CN114358619A - Double-layer assessment method and system for elastic power distribution network resilience assessment - Google Patents
Double-layer assessment method and system for elastic power distribution network resilience assessment Download PDFInfo
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Abstract
The invention discloses a double-layer evaluation method and a double-layer evaluation system for elastic power distribution network resilience evaluation, aiming at a planning evaluation layer, obtaining historical disaster information of a power grid, and simulating disaster on the planning layer to generate a disaster scene; according to the operation evaluation level, forecasting disaster scenes in real time according to weather and multi-aspect forecasting information; carrying out disaster scene simulation analysis to obtain a time-interval change curve of the load of the power distribution system, extracting the maximum load loss ratio, the load loss time of the system and the power loss index of the system, continuously simulating a new disaster scene for a planning level until the scene simulation is finished, and then counting the indexes obtained in all scenes to obtain an index expected value; and feeding back the index result in real time for the operation level. The method can be used for evaluating the resilience of the elastic power distribution network on planning and operating levels, and realizes the unification of the two level evaluation methods.
Description
Technical Field
The invention belongs to the technical field of power distribution systems, and particularly relates to a double-layer evaluation method and system for elastic power distribution network resilience evaluation.
Background
In recent years, large-scale power failure events of an electric power system caused by natural disasters such as typhoons, rainstorms, ice disasters and the like are frequent, and great challenges and threats are brought to safe and stable operation of the electric power system. Therefore, researches related to a power grid enhancement scheme for resisting natural disasters need to be carried out urgently, and the construction of an elastic power system with prevention, resistance and quick recovery capabilities becomes urgent.
Related researches are widely carried out at home and abroad, a plurality of evaluation methods and evaluation indexes are provided, but the resistance and the recovery capability of the power system to disasters are often evaluated from a single dimension and a single level, and the evaluation method is not strong in universality, so that the invention provides a double-layer evaluation method from a planning level and an operating level to comprehensively measure the elasticity level of a power grid so as to solve related problems.
Disclosure of Invention
The invention aims to solve the technical problem that the method and the system for evaluating the resilience of the elastic power distribution network are provided aiming at the defects in the prior art, so that the level of the resilience of the elastic power distribution network is evaluated from two levels of planning and operation, and the problem that the method for evaluating the resilience of the elastic power distribution network in the prior art is insufficient in universality is solved.
The invention adopts the following technical scheme:
a double-layer evaluation method for elastic power distribution network restoring force evaluation comprises the following steps:
s1, acquiring historical disaster information of the power grid aiming at a planning evaluation level, selecting common disasters to simulate disasters of the planning level, and simulating to generate a disaster scene; according to the operation evaluation level, forecasting disaster scenes in real time according to weather and multi-aspect forecasting information;
s2, simulating and generating a disaster scene and predicting the disaster scene in real time according to the step S1, and performing disaster scene simulation analysis to obtain a time-interval change curve of the load of the power distribution system;
s3, extracting the maximum load loss ratio, the system load loss time and the system power loss index of the power distribution system according to the time-interval change curve of the power distribution system load obtained in the step S2;
s4, according to the maximum loss load ratio of the power distribution system, the loss load time of the system and the loss power indexes of the system extracted in the step S3, continuing to simulate a new disaster scene for a planning level until the scene simulation is finished, and then counting the indexes obtained in all scenes to obtain index expected values; and feeding back the index result in real time for the operation level.
Specifically, in step S2, the disaster scene simulation analysis specifically includes:
s201, obtaining a fault rate sequence lambda of each line of the power distribution network in each hour by using a distribution line fault rate modelk；
S202, according to the line fault rate obtained in the step S201, sampling by using a random number to obtain the fault shutdown time of the line;
s203, according to the line fault outage time obtained in the step S202, performing load transfer simulation in a disaster to obtain the size and the time of cutting off the load;
s204, according to the result obtained by the load transfer simulation in the step S203, performing the post-disaster load recovery simulation, extracting the elasticity index of the power distribution network, and according to the restoration time TrThe distribution function of the load recovery system obtains the repair time of the line and the size and the time of the recovery load;
and S205, obtaining a variation curve of the system load from time to time according to the size and the time of the cutting and recovering load obtained by the simulation of the step S203 and the step S204.
Further, in step S201, a fault rate sequence λ of each line of the power distribution network per hourkComprises the following steps:
wherein λ iskIs at tkFailure rate at time, gamma1、γ2、γ3Is a fitting coefficient; v (t)k) Is tkWind speed at time, λnIs the failure rate of the component under normal conditions.
Further, in step S202, the normal working time of the power distribution line is set to TnWill TnThe probability less than or equal to t is expressed as a fault function, and the initial time t when the disaster comes is0All the elements are new elements, so that the normal working time T of the circuitn≤t0Has a probability of 0 to obtain F (t)0) 0, randomly generating [0,1]Random number beta distributed uniformly in the interior, let beta be F (t)f) Obtaining the fault time t of the line according to the fault functionfIf t isfAnd if the time is more than the predicted disaster ending time, the fault tripping of the line is not generated in the disaster.
Further, the fault function is:
wherein, tk≤t<tk+1，CkIs an integration constant and satisfies Ck＝1-F(tk)；λkFor distribution line in time period tk,tk+1) The failure rate in.
Further, in step S204, the rush-repair time T of each distribution linerObtaining the probability density function f (T) of the repair time by obeying the exponential distribution of the same parametersr) Determining the repair time TrIs randomly generated [0,1 ]]Random number beta distributed uniformly in the interior, let beta be F (T)r) The repair time of the line is obtained as follows:
Tr＝-μlnβ
where μ is the expected value of the line repair time.
In particularIn step S3, the maximum loss ratio S of the distribution systemrComprises the following steps:
wherein, P0The total active load of the power distribution network before a disaster comes; pminThe minimum active load that the distribution network can supply during the impact of a disaster.
Specifically, in step S3, the power distribution system loses the load time StComprises the following steps:
St＝tr-t0
wherein, trIndicating the time when all the loads of the power failure caused by the disaster are recovered; t is t0The power distribution network disaster early-stage load power failure detection method shows the initial moment of power distribution network disaster to cause load power failure.
Specifically, in step S3, the power distribution system loses power SeComprises the following steps:
wherein, P0The total active load of the power distribution network before a disaster comes; p (t) is a function of the distribution network supply active load over time after the arrival of the disaster.
Another technical solution of the present invention is a double-layer evaluation system for evaluating a resilience of an elastic distribution network, including:
the scene module is used for acquiring historical disaster information of the power grid aiming at a planning evaluation layer, selecting common disasters to simulate disasters of the planning layer and simulating to generate a disaster scene; according to the operation evaluation level, forecasting disaster scenes in real time according to weather and multi-aspect forecasting information;
the analysis module is used for simulating and generating a disaster scene and predicting the disaster scene in real time according to the scene module, and performing disaster scene simulation analysis to obtain a time-interval change curve of the load of the power distribution system;
the index module extracts the maximum load loss ratio of the power distribution system, the load loss time of the system and the power loss index of the system according to the time-interval change curve of the load of the power distribution system obtained by the analysis module;
the evaluation module continues to simulate a new disaster scene according to the maximum load loss ratio of the power distribution system, the load loss time of the system and the power loss indexes of the system extracted by the index module until the scene simulation is finished, and then counts indexes obtained in all scenes to obtain index expected values; and feeding back disaster results in real time through the operation evaluation layer.
Compared with the prior art, the invention has at least the following beneficial effects:
the invention discloses a double-layer assessment method for elastic power distribution network resilience assessment, which comprises the steps of dividing an elastic assessment application scene of a power system into planning assessment and operation assessment according to different elastic assessment application scenes of the power system, carrying out disaster scene simulation on a planning assessment layer, carrying out disaster scene prediction on an operation assessment layer, further carrying out disaster scene simulation analysis on the scenes of the two layers to obtain a change curve of a load of the power distribution system in a time interval, then extracting a maximum load loss ratio of the power distribution system, system load loss time and a system power loss amount index, finally using the planning assessment index result for system planning disaster dealing with extreme weather influence according to different assessment layers, feeding back the operation assessment index result to an operator, and providing real-time guidance and reference for operation decision-making personnel.
Furthermore, through simulation analysis of a disaster scene, the size and the time of the load removed in the disaster and the size and the time of the load recovered after the disaster can be obtained, so that the elastic index under the scene is obtained, a staged result can be provided for final index calculation of a planning level, and guidance data can be provided for real-time decision making of an operation level.
Further, the failure rate sequence lambda of each line of the power distribution network per hour is obtainedkParameters can be provided for subsequent fault shutdown time simulation.
Further, by assuming that the element is at the time t of occurrence of the failure0All are new elements, so that the problems are simplified and the analysis is convenient.
Further, by fault functionBy inverse transformation, the fault time t of the line is obtainedfAnd further, the system can obtain which lines can be in fault tripping in disasters, so that the load loses power supply.
Further, the time for repairing the circuit is T through simulationrAnd then, the line fault time and the load loss size and time obtained in the previous step can be combined to further obtain a time-interval change curve of the system load.
Further, the maximum load loss ratio index S of the power distribution system is usedrThe power distribution network protection device can represent the resistance capability of the power distribution network aiming at a certain disaster scene, and reflect the power distribution network power protection capability under the disaster.
Further, the time index S of the load loss of the power distribution systemtThe setting of (2) can characterize the quick recovery ability of distribution network to a certain disaster scene, reflect the restoring force of distribution network under the calamity
Further, the power loss index S of the power distribution systemeThe method can represent the total power loss of the power distribution network suffered from a certain scene disaster, and is used for estimating the economic loss caused by power failure.
In conclusion, the method can be used for elastic distribution network resilience evaluation of planning and operation layers, and unification of two layer evaluation methods is realized, so that the method has higher universality than the original single layer evaluation method.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
FIG. 1 shows a dynamic load change process in a power distribution network disaster scenario;
FIG. 2 is a comparison of two-layer evaluation methods;
FIG. 3 is a schematic flow chart of a two-layer evaluation method;
FIG. 4 is a flow chart of a disaster scenario simulation analysis;
FIG. 5 is a power diagram of the system load loss of 6-13 h after a disaster occurs in an actual system.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the description of the present invention, it should be understood that the terms "comprises" and/or "comprising" indicate the presence of the stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the specification of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
Various structural schematics according to the disclosed embodiments of the invention are shown in the drawings. The figures are not drawn to scale, wherein certain details are exaggerated and possibly omitted for clarity of presentation. The shapes of various regions, layers and their relative sizes and positional relationships shown in the drawings are merely exemplary, and deviations may occur in practice due to manufacturing tolerances or technical limitations, and a person skilled in the art may additionally design regions/layers having different shapes, sizes, relative positions, according to actual needs.
Referring to fig. 2, the invention provides a double-layer evaluation method for elastic power distribution network resilience evaluation, which divides an electric power system elastic evaluation application scenario into planning evaluation and operation evaluation according to different electric power system elastic evaluation application scenarios, and the planning evaluation is an offline evaluation mode, which is a comprehensive elastic evaluation of a system considering extreme events and can provide a basis for planning a system dealing with extreme disaster weather influences; the operation evaluation is an online evaluation mode, which considers the risk evaluation under the system operation condition in a specific disaster scene and can provide related operation decision support when the system encounters a disaster.
The resistance, absorption and response recovery capability of the power distribution network for dealing with extreme disasters can be quantitatively evaluated through planning evaluation and operation evaluation, but the two evaluation methods are different from the evaluation scenes and the evaluation methods and the scenes finally applied to the power distribution network. The evaluation of the planning level focuses on reflecting the elasticity level of the whole system, while the evaluation of the operation level focuses on reflecting the real-time risk of the system, and the risk facing the system is dynamically changed.
1) In the aspect of evaluating scenes, simulated disaster scenes generated in the process of simulating disasters by a simulation method are used in planning evaluation, namely the types and the intensity of the disasters are obtained by simulation; and the operation evaluation is an actual disaster scene obtained according to meteorological prediction and other modes.
2) In the aspect of an evaluation method, planning and evaluating not only need to simulate and consider the uncertainty of the fault rate of system elements, but also need to simulate and consider the uncertainty of disasters; and the operation evaluation only needs to simulate and consider the fault rate change characteristic of the element under the current intensity. Therefore, two-layer nested Monte Carlo simulation is needed for planning evaluation, and the operation evaluation only needs to use single-layer Monte Carlo to simulate the risk of the system in a short time under the current operation state.
3) In the aspect of application scenes, planning and evaluating the comprehensive elasticity level for evaluating the system to cope with the disasters for a long time, analyzing and comparing different reinforcement strategy effects of the same system, and guiding and strengthening the capacity of coping with various disasters; the operation evaluation can reflect the real-time response condition of external disasters of the system, and provides real-time guidance and suggestions for power grid operation decision-making personnel.
According to the process, the elasticity evaluation of the planning level is not specific to a specific disaster, and if the system is not modified, the elasticity level of the system is considered to be unchanged in a certain period; the risk assessment of the operation layer is specific to the current specific disaster, and the assessment result can reflect the real-time change condition of the disaster resisting capability of the system, so that the risk assessment has a great relationship with the current disaster, and indexes of different disasters under different strengths can have great difference.
Referring to fig. 3, the present invention provides a double-layer evaluation method for evaluating the resilience of an elastic distribution network, including the following steps:
s1, aiming at a planning evaluation layer: acquiring historical disaster information of a power grid, analyzing the types of common disasters in the area, selecting the common disasters to simulate the disasters on a planning level, and simulating to generate a specific disaster scene; aiming at the operation evaluation layer: providing forecast of an imminent disaster scene according to weather and multi-aspect forecast information;
s2, carrying out disaster scene simulation analysis according to the specific scene obtained in the step S1;
referring to fig. 4, the simulation analysis of the disaster scene specifically includes:
s201, obtaining a fault rate sequence lambda of each line of the power distribution network in each hour by using a distribution line fault rate modelk；
Taking typhoon disasters as an example, the larger the typhoon wind speed is, the larger the line fault rate is, and we consider that the fault rate in the hourly time scale range is a constant, and then the fault rate at the k time period is:
wherein λ iskIs at tkThe unit of the fault rate of the time is sub/(y.km); gamma ray1、γ2、γ3Are fitting coefficients, all of which are constants; v (t)k) Is tkThe unit of the wind speed at the moment is m/s; lambda [ alpha ]nThe failure rate of the device under normal conditions is expressed by the unit of times/(y.km).
S202, sampling a random number to obtain the fault shutdown time of the line;
lines are considered to be irreparable elements during a disaster, i.e. considered to be irreparable elementsBefore the disaster is over, the line is always in a fault state, and the normal working time of the power distribution line is TnThen T isnThe probability ≦ t is expressed as the fault function:
wherein, CkIs an integration constant, and satisfies Ck＝1-F(tk)；λkFor distribution line in time period tk,tk+1) The failure rate in. For the initial time t when the disaster comes0All elements can be considered as intact and new elements, so that the normal working time T of the circuitn≤t0Has a probability of 0 to obtain F (t)0)＝0。
Randomly generating [0,1 ]]Random number beta distributed uniformly in the interior, let beta be F (t)f) Substituting the formula (5) to obtain the fault time t of the linefIf t isfIf the time is larger than the predicted disaster ending time, the line is considered not to have fault tripping in the disaster.
S203, simulating load transfer in a disaster;
the load of a fault line in a disaster can be transferred through a communication line, a path from the power-off load to a power supply is searched through a path search algorithm, if the load point has no possible restoration path, the load is considered to lose power supply, restoration is waited after the disaster, and if the restoration path exists, the load is considered to be not powered off.
S204, simulating post-disaster load recovery
After the disaster, the emergency maintenance team begins to carry out line emergency maintenance and recovery, the hourly power distribution network recovery process is simulated, and the emergency maintenance time T of each distribution line is considered in the simulationrObtaining the probability density function f (T) of the repair time by obeying the exponential distribution of the same parametersr) Expressed as:
whereinMu is the expected value of the line repair time; t isrThe repair time is.
Further obtaining the repair time TrDistribution function of
Randomly generating [0,1 ]]Random number beta distributed uniformly in the interior, let beta be F (T)r) Substituting equation (7) to obtain the repair time of the line as follows:
Tr＝-μlnβ (8)
s3, obtaining a system maximum load loss ratio, a system load loss time and a system power loss index according to the time-interval change curve of the distribution system load obtained in the step S2;
referring to fig. 1, after a disaster occurs in the elastic distribution network, three indexes, namely, a maximum loss load ratio of the distribution system, a loss load time of the distribution system, and a loss power of the distribution system, are selected to measure the elasticity level of the distribution system.
1) Maximum loss of load ratio for power distribution system
Wherein, P0The total active load of the power distribution network before a disaster comes; pminThe minimum active load that the distribution network can supply during the impact of a disaster. System maximum loss of load ratio indicator SrThe method has the advantages that the resisting capability of the power distribution network for a certain disaster scene is represented, and the power supply protecting capability of the power distribution network under the disaster is reflected.
2) Time of loss of load of power distribution system
St＝tr-t0 (2)
Wherein, trIndicating the time when all the loads of the power failure caused by the disaster are recovered; t is t0The power distribution network disaster early-stage load power failure detection method shows the initial moment of power distribution network disaster to cause load power failure. Time index S of system load losstCharacterizes the rapid recovery of the distribution network to a disaster sceneAnd the capability reflects the restoring force of the power distribution network under the disaster.
3) Power loss of power distribution system
Wherein, P0The total active load of the power distribution network before a disaster comes; p (t) is a function of the distribution network supply active load over time after the arrival of the disaster. System power loss indicator SeThe total power loss of the power distribution network subjected to a certain scene disaster is represented, and the total power loss is used for estimating the economic loss caused by power failure.
S4, returning the evaluation of the planning level to the step S1, continuing to simulate a new disaster scene until the scene simulation is finished, and then counting indexes obtained in all scenes to obtain index expected values; and for the evaluation of the operation level, the index result is fed back to the operation personnel in real time, so that real-time guidance and reference are provided for the operation decision personnel.
In another embodiment of the present invention, a double-layer evaluation system for evaluating the restoring force of an elastic power distribution network is provided, where the system can be used to implement the above double-layer evaluation method for evaluating the restoring force of an elastic power distribution network, and specifically, the double-layer evaluation system for evaluating the restoring force of an elastic power distribution network includes a scene module, an analysis module, an index module, and an evaluation module.
The scene module acquires historical disaster information of the power grid aiming at a planning evaluation level, selects common disasters to simulate disasters of the planning level and simulates a disaster scene; according to the operation evaluation level, forecasting disaster scenes in real time according to weather and multi-aspect forecasting information;
the analysis module is used for simulating and generating a disaster scene and predicting the disaster scene in real time according to the scene module, and performing disaster scene simulation analysis to obtain a time-interval change curve of the load of the power distribution system;
the index module extracts the maximum load loss ratio of the power distribution system, the load loss time of the system and the power loss index of the system according to the time-interval change curve of the load of the power distribution system obtained by the analysis module;
the evaluation module continues to simulate a new disaster scene according to the maximum load loss ratio of the power distribution system, the load loss time of the system and the power loss indexes of the system extracted by the index module until the scene simulation is finished, and then counts indexes obtained in all scenes to obtain index expected values; and feeding back disaster results in real time through the operation evaluation layer.
In order to make the objects, 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 with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. The components of the embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Examples
Referring to fig. 5, taking the recovery process of an actual system in a certain area after a simulated disaster as an example, the calculation of the relevant indexes is performed, where case 1 is a basic case, and cases 2, 3, and 4 are comparison cases adopting corresponding promotion strategies.
Case 1: 4 sets of 200MW units of the A hydraulic power plant are set as black start power supplies, the expected time for repairing a fault line is 45min, and three maintenance teams repair fault elements in the area.
Case 2: influence of capacity improvement and layout of the black start power supply on power grid recovery. In order to analyze the influence of the capacity and the layout of the black start power supply on the recovery of a power grid, the capacity of the black start power supply is increased and the layout of the power supply is optimized on the basis of case 1, the black start power supply is set as 4 200MW units of a hydraulic power plant A and 2 units of 4 300MW units of a hydraulic power plant B, and other parameters are unchanged.
Case 3: influence of the optimized deployment of maintenance personnel and materials on the recovery of the power grid before a disaster. And (3) deploying the repair team and the maintenance materials in advance to reduce the distance from a maintenance worker to a fault point, advancing the maintenance completion time of the element to 30min on the basis of case 1, and keeping the other parameters unchanged.
Case 4: and (3) influence of post-disaster personnel scheduling and element repair sequence optimization on power grid recovery. And optimizing the maintenance sequence of the elements in the cooperative recovery process, and reasonably adjusting the maintenance completion time of each element on the basis of the case 1 according to the new repair sequence. The remaining parameters were unchanged.
TABLE 1 calculation of the four case indicators
Compared with the basic case 1, cases 2 to 4 have reduced loss load proportion and loss electric quantity, and the overall power restoration time is also shortened.
The capacity of the black-start power supply is improved, the material deployment of maintenance personnel before disaster and the cooperative optimization of restoration and restoration after disaster can obviously reduce the overall power restoration time of the system and reduce the power loss of the system in the restoration process.
In summary, according to the double-layer assessment method and system for assessing the resilience of the elastic power distribution network, the application scenario of the elastic assessment of the power system is divided into planning assessment and operation assessment according to different application scenarios of the elastic assessment of the power system. And finally, according to different evaluation levels, the planning evaluation index result is used for planning a system for dealing with extreme disaster weather influence, and the operation evaluation index result is fed back to operators, so that real-time guidance and reference are provided for operation decision-making personnel. The test system can be obtained through result verification of the test system, and the capacity of the black-start power supply is improved, the material deployment of maintenance personnel before disaster and the repair-recovery cooperative optimization after disaster can obviously reduce the overall power restoration time of the system and reduce the power loss of the system in the recovery process. The method can effectively and quantitatively evaluate the elasticity level of the power distribution system.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above-mentioned contents are only for illustrating the technical idea of the present invention, and the protection scope of the present invention is not limited thereby, and any modification made on the basis of the technical idea of the present invention falls within the protection scope of the claims of the present invention.
Claims (10)
1. A double-layer assessment method for elastic distribution network resilience assessment is characterized by comprising the following steps:
s1, acquiring historical disaster information of the power grid aiming at a planning evaluation level, selecting common disasters to simulate disasters of the planning level, and simulating to generate a disaster scene; according to the operation evaluation level, forecasting disaster scenes in real time according to weather and multi-aspect forecasting information;
s2, simulating and generating a disaster scene and predicting the disaster scene in real time according to the step S1, and performing disaster scene simulation analysis to obtain a time-interval change curve of the load of the power distribution system;
s3, extracting the maximum load loss ratio, the system load loss time and the system power loss index of the power distribution system according to the time-interval change curve of the power distribution system load obtained in the step S2;
s4, according to the maximum loss load ratio of the power distribution system, the loss load time of the system and the loss power indexes of the system extracted in the step S3, continuing to simulate a new disaster scene for a planning level until the scene simulation is finished, and then counting the indexes obtained in all scenes to obtain index expected values; and feeding back the index result in real time for the operation level.
2. The double-layer assessment method for elastic power distribution network resilience assessment according to claim 1, wherein in step S2, the disaster scenario simulation analysis specifically comprises:
s201, obtaining a fault rate sequence lambda of each line of the power distribution network in each hour by using a distribution line fault rate modelk；
S202, according to the line fault rate obtained in the step S201, sampling by using a random number to obtain the fault shutdown time of the line;
s203, according to the line fault outage time obtained in the step S202, performing load transfer simulation in a disaster to obtain the size and the time of cutting off the load;
s204, according to the result obtained by the load transfer simulation in the step S203, performing the post-disaster load recovery simulation, extracting the elasticity index of the power distribution network, and according to the restoration time TrThe distribution function of the load recovery system obtains the repair time of the line and the size and the time of the recovery load;
and S205, obtaining a variation curve of the system load from time to time according to the size and the time of the cutting and recovering load obtained by the simulation of the step S203 and the step S204.
3. The double-layer evaluation method for elastic distribution network restoring force evaluation according to claim 2, wherein in step S201, the fault rate sequence λ of each line of the distribution network per hourkComprises the following steps:
wherein λ iskIs at tkFailure rate at time, gamma1、γ2、γ3Is a fitting coefficient; v (t)k) Is tkWind speed at time, λnIs the failure rate of the component under normal conditions.
4. The double-layer evaluation method for the resilience of the elastic distribution network according to claim 2, wherein in step S202, the normal working time of the power distribution line is set to TnWill TnThe probability less than or equal to t is expressed as a fault function, and the initial time t when the disaster comes is0All the elements are new elements, so that the normal working time T of the circuitn≤t0Has a probability of 0 to obtain F (t)0) 0, randomly generating [0,1]Random number beta distributed uniformly in the interior, let beta be F (t)f) Obtaining the fault time t of the line according to the fault functionfIf t isfAnd if the time is more than the predicted disaster ending time, the fault tripping of the line is not generated in the disaster.
5. The double-layer evaluation method for elastic power distribution network resilience evaluation according to claim 4, wherein the fault function is:
wherein, tk≤t<tk+1，CkIs an integration constant and satisfies Ck＝1-F(tk)；λkFor distribution line in time period tk,tk+1) The failure rate in.
6. The double-layer assessment method for elastic distribution network restoring force assessment according to claim 2, wherein in step S204, the rush-repair time T of each distribution linerObtaining the probability density function f (T) of the repair time by obeying the exponential distribution of the same parametersr) Determining the repair time TrIs randomly generated [0,1 ]]Random number beta distributed uniformly in the interior, let beta be F (T)r) The repair time of the line is obtained as follows:
Tr＝-μlnβ
where μ is the expected value of the line repair time.
7. The double-layer assessment method for elastic power distribution network restoring force assessment according to claim 1, wherein in step S3, the maximum loss of load ratio S of the power distribution systemrComprises the following steps:
wherein, P0The total active load of the power distribution network before a disaster comes; pminThe minimum active load that the distribution network can supply during the impact of a disaster.
8. The double-layer assessment method for elastic distribution network restoring force assessment according to claim 1, wherein in step S3, the distribution system loss load time StComprises the following steps:
St＝tr-t0
wherein, trIndicating the time when all the loads of the power failure caused by the disaster are recovered; t is t0The power distribution network disaster early-stage load power failure detection method shows the initial moment of power distribution network disaster to cause load power failure.
9. The double-layer assessment method for elastic power distribution network resilience assessment according to claim 1, wherein in step S3, the power distribution system loses power SeComprises the following steps:
wherein, P0The total active load of the power distribution network before a disaster comes; p (t) is a function of the distribution network supply active load over time after the arrival of the disaster.
10. A double-layer assessment system for elastic distribution network resilience assessment, comprising:
the scene module is used for acquiring historical disaster information of the power grid aiming at a planning evaluation layer, selecting common disasters to simulate disasters of the planning layer and simulating to generate a disaster scene; according to the operation evaluation level, forecasting disaster scenes in real time according to weather and multi-aspect forecasting information;
the analysis module is used for simulating and generating a disaster scene and predicting the disaster scene in real time according to the scene module, and performing disaster scene simulation analysis to obtain a time-interval change curve of the load of the power distribution system;
the index module extracts the maximum load loss ratio of the power distribution system, the load loss time of the system and the power loss index of the system according to the time-interval change curve of the load of the power distribution system obtained by the analysis module;
the evaluation module continues to simulate a new disaster scene according to the maximum load loss ratio of the power distribution system, the load loss time of the system and the power loss indexes of the system extracted by the index module until the scene simulation is finished, and then counts indexes obtained in all scenes to obtain index expected values; and feeding back disaster results in real time through the operation evaluation layer.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115330559A (en) * | 2022-10-17 | 2022-11-11 | 国网浙江余姚市供电有限公司 | Power distribution network elasticity evaluation method and device based on information data time-space coordination |
| CN115879833A (en) * | 2023-03-02 | 2023-03-31 | 国网山东省电力公司威海供电公司 | Double-layer power distribution network toughness evaluation method and system considering disaster response and recovery |
| CN117335570A (en) * | 2023-10-09 | 2024-01-02 | 国网河南省电力公司濮阳供电公司 | Visual monitoring system and method for panoramic information of elastic power distribution network |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115330559A (en) * | 2022-10-17 | 2022-11-11 | 国网浙江余姚市供电有限公司 | Power distribution network elasticity evaluation method and device based on information data time-space coordination |
| CN115879833A (en) * | 2023-03-02 | 2023-03-31 | 国网山东省电力公司威海供电公司 | Double-layer power distribution network toughness evaluation method and system considering disaster response and recovery |
| CN117335570A (en) * | 2023-10-09 | 2024-01-02 | 国网河南省电力公司濮阳供电公司 | Visual monitoring system and method for panoramic information of elastic power distribution network |
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