds to the weight, α aor + α rs + α rc + α fac =1.
  4. 根据权利要求1所述的一种配电网的韧性综合评估方法，其特征在于，所述协同力对应的二级评价指标中，所述配电线路联络率E 1的计算表达式为： The comprehensive evaluation method for resilience of a distribution network according to claim 1, wherein, in the secondary evaluation index corresponding to the synergy, the calculation expression of the connection rate E of the distribution line is:
    Figure PCTCN2021142298-appb-100007
    Figure PCTCN2021142298-appb-100007
    式中，n l,H为区域中35～110kV高压线路总条数，n tl,H为区域中35～110kV高压联络线路条数，n l,L为区域中10(20)kV低压线路总条数，n tl,L为区域中10(20)kV低压联络线路条数，α l,H、α l,L分别为高压线路和低压线路指标权重，α l,H+α l,L＝1； In the formula, n l,H is the total number of 35-110kV high-voltage lines in the area, n tl,H is the number of 35-110kV high-voltage connection lines in the area, n l,L is the total number of 10(20)kV low-voltage lines in the area The number of lines, n tl,L is the number of 10(20)kV low-voltage connection lines in the area, α l,H , α l,L are the index weights of high-voltage lines and low-voltage lines respectively, α l,H +α l,L = 1;
    所述配网转供率E 2的计算表达式为： The calculation expression of the distribution network transfer rate E2 is:
    Figure PCTCN2021142298-appb-100008
    Figure PCTCN2021142298-appb-100008
    式中，n l,tl为配网范围内可转供线路条数，n l为线路总条数。 In the formula, n l, tl are the number of transferable lines within the scope of the distribution network, and n l is the total number of lines.
  5. 根据权利要求1所述的一种配电网的韧性综合评估方法，其特征在于，所述协同力对应的二级评价指标中，所述可协调柔性负荷比例E 3的计算表达式为： The method for comprehensively evaluating the toughness of a distribution network according to claim 1, wherein, in the secondary evaluation index corresponding to the synergy force, the calculation expression of the coordinated flexible load ratio E3 is:
    Figure PCTCN2021142298-appb-100009
    Figure PCTCN2021142298-appb-100009
    式中，S FL为可协调柔性负荷峰值，S L,max为年网供最大负荷； In the formula, S FL is the peak value of the coordinated flexible load, and S L,max is the maximum load of the annual network supply;
    所述本地清洁能源消纳率E 4的计算表达式为： The calculation expression of the local clean energy consumption rate E4 is:
    Figure PCTCN2021142298-appb-100010
    Figure PCTCN2021142298-appb-100010
    式中，P oi为区域外净受入电量，P oa为区域外协议电量，P co为本地清洁能源上网电量，P cg为本地清洁能源发电量。 In the formula, P oi is the net electricity received outside the region, P oa is the agreed electricity outside the region, P co is the on-grid electricity of local clean energy, and P cg is the power generation of local clean energy.
  6. 根据权利要求1所述的一种配电网的韧性综合评估方法，其特征在于，所述学习力对应的二级评价指标中，所述态势预测数据与实际数据误差期望F 1的计算表达式为： The comprehensive evaluation method for resilience of a distribution network according to claim 1, wherein, in the secondary evaluation index corresponding to the learning ability, the calculation expression of the error expectation F between the situation prediction data and the actual data for:
    Figure PCTCN2021142298-appb-100011
    Figure PCTCN2021142298-appb-100011
    式中，T为量测的总时长，N z,t为t时刻感知系统预测的量测总数，
    Figure PCTCN2021142298-appb-100012
    为t时刻感知系统得到的第i项量测预估值，h(x true，i)为t时刻第i项量测对应的系统状态真值；     In the formula, T is the total duration of measurement, N z,t is the total number of measurements predicted by the sensing system at time t,
    Figure PCTCN2021142298-appb-100012
    h(x true, i ) is the true value of the system state corresponding to the i-th measurement at time t;
    所述灾后感知系统可修复漏洞比例F 2的计算表达式为： The calculation expression of the repairable vulnerability ratio F2 of the post-disaster awareness system is:
    Figure PCTCN2021142298-appb-100013
    Figure PCTCN2021142298-appb-100013
    式中，n vf为感知系统灾后发现漏洞总数，n vr为感知系统灾后可修复漏洞数。 In the formula, n vf is the total number of vulnerabilities found in the perception system after the disaster, and n vr is the number of repairable vulnerabilities in the perception system after the disaster.
  7. 根据权利要求1所述的一种配电网的韧性综合评估方法，其特征在于，所述应变力对应的二级评价指标包括电压暂变率、潮流越限率、电压谐波畸变率、频率偏差率、配电需要率、N-1校验通过率、有功备用率和拓扑完整度中的一个或多个。The comprehensive evaluation method for resilience of distribution network according to claim 1, characterized in that, the secondary evaluation index corresponding to the strain force includes voltage transient rate, power flow limit rate, voltage harmonic distortion rate, frequency One or more of deviation rate, power distribution requirement rate, N-1 verification pass rate, active power reserve rate, and topology integrity.
  8. 根据权利要求7所述的一种配电网的韧性综合评估方法，其特征在于，所述电压暂变率B 1的计算表达式为： The method for comprehensively evaluating the resilience of a distribution network according to claim 7, wherein the calculation expression of the voltage transient rate B1 is:
    Figure PCTCN2021142298-appb-100014
    Figure PCTCN2021142298-appb-100014
    Figure PCTCN2021142298-appb-100015
    Figure PCTCN2021142298-appb-100015
    式中，n p为电压暂变次数，V i tc(t)为节点i当前暂态时刻的电压暂变量，V i,max为节点i的暂态上限电压，V i,min为节点i的暂态下限电压，V i(t)指节点i当前暂态时刻的电压，T为统计周期； In the formula, n p is the number of voltage transient changes, V i tc (t) is the voltage transient variable at the current transient moment of node i, V i,max is the transient upper limit voltage of node i, V i,min is the voltage of node i Transient lower limit voltage, V i (t) refers to the voltage of node i at the current transient moment, T is the statistical period;
    所述潮流越限率B 2的计算表达式为： The calculation expression of the power flow limit rate B2 is:
    Figure PCTCN2021142298-appb-100016
    Figure PCTCN2021142298-appb-100016
    Figure PCTCN2021142298-appb-100017
    Figure PCTCN2021142298-appb-100017
    式中，
    Figure PCTCN2021142298-appb-100018
    为支路i在t时刻的潮流越限量，S i,max为支路i的额定潮流上限，S i(t)为支路i在t时刻的潮流大小，n l为电网支路总数；     In the formula,
    Figure PCTCN2021142298-appb-100018
    is the power flow limit of branch i at time t, S i,max is the rated power flow upper limit of branch i, S i (t) is the power flow of branch i at time t, and n l is the total number of power grid branches;
    所述电压谐波畸变率B 3的计算表达式为： The calculation expression of the voltage harmonic distortion rate B3 is:
    Figure PCTCN2021142298-appb-100019
    Figure PCTCN2021142298-appb-100019
    式中，V 1,i为节点i的基波电压有效值，V k,i为节点i的第k次谐波电压有效值，n p为总节点数； In the formula, V 1,i is the effective value of the fundamental wave voltage of node i, V k,i is the effective value of the kth harmonic voltage of node i, and n p is the total number of nodes;
    所述频率偏差率B 4的计算表达式为： The calculation expression of the frequency deviation rate B4 is:
    Figure PCTCN2021142298-appb-100020
    Figure PCTCN2021142298-appb-100020
    式中，f为系统当前频率，f N为额定频率，Δf th为频率偏差限值。 In the formula, f is the current frequency of the system, f N is the rated frequency, and Δf th is the frequency deviation limit.
  9. 根据权利要求7所述的一种配电网的韧性综合评估方法，其特征在于，所述配电需要率B 5的计算表达式为： The method for comprehensively evaluating the resilience of a distribution network according to claim 7, wherein the calculation expression of the distribution demand rate B5 is:
    Figure PCTCN2021142298-appb-100021
    Figure PCTCN2021142298-appb-100021
    式中，P a为韧性电网用户实际用电总功率，P N为韧性电网用户总额定频率； In the formula, P a is the total power actually consumed by users of the resilient grid, and P N is the total rated frequency of users of the resilient grid;
    所述N-1校验通过率B 6的计算表达式为： The calculation expression of the N-1 verification pass rate B6 is:
    Figure PCTCN2021142298-appb-100022
    Figure PCTCN2021142298-appb-100022
    式中，n t为电网范围内变电站总数，n t(N-1)为通过N-1校验的变电站数，n l为电网范围内线路总数，n l(N-1)为通过N-1校验的线路数，α t、α l分别为变电站和线路指标权重，α t+α l＝1； In the formula, n t is the total number of substations within the power grid, n t(N-1) is the number of substations passing N-1 verification, n l is the total number of lines within the power grid, and n l(N-1) is the number of substations passing N-1 1 The number of lines to be verified, α t and α l are the index weights of substation and line respectively, α t + α l = 1;
    所述有功备用率B 7的计算表达式为： The calculation expression of described active power reserve ratio B7 is:
    Figure PCTCN2021142298-appb-100023
    Figure PCTCN2021142298-appb-100023
    式中，P r为电网有功备用容量，P r.lim为电网有功备用容量限值； In the formula, P r is the active power reserve capacity of the power grid, and P r.lim is the limit value of the power grid active power reserve capacity;
    所述拓扑完整度B 8的计算表达式为： The calculation expression of the topological integrity B8 is:
    Figure PCTCN2021142298-appb-100024
    Figure PCTCN2021142298-appb-100024
    式中，s i(t)为时刻t下线路i的运行状态，当线路i正常运行时，s i(t)＝1，当线路i停运时，s i(t)＝0，T为统计周期，n l为总线路数。 In the formula, s i (t) is the operating state of line i at time t, when line i is in normal operation, s i (t) = 1, when line i is out of service, s i (t) = 0, T is Statistical cycle, n l is the total number of lines.
  10. 根据权利要求1所述的一种配电网的韧性综合评估方法，其特征在于，所述防御力对应的二级评价指标包括性能指数、配电容载比和电网故障率中的一个或多个。A method for comprehensively evaluating the resilience of distribution networks according to claim 1, wherein the secondary evaluation indicators corresponding to the defense force include one or more of performance index, distribution capacity-to-load ratio, and grid failure rate .
  11. 根据权利要求10所述的一种配电网的韧性综合评估方法，其特征在于，所述性能指数C 1的计算表达式为： The method for comprehensively evaluating the resilience of a distribution network according to claim 10, wherein the calculation expression of the performance index C1 is:
    Figure PCTCN2021142298-appb-100025
    Figure PCTCN2021142298-appb-100025
    式中，P o为灾害前原始电网容量，P d为采取主动防御措施后的电网容量，P low为电网性能降至最低水平时的容量，t low为电网性能降至最低水平时的时间，t d为采取主动防御措施的时间； In the formula, P o is the original grid capacity before the disaster, P d is the grid capacity after taking active defense measures, P low is the capacity when the grid performance drops to the lowest level, and t low is the time when the grid performance drops to the lowest level, t d is the time for taking active defense measures;
    所述配网容载比C 2的计算表达式为： The calculation expression of the distribution network capacity load ratio C2 is:
    Figure PCTCN2021142298-appb-100026
    Figure PCTCN2021142298-appb-100026
    式中，S T为配网变电设备总容量，S L,max为年网供最大负荷； In the formula, S T is the total capacity of distribution network substation equipment, S L,max is the maximum load of annual network supply;
    所述电网故障率C 3的计算表达式为： The calculation expression of the grid failure rate C3 is:
    Figure PCTCN2021142298-appb-100027
    Figure PCTCN2021142298-appb-100027
    式中，n pe为电网内电力设备总数，p fault,i为设备i的故障概率。 In the formula, n pe is the total number of power equipment in the grid, and p fault,i is the failure probability of equipment i.
  12. 根据权利要求1所述的一种配电网的韧性综合评估方法，其特征在于，所述恢复力对应的二级评价指标包括用户平均停电时间、故障自愈率、黑启动成功率和系统平均预安排停电时间中的一个或多个。The comprehensive evaluation method for resilience of distribution network according to claim 1, characterized in that, the secondary evaluation index corresponding to the resilience includes average power outage time of users, fault self-healing rate, black start success rate and system average One or more of the pre-scheduled outage times.
  13. 根据权利要求12所述的一种配电网的韧性综合评估方法，其特征在于，所述用户平均停电时间D 1的计算表达式为： The method for comprehensively evaluating resilience of a distribution network according to claim 12, wherein the calculation expression of the user average power outage time D1 is:
    Figure PCTCN2021142298-appb-100028
    Figure PCTCN2021142298-appb-100028
    式中，t cut为第i次故障停电持续时间，n ucut,i为第i次故障停电用户数，n u为电网总用户数； In the formula, t cut is the power outage duration of the i-th fault, n ucut,i is the number of users of the i-th fault power outage, and n u is the total number of users of the power grid;
    所述故障自愈率D 2的计算表达式为： The calculation expression of the fault self-healing rate D2 is:
    Figure PCTCN2021142298-appb-100029
    Figure PCTCN2021142298-appb-100029
    式中，n ush,i为第i次故障自愈用户数，n ufault,i为第i次故障影响的总用户数； In the formula, n ush,i is the number of self-healing users of the i-th fault, and n ufault,i is the total number of users affected by the i-th fault;
    所述黑启动成功率D 3的计算表达式为： The calculation expression of described black start success rate D3 is:
    Figure PCTCN2021142298-appb-100030
    Figure PCTCN2021142298-appb-100030
    式中，n ubs,i为第i次故障通过黑启动恢复供电的用户数，n ufault,i为第i次故障影响的总用户数。 In the formula, n ubs,i is the number of users whose power supply is restored through black start for the i-th fault, and n ufault,i is the total number of users affected by the i-th fault.
  14. 根据权利要求12所述的一种配电网的韧性综合评估方法，其特征在于，所述系统平均预安排停电时间D 4的计算表达式为： The method for comprehensively assessing the resilience of a distribution network according to claim 12, wherein the calculation expression of the average prearranged power outage time D4 of the system is:
    Figure PCTCN2021142298-appb-100031
    Figure PCTCN2021142298-appb-100031
    式中，t pc,i为第i次预安排停电时间，n upc,i为第i次预安排停电用户数，n u为电网总用户数。 In the formula, t pc,i is the i-th pre-scheduled power outage time, n upc,i is the number of pre-scheduled power outage users for the i-th time, and n u is the total number of power grid users.
  15. 根据权利要求1所述的一种配电网的韧性综合评估方法，其特征在于，所述二级评价指标和一级评价指标的权重的设定过程均包括以下步骤：The method for comprehensively evaluating the resilience of a distribution network according to claim 1, wherein the setting process of the weight of the secondary evaluation index and the primary evaluation index all includes the following steps:
    主观赋权步骤：对各项指标进行主观赋权；Subjective weighting step: carry out subjective weighting on each indicator;
    客观赋权步骤：对各项指标进行客观赋权；Objective empowerment step: objectively empower each indicator;
    综合权重优化步骤：获取所述主观赋权步骤和客观赋权步骤中各赋权方法得到的权重向量；从而计算各赋权方法整体的集合权重，所述集合权重的计算表达式为：Comprehensive weight optimization step: obtaining the weight vector obtained by each weighting method in the subjective weighting step and the objective weighting step; thereby calculating the overall set weight of each weighting method, and the calculation expression of the set weight is:
    Figure PCTCN2021142298-appb-100032
    Figure PCTCN2021142298-appb-100032
    式中，M为赋权方法的总数，u m＝(u m1,u m2,…,u mN)为第m个赋权方法的权重向量，u mn为第m个赋权方法获得的第n个指标的权重，N为指标的总数，d n为集合权重； In the formula, M is the total number of weighting methods, u m =(u m1 ,u m2 ,…,u mN ) is the weight vector of the mth weighting method, u mn is the nth weighting method obtained by the mth weighting method The weight of indicators, N is the total number of indicators, d n is the set weight;
    计算每种赋权方法结果与所述集合权重间的相对熵，该相对熵的计算表达式为：Calculate the relative entropy between the result of each weighting method and the set weight, the calculation expression of the relative entropy is:
    Figure PCTCN2021142298-appb-100033
    Figure PCTCN2021142298-appb-100033
    式中，h(u m,d)为第m个赋权方法的权重向量与集合权重间的相对熵； In the formula, h(u m ,d) is the relative entropy between the weight vector of the mth weighting method and the set weight;
    根据所述相对熵，计算每种赋权方法的偏好系数，该偏好系数的计算表达式为：According to the relative entropy, calculate the preference coefficient of each weighting method, the calculation expression of the preference coefficient is:
    Figure PCTCN2021142298-appb-100034
    Figure PCTCN2021142298-appb-100034
    式中，a m为第m个赋权方法的偏好系数； In the formula, a m is the preference coefficient of the mth weighting method;
    根据所述偏好系数计算各指标的综合指标权重系数，该综合指标权重系数的计算表达式为：The comprehensive index weight coefficient of each index is calculated according to the preference coefficient, and the calculation expression of the comprehensive index weight coefficient is:
    Figure PCTCN2021142298-appb-100035
    Figure PCTCN2021142298-appb-100035
    式中，w n为第n个指标的综合指标权重系数。 In the formula, w n is the comprehensive index weight coefficient of the nth index.
  16. 根据权利要求15所述的一种配电网的韧性综合评估方法，其特征在于，所述主观赋权步骤包括：采用二项系数法对各项指标进行主观赋权，所述二项系数法包括以下步骤：A method for comprehensively evaluating the resilience of distribution networks according to claim 15, wherein the subjective weighting step comprises: using the binomial coefficient method to subjectively weight each index, and the binomial coefficient method Include the following steps:
    由M位专家对共N项评估指标进行两两对比，独立得到指标集的重要度排序O m，取各专家排序平均值得到第n项指标的平均重要度排序，该第n项指标的平均重要度排序的计算表达式为： M experts make a pairwise comparison of a total of N evaluation indicators, and independently obtain the importance ranking O m of the index set, and take the average ranking of each expert to obtain the average importance ranking of the nth index, and the average of the nth index The calculation expression for importance ranking is:
    Figure PCTCN2021142298-appb-100036
    Figure PCTCN2021142298-appb-100036
    式中，O(x n)为第n项指标的平均重要度排序，O m(n)为第m个对第n项指标的重要度排序； In the formula, O(x n ) is the average importance ranking of the nth index, and O m (n) is the importance ranking of the mth index to the nth index;
    按照平均重要度排序从小到大的顺序重新排列N项评估指标，得到新的指标序列：Rearrange the N evaluation indicators according to the order of average importance from small to large, and get a new index sequence:
    Figure PCTCN2021142298-appb-100037
    Figure PCTCN2021142298-appb-100037
    式中，x 1,x 2,…,x N为排序后的评估指标； In the formula, x 1 , x 2 ,…, x N are the sorted evaluation indicators;
    做出指标集的对称排序：Make a symmetric ordering of an index set:
    x N,…,x 2,x 1,x 3,…,x N-1 x N ,…,x 2 ,x 1 ,x 3 ,…,x N-1
    按对称排序指标集再次从左到右为各指标编号，记作i，即可计算得到各指标主观权重，所述各指标主观权重的计算表达式为：Sorting index sets according to symmetry again numbers each index from left to right, denoted as i, then the subjective weight of each index can be calculated, and the calculation expression of the subjective weight of each index is:
    Figure PCTCN2021142298-appb-100038
    Figure PCTCN2021142298-appb-100038
    式中，u i为指标编号为i的指标的主观权重，
    Figure PCTCN2021142298-appb-100039
    为指标排列组合的计算结果。     In the formula, u i is the subjective weight of the indicator whose index number is i,
    Figure PCTCN2021142298-appb-100039
    Computational results for indicator permutations.
  17. 根据权利要求15所述的一种配电网的韧性综合评估方法，其特征在于，所述客观赋权步骤执行前还包括：对各指标进行归一化处理，该归一化处理具体为：According to claim 15, a method for comprehensively evaluating resilience of a distribution network, characterized in that before the execution of the objective weighting step, it also includes: performing normalization processing on each index, and the normalization processing is specifically:
    效益型指标的归一化处理表达式为：The normalized processing expression of the benefit index is:
    Figure PCTCN2021142298-appb-100040
    Figure PCTCN2021142298-appb-100040
    式中，x mn为第m个待选方案的第n项指标实际计算数值，y mn′为第m个待选方案的第n项指标的效益型指标归一化值，x n,min为第n项指标的最小值，x n,max为第n项指标的最大值，所述待选方案为采用所述指标获得的各项实际指标值； In the formula, x mn is the actual calculated value of the nth index of the mth candidate, y mn ′ is the normalized value of the benefit index of the nth index of the mth candidate, and x n,min is The minimum value of the nth item index, x n, max is the maximum value of the nth item index, and the described candidate scheme is each actual index value obtained by adopting the described index;
    成本型指标的归一化处理表达式为：The normalized processing expression of the cost index is:
    Figure PCTCN2021142298-appb-100041
    Figure PCTCN2021142298-appb-100041
    式中，y mn″为第m个客观赋权方案的第n项指标的成本型指标归一化值。 In the formula, y mn ″ is the normalized value of the cost index of the nth index of the mth objective weighting scheme.
  18. 根据权利要求17所述的一种配电网的韧性综合评估方法，其特征在于，所述客观赋权步骤包括：采用反熵权法对各项指标进行客观赋权，所述反熵权法的计算过程包括：A method for comprehensively evaluating resilience of distribution networks according to claim 17, wherein the objective weighting step comprises: using an anti-entropy weight method to objectively weight each index, and the anti-entropy weight method The calculation process includes:
    计算各指标的反熵值h n，该反熵值h n的计算表达式为： Calculate the anti-entropy value h n of each index, the calculation expression of the anti-entropy value h n is:
    Figure PCTCN2021142298-appb-100042
    Figure PCTCN2021142298-appb-100042
    Figure PCTCN2021142298-appb-100043
    Figure PCTCN2021142298-appb-100043
    式中，y mn为第m个客观赋权方案的第n项指标的指标归一化值，M为待选方案的总数； In the formula, y mn is the index normalization value of the nth item index of the mth objective weighting scheme, and M is the total number of alternative schemes;
    根据所述反熵值进一步确定各指标权重，所述指标权重的计算表达式为：Each index weight is further determined according to the anti-entropy value, and the calculation expression of the index weight is:
    Figure PCTCN2021142298-appb-100044
    Figure PCTCN2021142298-appb-100044
    式中，u n为第n项指标的指标权重，N为指标的总数。 In the formula, u n is the indicator weight of the nth indicator, and N is the total number of indicators.
  19. 根据权利要求17所述的一种配电网的韧性综合评估方法，其特征在于，所述客观赋权步骤包括：采用CRITIC法对各项指标进行客观赋权，所述CRITIC法的计算过程包括：A method for comprehensively evaluating resilience of a distribution network according to claim 17, wherein the objective weighting step comprises: using the CRITIC method to objectively weight various indicators, and the calculation process of the CRITIC method includes :
    计算各指标的冗余信息熵p n，该冗余信息熵p n的计算表达式为： Calculate the redundant information entropy p n of each index, the calculation expression of the redundant information entropy p n is:
    Figure PCTCN2021142298-appb-100045
    Figure PCTCN2021142298-appb-100045
    Figure PCTCN2021142298-appb-100046
    Figure PCTCN2021142298-appb-100046
    式中，p n为第n项指标的冗余信息熵，y mn为第m个客观赋权方案的第n项指标的指标归一化值，M为 待选方案的总数； In the formula, p n is the redundant information entropy of the nth item index, y mn is the index normalization value of the nth item index of the mth objective weighting scheme, and M is the total number of alternative schemes;
    利用归一化矩阵计算各列间协方差和指标的变异系数s n，从而计算各指标间的相关系数，所述各指标间的相关系数的计算表达式为： Use the normalized matrix to calculate the covariance between columns and the coefficient of variation sn of the index, so as to calculate the correlation coefficient between each index. The calculation expression of the correlation coefficient between each index is:
    Figure PCTCN2021142298-appb-100047
    Figure PCTCN2021142298-appb-100047
    Figure PCTCN2021142298-appb-100048
    Figure PCTCN2021142298-appb-100048
    Figure PCTCN2021142298-appb-100049
    Figure PCTCN2021142298-appb-100049
    式中，
    Figure PCTCN2021142298-appb-100050
    为第n项指标的归一化值，s n为第n项指标的变异系数，N为指标的总数，
    Figure PCTCN2021142298-appb-100051
    为第n项和第n *项的相关系数，
    Figure PCTCN2021142298-appb-100052
    为第n *项的指标值，
    Figure PCTCN2021142298-appb-100053
    为指标值y n和
    Figure PCTCN2021142298-appb-100054
    间的协方差，
    Figure PCTCN2021142298-appb-100055
    为第n *项的变异系数；     In the formula,
    Figure PCTCN2021142298-appb-100050
    is the normalized value of the nth index, s n is the variation coefficient of the nth index, N is the total number of indexes,
    Figure PCTCN2021142298-appb-100051
    is the correlation coefficient between the nth item and the n * th item,
    Figure PCTCN2021142298-appb-100052
    is the index value of the n * th item,
    Figure PCTCN2021142298-appb-100053
    is the index value y n and
    Figure PCTCN2021142298-appb-100054
    covariance between
    Figure PCTCN2021142298-appb-100055
    is the coefficient of variation of the n * th item;
    评估各指标所包含的信息量，该信息量的计算表达式为：Evaluate the amount of information contained in each index, the calculation expression of the amount of information is:
    Figure PCTCN2021142298-appb-100056
    Figure PCTCN2021142298-appb-100056
    式中，i n为第n项指标的信息量； In the formula, i n is the amount of information of the nth index;
    根据信息量确定指标权重，该指标权重的计算表达式为：The indicator weight is determined according to the amount of information, and the calculation expression of the indicator weight is:
    Figure PCTCN2021142298-appb-100057
    Figure PCTCN2021142298-appb-100057
    式中，u n为第n项指标的指标权重。 In the formula, u n is the index weight of the nth index.
  20. 一种配电网的韧性综合评估系统，其特征在于，包括存储器和处理器，所述存储器存储有计算机程序，处理器调用所述计算机程序执行如权利要求1至19任一所述的方法的步骤。A comprehensive evaluation system for the resilience of a power distribution network, characterized in that it includes a memory and a processor, the memory stores a computer program, and the processor invokes the computer program to execute the method according to any one of claims 1 to 19 step.
PCT/CN2021/142298 2021-09-10 2021-12-29 Method and system for comprehensive evaluation of resilience of power distribution network WO2023035499A1 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
AU2021335236A AU2021335236A1 (en) 2021-09-10 2021-12-29 Comprehensive resilience evaluation method and system for distribution network

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN202111059384.0 2021-09-10
CN202111059384.0A CN113868585A (en) 2021-09-10 2021-09-10 Comprehensive toughness evaluation method and system for power distribution network

Publications (1)

Publication Number Publication Date
WO2023035499A1 true WO2023035499A1 (en) 2023-03-16

Family

ID=78995242

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2021/142298 WO2023035499A1 (en) 2021-09-10 2021-12-29 Method and system for comprehensive evaluation of resilience of power distribution network

Country Status (3)

Country Link
CN (1) CN113868585A (en)
AU (1) AU2021335236A1 (en)
WO (1) WO2023035499A1 (en)

Cited By (16)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113283698A (en) * 2021-04-21 2021-08-20 华北电力大学 Relay protection anti-electromagnetic interference evaluation index system and evaluation method
CN116136988A (en) * 2023-04-19 2023-05-19 国网浙江省电力有限公司宁波供电公司 Space-time compass distribution-based power distribution network power supply grid construction optimization sequencing method
CN116341992A (en) * 2023-05-29 2023-06-27 广东电网有限责任公司佛山供电局 Comprehensive evaluation method and device for power distribution network, electronic equipment and storage medium
CN116361925A (en) * 2023-05-31 2023-06-30 西北工业大学 Multi-scheme assessment method and system for ship transmission configuration
CN116485286A (en) * 2023-06-21 2023-07-25 中铁第四勘察设计院集团有限公司 Regional passenger dedicated line planning and evaluation method and system based on analytic hierarchy process
CN116629455A (en) * 2023-07-19 2023-08-22 山西阳风新能售电有限公司 Intelligent orientation prediction method based on power supply
CN116703368A (en) * 2023-08-08 2023-09-05 国网信通亿力科技有限责任公司 Synchronous line loss intelligent closed-loop monitoring method based on data mining
CN116744321A (en) * 2023-08-11 2023-09-12 中维建技术有限公司 Data regulation and control method for intelligent operation and maintenance integrated platform for 5G communication
CN116739417A (en) * 2023-05-24 2023-09-12 国家电网有限公司华东分部 Gateway electric energy meter state evaluation method and device, storage medium and computer equipment
CN116742645A (en) * 2023-08-15 2023-09-12 北京中电普华信息技术有限公司 Power load regulation and control task allocation method and device
CN116901774A (en) * 2023-09-11 2023-10-20 南京安充智能科技有限公司 Flexible power distribution method, system and storage medium based on full-network charging pile
CN116933981A (en) * 2023-09-15 2023-10-24 安徽方能电气技术有限公司 Regional power stability analysis and evaluation method based on power outage and restoration event data monitoring
CN117114491A (en) * 2023-09-06 2023-11-24 青岛民航凯亚系统集成有限公司 Airport information system operation and maintenance capability evaluation method and system based on entropy method
CN117200460A (en) * 2023-11-06 2023-12-08 国网湖北省电力有限公司经济技术研究院 Active power distribution network measurement optimization configuration method and system
CN117235373A (en) * 2023-11-14 2023-12-15 四川省计算机研究院 Scientific research hot spot recommendation method based on information entropy
CN117726079B (en) * 2024-02-05 2024-04-16 肯拓（天津）工业自动化技术有限公司 Automatic annular production line optimization method based on electromechanical integration

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116433073A (en) * 2023-02-23 2023-07-14 华北电力大学 Wind power plant operation efficiency evaluation method, device, equipment and medium

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20200153273A1 (en) * 2018-11-13 2020-05-14 Mitsubishi Electric Research Laboratories, Inc. Methods and Systems for Post-Disaster Resilient Restoration of Power Distribution System
CN111179117A (en) * 2019-12-27 2020-05-19 天津大学 Calculation method and device for situation awareness effect evaluation of intelligent power distribution network
CN112001626A (en) * 2020-08-21 2020-11-27 广东电网有限责任公司广州供电局 Method for evaluating toughness of power distribution network in typhoon weather, storage medium and equipment
CN113033886A (en) * 2021-03-18 2021-06-25 国网江苏省电力有限公司扬州供电分公司 Power distribution network planning construction evaluation method

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20200153273A1 (en) * 2018-11-13 2020-05-14 Mitsubishi Electric Research Laboratories, Inc. Methods and Systems for Post-Disaster Resilient Restoration of Power Distribution System
CN111179117A (en) * 2019-12-27 2020-05-19 天津大学 Calculation method and device for situation awareness effect evaluation of intelligent power distribution network
CN112001626A (en) * 2020-08-21 2020-11-27 广东电网有限责任公司广州供电局 Method for evaluating toughness of power distribution network in typhoon weather, storage medium and equipment
CN113033886A (en) * 2021-03-18 2021-06-25 国网江苏省电力有限公司扬州供电分公司 Power distribution network planning construction evaluation method

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
LIN TINGJUN, DONG KUN; ZHAO JIANFENG; LIU KANGLI; YU YUE; WANG JIN: "Research Status and Prospects of Internal and External Collaborative Optimization Scheduling Technology for Integrated Energy System", SHAANXI ELECTRONIC POWER, vol. 49, no. 6, 1 June 2021 (2021-06-01), pages 1 - 8, XP093044916, ISSN: 2096-4145 *
QIANTU RUAN, WEI XIE, YIN XU, BIN HUA, PING SONG, JINGHAN HE, QIQI ZHANG: "Concept and Key Features of Resilient Power Grids", PROCEEDINGS OF THE CSEE, ZHONGGUO DIANJI GONGCHENG XUEHUI, CN, vol. 40, no. 21, 5 November 2020 (2020-11-05), CN , pages 6773 - 6784, XP093044914, ISSN: 0258-8013, DOI: 10.13334/j.0258-8013.pcsee.201308 *
YANG ZHAO, HE MINGHAO; HAN JUN; FENG MINGYUE: "A New Evaluation Method for Radar Emitter Signal Recognition", XIANDAI-LEIDA = MODERN RADAR, NANJING DIANZI JISHU YANJIUSUO, CN, vol. 41, no. 10, 1 October 2019 (2019-10-01), CN , pages 68 - 73, XP093044918, ISSN: 1004-7859, DOI: 10.16592/j.cnki.1004-7859.2019.10.013 *
ZHOU JIANGXIN; ZHAO WANJIAN; ZHANG SHIWEI; LIU YANGYANG; GONG JINXIA; YE YAO: "Resilience Enhancement of Power Grid Considering Optimal Operation of Regional Integrated Energy System Under Typhoon Disaster", 2021 3RD ASIA ENERGY AND ELECTRICAL ENGINEERING SYMPOSIUM (AEEES), IEEE, 26 March 2021 (2021-03-26), pages 546 - 551, XP033904967, DOI: 10.1109/AEEES51875.2021.9403154 *

Cited By (27)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113283698A (en) * 2021-04-21 2021-08-20 华北电力大学 Relay protection anti-electromagnetic interference evaluation index system and evaluation method
CN116136988A (en) * 2023-04-19 2023-05-19 国网浙江省电力有限公司宁波供电公司 Space-time compass distribution-based power distribution network power supply grid construction optimization sequencing method
CN116136988B (en) * 2023-04-19 2023-07-07 国网浙江省电力有限公司宁波供电公司 Space-time compass distribution-based power distribution network power supply grid construction optimization sequencing method
CN116739417A (en) * 2023-05-24 2023-09-12 国家电网有限公司华东分部 Gateway electric energy meter state evaluation method and device, storage medium and computer equipment
CN116341992A (en) * 2023-05-29 2023-06-27 广东电网有限责任公司佛山供电局 Comprehensive evaluation method and device for power distribution network, electronic equipment and storage medium
CN116361925A (en) * 2023-05-31 2023-06-30 西北工业大学 Multi-scheme assessment method and system for ship transmission configuration
CN116361925B (en) * 2023-05-31 2023-11-03 西北工业大学 Multi-scheme assessment method and system for ship transmission configuration
CN116485286B (en) * 2023-06-21 2023-10-03 中铁第四勘察设计院集团有限公司 Regional passenger dedicated line planning and evaluation method and system based on analytic hierarchy process
CN116485286A (en) * 2023-06-21 2023-07-25 中铁第四勘察设计院集团有限公司 Regional passenger dedicated line planning and evaluation method and system based on analytic hierarchy process
CN116629455A (en) * 2023-07-19 2023-08-22 山西阳风新能售电有限公司 Intelligent orientation prediction method based on power supply
CN116629455B (en) * 2023-07-19 2023-10-31 山西阳风新能售电有限公司 Intelligent orientation prediction method based on power supply
CN116703368B (en) * 2023-08-08 2023-10-13 国网信通亿力科技有限责任公司 Synchronous line loss intelligent closed-loop monitoring method based on data mining
CN116703368A (en) * 2023-08-08 2023-09-05 国网信通亿力科技有限责任公司 Synchronous line loss intelligent closed-loop monitoring method based on data mining
CN116744321B (en) * 2023-08-11 2023-11-14 中维建技术有限公司 Data regulation and control method for intelligent operation and maintenance integrated platform for 5G communication
CN116744321A (en) * 2023-08-11 2023-09-12 中维建技术有限公司 Data regulation and control method for intelligent operation and maintenance integrated platform for 5G communication
CN116742645B (en) * 2023-08-15 2024-02-27 北京中电普华信息技术有限公司 Power load regulation and control task allocation method and device
CN116742645A (en) * 2023-08-15 2023-09-12 北京中电普华信息技术有限公司 Power load regulation and control task allocation method and device
CN117114491A (en) * 2023-09-06 2023-11-24 青岛民航凯亚系统集成有限公司 Airport information system operation and maintenance capability evaluation method and system based on entropy method
CN116901774A (en) * 2023-09-11 2023-10-20 南京安充智能科技有限公司 Flexible power distribution method, system and storage medium based on full-network charging pile
CN116901774B (en) * 2023-09-11 2023-11-14 南京安充智能科技有限公司 Flexible power distribution method, system and storage medium based on full-network charging pile
CN116933981A (en) * 2023-09-15 2023-10-24 安徽方能电气技术有限公司 Regional power stability analysis and evaluation method based on power outage and restoration event data monitoring
CN116933981B (en) * 2023-09-15 2023-12-08 安徽方能电气技术有限公司 Regional power stability analysis and evaluation method based on power outage and restoration event data monitoring
CN117200460A (en) * 2023-11-06 2023-12-08 国网湖北省电力有限公司经济技术研究院 Active power distribution network measurement optimization configuration method and system
CN117200460B (en) * 2023-11-06 2024-01-23 国网湖北省电力有限公司经济技术研究院 Active power distribution network measurement optimization configuration method and system
CN117235373A (en) * 2023-11-14 2023-12-15 四川省计算机研究院 Scientific research hot spot recommendation method based on information entropy
CN117235373B (en) * 2023-11-14 2024-03-15 四川省计算机研究院 Scientific research hot spot recommendation method based on information entropy
CN117726079B (en) * 2024-02-05 2024-04-16 肯拓（天津）工业自动化技术有限公司 Automatic annular production line optimization method based on electromechanical integration

Also Published As

Publication number Publication date
CN113868585A (en) 2021-12-31
AU2021335236A1 (en) 2023-03-30

Similar Documents

Publication Publication Date Title
WO2023035499A1 (en) Method and system for comprehensive evaluation of resilience of power distribution network
Afzal et al. State‐of‐the‐art review on power system resilience and assessment techniques
Chuansheng et al. Safety evaluation of smart grid based on AHP-entropy method
CN107909253B (en) Intelligent power distribution network scheduling control effect evaluation method based on inter-zone analytic method
CN102013085A (en) Evaluation method for distribution network reliability
Setreus et al. Identifying critical components for transmission system reliability
Bai et al. Improved resilience measure for component recovery priority in power grids
Kong et al. Power supply reliability evaluation based on big data analysis for distribution networks considering uncertain factors
Ge et al. Evaluation of the situational awareness effects for smart distribution networks under the novel design of indicator framework and hybrid weighting method
Ge et al. An evaluation system for HVDC protection systems by a novel indicator framework and a self-learning combination method
Liu et al. Seismic resilience evaluation and retrofitting strategy for substation system
CN110991816A (en) Construction level monitoring method and device for first-class power distribution network
Bie et al. Evaluation of power system cascading outages
Cai et al. Method for Evaluation on Power Grid Operation Status for Intra-day Tie-line Scheduling
Ju Modeling, simulation, and analysis of cascading outages in power systems
Yang et al. Optimal resource allocation to enhance power grid resilience against hurricanes
Wu et al. Study on risk assessment system of power failure in distribution network of large cities
Chen et al. Evaluation for the resilience of distribution network
Chu et al. Self-healing control method in abnormal state of distribution network
Liu et al. Power grid risk assessment method based on risk probability engineering and its application
Zhang et al. Enhancing power grid resilience against typhoon disasters by scheduling of generators along with optimal transmission switching
Zhang et al. Research on smart grid evaluation index system based on the analytic hierarchy process
Hao et al. Data-driven lean management for distribution network
Chen et al. Risk management for electrifying off-grid island using renewable energy microgrid
Pan et al. A Survivability Assessment Model for the Weak-Link Power Grid under Extreme Events

Legal Events

Date Code Title Description
ENP Entry into the national phase

Ref document number: 2021335236

Country of ref document: AU

Date of ref document: 20211229

Kind code of ref document: A

121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 21956668

Country of ref document: EP

Kind code of ref document: A1