CN114336628A - Photovoltaic power supply access distribution network safety evaluation method based on random power flow - Google Patents

Photovoltaic power supply access distribution network safety evaluation method based on random power flow Download PDF

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CN114336628A
CN114336628A CN202111436076.5A CN202111436076A CN114336628A CN 114336628 A CN114336628 A CN 114336628A CN 202111436076 A CN202111436076 A CN 202111436076A CN 114336628 A CN114336628 A CN 114336628A
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power
photovoltaic
distribution network
random
load
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丁斌
邢志坤
王帆
袁博
赵树军
唐宝锋
赵路新
路鹏程
钟成
蒋雨
孟斌
张宁
张海涛
闫浩然
连浩然
郭磊
陈晨
陈振华
田雨
康伟娇
顾辰方
蔡佳铭
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Xiongan New Area Power Supply Company State Grid Hebei Electric Power Co
State Grid Corp of China SGCC
Shanghai Electric Power Design Institute Co Ltd
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Xiongan New Area Power Supply Company State Grid Hebei Electric Power Co
State Grid Corp of China SGCC
Shanghai Electric Power Design Institute Co Ltd
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    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B70/00—Technologies for an efficient end-user side electric power management and consumption
    • Y02B70/30—Systems integrating technologies related to power network operation and communication or information technologies for improving the carbon footprint of the management of residential or tertiary loads, i.e. smart grids as climate change mitigation technology in the buildings sector, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
    • Y02B70/3225—Demand response systems, e.g. load shedding, peak shaving
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/50—Photovoltaic [PV] energy
    • Y02E10/56—Power conversion systems, e.g. maximum power point trackers
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
    • Y02E40/30—Reactive power compensation
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S20/00—Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
    • Y04S20/20—End-user application control systems
    • Y04S20/222—Demand response systems, e.g. load shedding, peak shaving

Abstract

The invention discloses a photovoltaic power supply access distribution network safety evaluation method based on random power flow. Firstly, carrying out investigation and collection on various parameters required by evaluation related to the evaluation of the operation safety of the power distribution network; constructing or describing a probability process of uncertain elements such as photovoltaic output, load and the like; sampling to generate photovoltaic and load sequences which obey corresponding probability distribution, wherein the combination formed by the photovoltaic and load sequences is a calculation scene of random power flow concern and research; step four, determining an expected failure set; fifthly, under the generated calculation scene, investigating and registering the result of the simulation experiment to obtain the solution of the problem; step six, defining thought behavior indexes; and step seven, substituting the calculation result into the formula to analyze and evaluate the value of the index according to the load flow calculation result. The invention provides a safety evaluation process and a safety evaluation method for a photovoltaic power supply to be connected into a power distribution network, and aims to provide beneficial reference for a safety evaluation scene of the power distribution network with large-scale or large-scale photovoltaic connection.

Description

Photovoltaic power supply access distribution network safety evaluation method based on random power flow
Technical Field
The invention relates to the technical field of evaluation of running states of photovoltaic power supply access power grids, in particular to a photovoltaic access power distribution grid safety evaluation method based on a random power flow method.
Background
The photovoltaic power generation mode is different from the traditional thermal power generation, and the essential difference is that the distribution of solar energy resources on time and space scales is not balanced, so that the output of the photovoltaic power generation has great randomness and fluctuation. After the photovoltaic is connected into a power system, the stability and the reliability of the system are influenced widely and profoundly. The randomness, the fluctuation and the distribution of the output of the photovoltaic power supply lead to the aggravation of the uncertainty of the flow direction and the distribution of the power flow. This uncertainty is present in both the flow direction and the flow level: on one hand, the power distribution network is different from the traditional passive power distribution network in unidirectional power flow, and the bidirectional flow of line power flow can be caused after a large number of photovoltaic power sources are connected. Especially, on the occasion that the load demand is low and the photovoltaic output is sufficient, redundant photovoltaic electric quantity is fed into the upper-level power grid, and the coordination among original equipment and the action condition of the voltage regulator are influenced. On the other hand, the uncertainty of the generated power of the photovoltaic power supply reduces the accuracy of short-term power prediction, and meanwhile, the number of power supply points in the power distribution network is remarkably increased, the positions are dispersed, and the single-point scale is small. This will increase the difficulty of planning the operation of the conventional unit and controlling the cross-sectional exchange power.
The large-scale photovoltaic grid connection has great influence on the operation mode of the system, the system state is more complicated and changeable, and higher requirements are provided for the electric evaluation and check work of the power grid. On the premise of inputting background data of a planning scene, photovoltaic access conditions, regional development planning and other data, calculating and evaluating electrical quantity in a planning scheme, finding potential problems and hidden defects in the planning scheme, and correspondingly adjusting and supplementing the planning scheme according to results, so that the purposes of improving the planning level and preventing operation risks in future large-scale photovoltaic access scenes are achieved.
Chenhai Yan et al. "Power distribution network load flow calculation with distributed power supply." Power System Automation 30.1(2006):6. Joe-Shake, Chen-Shaw, Zhang particle, etc. Power decomposition load flow calculation method [ J ]. Chinese Motor engineering report, 2001,21(1):4. all report traditional load flow calculation to calculate the electric capacity of the power system under the steady state operation state according to the wiring mode, parameters and operation conditions of the power system. The network and node parameters used are considered to be definite values, and the calculated node voltage, branch load flow and the like are also definite. With the large-scale access of photovoltaic power sources, the uncertainty problem of the state analysis of the power distribution network is more prominent, and the traditional method has certain limitations. In practical application, the problems of power distribution network load flow calculation and safety evaluation considering large-scale access of a photovoltaic power supply are still in an exploration stage, and a mature and practical evaluation method considering various influence factors and meeting practical requirements is relatively lacked. The lack of a reasonable and scientific evaluation method easily causes that the operation level of the power distribution network after a large number of photovoltaic power supplies are connected cannot be accurately measured, and simultaneously, the remarkable advantages of the photovoltaic power supplies in the aspects of improving the energy utilization efficiency, transforming the energy production structure, realizing clean substitution, supporting a low-carbon transformation power grid and the like cannot be fully exerted, so that the follow-up popularization, popularization and application of renewable energy sources are not facilitated. Therefore, how to overcome the problem of subjective evaluation and implement a method for evaluating the safety of a photovoltaic power supply accessed to a power distribution network based on random power flow becomes a technical problem to be solved urgently by technical personnel in the field.
Disclosure of Invention
In view of the above defects in the prior art, the invention provides a method for evaluating the safety of a photovoltaic power supply accessed to a power distribution network based on random power flow, and the purpose of evaluating the safety of the photovoltaic power supply accessed to the power distribution network is realized by the basic idea and steps of the random power flow (monte carlo method). The photovoltaic output level, the output characteristics and the like are comprehensively considered, the power distribution network operation boundary combination after photovoltaic access and the operation state under each boundary are provided, and therefore the photovoltaic access evaluation flow and method based on the random power flow are provided, and beneficial reference is provided for power distribution network operation state engineering.
In order to achieve the purpose, the invention discloses a photovoltaic power supply access distribution network safety evaluation method based on random power flow, which comprises the following specific steps:
step one, carrying out investigation and collection on various parameters required by evaluation related to the evaluation of the operation safety of the power distribution network. The content comprises the following steps: installed capacities of various photovoltaic power supplies related to an object to be evaluated, power supply ranges of the photovoltaic power supplies (determined by connection relations between the photovoltaic power supplies and load nodes, net rack topology and operation modes), capacities of a superior power supply and a standby power supply of a power distribution network system, maximum energy supply capacity of the photovoltaic power supplies (determined by combining investigation results and design parameters and generally represented by power), energy consumption requirements of various load nodes in the power distribution network (determined by combining background design data and generally represented by power), historical output data of the photovoltaic power supplies (if the photovoltaic in the power distribution network to be evaluated is a planned or newly-built power supply, historical output levels of the photovoltaic power supplies in the same type of region can be selected), historical load data conditions and the like;
and step two, constructing or describing a probability process of uncertain elements such as photovoltaic output, load and the like. For the problem of random nature, it is mainly to correctly describe and model the probability process; for deterministic problems that are not inherently random, an artificial probabilistic process must be constructed in advance, with some of its parameters being exactly the solution to the required problem. I.e. to convert the problem of not having random properties into the problem of random properties. Generally, the photovoltaic output at a certain moment is considered to obey Beta distribution corresponding to the moment, and the load obeys normal distribution;
and step three, sampling and generating photovoltaic and load sequences and the like which obey corresponding probability distribution, wherein the formed combination is a calculation scene of random power flow concern and research. After the probability model is constructed by sampling the known probability distribution, since each probability model can be regarded as being composed of various probability distributions, the generation of a random variable (or a random vector) of the known probability distribution becomes a basic means for realizing a simulation experiment of the monte carlo method, which is also called random sampling. The process of generating random numbers is a matter of sampling from this probability distribution. On a computer, random numbers may be generated physically. From the known distributed random sampling there are various methods, which are implemented with the aid of random sequences, which are premised on the generation of random numbers;
and step four, determining an expected failure set. The invention needs to consider the capability of the power distribution network for keeping safe operation (such as line tide, node voltage not exceeding the limit and the like) when relevant nodes and equipment in the power distribution network have faults and a large number of photovoltaic power supplies are connected into the power distribution network. And extracting important or sensitive node numbers of expected accidents, forming an accident set by the important or sensitive node numbers, and recording the failure rate of the accident set.
And fifthly, under the generated calculation scene, investigating and registering the result of the simulation experiment, and obtaining the solution of the problem from the result. And (4) carrying out load flow calculation under each sampling boundary according to the sampled photovoltaic and load power values and the element state (whether a fault occurs), and repeating the calculation process to obtain the load flow distribution under each sampling scene. Analyzing the safety of the planning scheme by combining the safety behavior indexes, and extracting a statistical rule, probability indexes and the like from the safety behavior indexes to be used as a basis for evaluating the planning scheme;
and step six, defining the following behavior index PI (Performance index) to describe the severity of the expected accident. Common power flow calculation and analysis indexes comprise line power flow out-of-limit proportion, net rack power, electric energy loss and the like. The indexes are in a form of determined values, are difficult to be matched with the calculation characteristics of random power flow, and are not suitable for analyzing the system safety under the high-permeability photovoltaic access scene. Since there is no or only a weak coupling between active and reactive power in the network, two behavior indicators can be defined: the active power index and the reactive power index are specifically defined as follows:
(1) the active power behavior index is as follows: the index for measuring the active power overload degree of the feeder line is calculated according to the following formula:
Figure BDA0003377287770000041
in the formula: w is apIs an active power weight factor; piIs the active power flow in line i; pi maxAn upper limit value of active power of the line i; alpha is the line set with active power overload.
(2) Reactive power behavior index: the indexes for measuring the out-of-limit degree of the voltage and the reactive power are calculated according to the following formula:
Figure BDA0003377287770000042
in the formula: w is auIs a voltage weight factor; u shapekIs the voltage modulus of node k;
Figure BDA0003377287770000043
is the voltage modulus limit of node k; beta is a node set with the voltage modulus out of limit; w is aqIs a reactive power weight factor; qkIs the value of reactive power injected into node k;
Figure BDA0003377287770000044
is the reactive power limit for injection node k; gamma is the set of nodes with reactive power out of limit. Note that α, β, γ are all limited to out-of-limit lines or nodes; w is ap、wu、wqThe parameters can be adjusted, the values of the parameters are related to the operation experience and the importance of related lines and nodes under different out-of-limit conditions, and the values can be generally 1 under the condition of lacking actual data.
(3) Power out-of-limit probability: the safety analysis is carried out by using a random power flow algorithm, and the obtained power flow is a time-varying value, so that the power out-of-limit condition cannot be measured by only 'yes' or 'no', and a probability index is used for representing the power out-of-limit condition. Accordingly, a power threshold crossing index is defined and calculated according to the following formula:
Figure BDA0003377287770000045
in the formula: n is the total volume of the sampling sample of the Monte Carlo simulation method; n isiThe number of samples for which the power violation occurred for line i in the sample.
(4) Average degree of voltage deviation: because the number of nodes of the distribution network system is large, in order to better represent the voltage condition of the whole system, particularly the voltage drop phenomenon, the average deviation degree of the voltage is defined and calculated according to the following formula:
Figure BDA0003377287770000046
in the formula: k is a set of all nodes in the distribution network system; u shapekIs the voltage value of node k (average value of random power flow); u shapeNThe rated voltage value of the distribution network system is obtained; and m is the number of nodes of the system.
And step seven, substituting the calculation result into the formula to analyze and evaluate the value of the index according to the load flow calculation result. And taking the result as a safety comprehensive analysis result of the scene to be evaluated. And comparing the index calculation result of the grid to be evaluated with the basic grid before photovoltaic access or the grid adopting corresponding improvement and promotion measures so as to analyze the influence of the photovoltaic access on the safe operation capacity of the power distribution network and the like.
In the first step, the evaluating the parameter content of research and investment required by the survey and investment comprises:
the installed capacity of various photovoltaic power supplies and the power supply range of the photovoltaic power supplies related to the power distribution network frame to be evaluated are determined by the connection relation between the photovoltaic power supplies and the load nodes, the network frame topology and the operation mode;
the capacity of a superior power supply and a standby power supply of the power distribution network system to be evaluated and the maximum energy supply capacity of the photovoltaic power supply are determined by combining investigation results and design parameters and are usually represented by power;
the energy consumption requirements of various load nodes in the power distribution network system to be evaluated are determined by combining background design data and are usually represented by power; if the photovoltaic in the distribution network to be evaluated is a planned or newly-built power supply, the historical output level and the historical load data condition of the photovoltaic power supplies in the same type of regions can be selected and generally expressed by power;
in the second step, the photovoltaic output at a certain moment of the uncertain elements such as the photovoltaic output, the load and the like obeys Beta distribution corresponding to the moment, and the load obeys normal distribution;
in the third step, the renewable energy output level and the load level according to which the power flow is calculated are obtained by sampling from probability distribution fitted or modeled based on historical data, and the photovoltaic output level and the load level formed by each sampling are combined to be used as a basic boundary of the power flow calculation;
in the fourth step, the accident node or equipment in the expected accident set only relates to one place, that is, the safety assessment method provided by the invention is developed under the N-1 scene;
in the fifth step, after external boundaries such as photovoltaic output, load level and the like are determined, power flow calculation of the power distribution network after photovoltaic access is converted into a power flow calculation process of a conventional power distribution network frame;
in the sixth step, four behavior indexes are defined in total, including four indexes of active power behavior, reactive power behavior, power out-of-limit behavior and average deviation degree of voltage.
And seventhly, the influence of photovoltaic access on the operation safety of the power distribution network and the like is explained by combining the comprehensive calculation result of the behavior index and the comparison of the photovoltaic access. The maximum photovoltaic power capacity allowed to be accessed in the power distribution network and the influence of the photovoltaic power on the power distribution network can be analyzed by combining the influence and the operation condition of the photovoltaic power with a specific scale on the power distribution network after being accessed, so that the adaptability of the power distribution network to the photovoltaic power and the capability of the grid frame to be evaluated to be further accessed to the photovoltaic power can be analyzed.
The invention has the beneficial effects that:
the method compares the index calculation result of the grid to be evaluated with the basic grid before photovoltaic access or the grid adopting corresponding improvement and promotion measures so as to analyze the influence of the photovoltaic access on the safe operation capacity of the power distribution network and the like. The influence evaluation possibly caused by the fact that the photovoltaic power supply is connected into the power distribution network based on the random power flow is comprehensively considered, and the safety evaluation flow and the safety evaluation method of the photovoltaic power supply connected into the power distribution network are provided, so that beneficial reference is provided for the safety evaluation scene of the power distribution network with large-scale or large-scale photovoltaic access.
Drawings
FIG. 1 shows a flow chart of an embodiment of the present invention.
Fig. 2 shows an electrical wiring schematic of an embodiment of the invention.
Fig. 3 shows a simulation diagram of a photovoltaic unit output monte carlo sampling process according to an embodiment of the invention.
Fig. 4 is a schematic diagram illustrating a node active load cumulative probability distribution according to an embodiment of the present invention.
FIG. 5 is a diagram illustrating the node voltage results after the sampling calculation according to the embodiment of the present invention.
FIG. 6 is a schematic diagram illustrating cumulative probability distribution of node voltage calculation results according to an embodiment of the invention.
Detailed Description
Example 1
The present invention is applied in a Matlab 2016a environment, as shown in fig. 1-6, as an example of a specific embodiment.
Step one, carrying out investigation and collection on various parameters required by evaluation related to the evaluation of the operation safety of the power distribution network. Based on an IEEE 33 node system, the original system network reference voltage is 12.66kv, the original system is changed, an electrical wiring diagram of the new system is shown in the figure, 36 nodes, 4 buses and 40 feeders are adopted, the total active load of the system is 3715.0kW, and the total reactive load is 2300.0 kVar. A schematic diagram of the parameters of the calculation is shown in figure 2. The historical data of the photovoltaic output is shown in figure 3.
And step two, constructing or describing a probability process of uncertain elements such as photovoltaic output, load and the like. And simulating the output of the photovoltaic unit by a Monte Carlo simulation method. The photovoltaic output of each node has certain independence, and the photovoltaic output of each node needs to be sampled independently during simulation, namely, a plurality of different groups of random sequences are generated. Assuming that photovoltaic is connected at node 37, 3000 samples are taken for this example. The output state of the photovoltaic unit has three states of cutting, transition and rated operation, which accords with the randomness and volatility characteristics of the photovoltaic unit. Furthermore, the statistical photovoltaic has an average contribution of about 0.77MW, which is less than its rated contribution. The injected power of the load point adopts normal distribution. Taking node 7 of the above system as an example, the average value is 0.2MW, and the standard deviation is 0.04. The active power of the node is sampled by a monte carlo simulation method, and the probability distribution of the active load of the node 7 is obtained by analyzing the probability of the sampling value, as shown in fig. 4. The active load of the node 7 fluctuates between 0.08MW and 0.32MW approximately, and the probability is the maximum near 0.2MW, so that the load fluctuation of an actual power distribution system is well reflected.
And step three, sampling and generating photovoltaic and load sequences and the like which obey corresponding probability distribution, wherein the formed combination is a calculation scene of random power flow concern and research. After the probability model is constructed by sampling the known probability distribution, since each probability model can be regarded as being composed of various probability distributions, the generation of a random variable (or a random vector) of the known probability distribution becomes a basic means for realizing a simulation experiment of the monte carlo method, which is also called random sampling. The problem of generating random numbers is the sampling problem from this distribution. On a computer, random numbers may be generated physically. From the known distributed random sampling there are various methods, which are implemented with the aid of random sequences, which are premised on the generation of random numbers;
and step four, determining an expected failure set. The invention needs to consider the capability of the power distribution network for keeping safe operation (such as line tide, node voltage not exceeding the limit and the like) when relevant nodes and equipment in the power distribution network have faults and a large number of photovoltaic power supplies are connected into the power distribution network. And extracting important or sensitive node numbers of expected accidents, forming an accident set by the important or sensitive node numbers, and recording the failure rate of the accident set. The set of expected accidents in the present embodiment is set to have a failure at the bus bars L1, L2, L3, and L4.
And fifthly, under the generated calculation scene, investigating and registering the result of the simulation experiment, and obtaining the solution of the problem from the result. And (4) carrying out load flow calculation under each sampling boundary according to the sampled photovoltaic and load power values and the element state (whether a fault occurs), and repeating the calculation process to obtain the load flow distribution under each sampling scene. Analyzing the safety of the planning scheme by combining the safety behavior indexes, and extracting a statistical rule, probability indexes and the like from the safety behavior indexes to be used as a basis for evaluating the planning scheme;
and step six, defining a behavior index to describe the severity of the expected accident. Common power flow calculation and analysis indexes comprise line power flow out-of-limit proportion, net rack power, electric energy loss and the like. According to the index definition formula and the calculation method, the evaluation result of the safety of the power distribution network when the photovoltaic power supply with the rated power of 1MW is connected to the node 5 is calculated and obtained as shown in the following table:
TABLE 1 evaluation result of photovoltaic access security of distribution network
Figure BDA0003377287770000081
And step seven, substituting the calculation result into the formula to analyze and evaluate the value of the index according to the load flow calculation result. And taking the result as a safety comprehensive analysis result of the scene to be evaluated. And comparing the index calculation result of the grid to be evaluated with the basic grid before photovoltaic access or the grid adopting corresponding improvement and promotion measures so as to analyze the influence of the photovoltaic access on the safe operation capacity of the power distribution network and the like.
The safety evaluation results when no photovoltaic power supply is connected to the distribution network are shown in the following table:
TABLE 2 evaluation results of distribution network photovoltaic non-access security
Figure BDA0003377287770000082
In the embodiment of the invention, the load of each load node is generally heavier, the system load flow is heavier when the power supply is not accessed at the tail end of the system, the out-of-limit risk is higher, and the problem of heavy overload of a circuit is more obvious. The photovoltaic power supply in the system plays a certain role in lifting the whole voltage of the system after being connected, meanwhile, the pressure of the load node receiving power from a superior power grid is reduced, and the photovoltaic power supply system plays a certain role in relieving the problem of power flow out-of-limit of a distribution network system.
The foregoing detailed description of the preferred embodiments of the invention has been presented. It should be understood that numerous modifications and variations could be devised by those skilled in the art in light of the present teachings without departing from the inventive concepts. Therefore, the technical solutions available to those skilled in the art through logic analysis, reasoning and limited experiments based on the prior art according to the concept of the present invention should be within the scope of protection defined by the claims.

Claims (10)

1. A photovoltaic access power distribution network safety evaluation method based on a random power flow method is characterized by comprising the following steps: (1) carrying out investigation and collection on various parameters required by evaluation related to the evaluation of the operation safety of the power distribution network; (2) constructing or describing a probability process of photovoltaic output and load uncertainty elements; (3) sampling to generate photovoltaic and load sequences which obey corresponding probability distribution, wherein the formed combination is a calculation scene of random power flow concern and research; (4) determining an expected failure set; (5) under the generated calculation scene, investigating and registering the result of the simulation experiment to obtain the solution of the problem; (6) defining a behavior index PI for describing the severity of the expected accident; (7) and substituting the calculation result into the formula to analyze the value of the evaluation index according to the load flow calculation result, and taking the value as a safety comprehensive analysis result of the scene to be evaluated.
2. The photovoltaic access distribution network safety evaluation method based on the random power flow method as claimed in claim 1, wherein the step (1) comprises: the method comprises the following steps of setting installed capacity of various photovoltaic power supplies related to an object to be evaluated, power supply range of the photovoltaic power supplies, capacity of a power distribution network system upper-level power supply and a standby power supply, maximum energy supply capacity of the photovoltaic power supplies, energy consumption requirements of various load nodes in the power distribution network, historical output data of the photovoltaic power supplies and historical load data.
3. The photovoltaic access power distribution network safety evaluation method based on the random power flow method as claimed in claim 2, wherein the power supply range of the photovoltaic power supply is determined by the connection relationship between the photovoltaic power supply and the load nodes, and the network frame topology and the operation mode; the maximum energy supply capacity of the photovoltaic power supply is determined by combining the investigation result and the design parameter and is expressed by power; the energy consumption requirements of various load nodes in the power distribution network are determined by combining background design data and are expressed by power; the historical output data of the photovoltaic power supply comprises the historical output level of photovoltaic power supplies in the same type of regions, wherein the photovoltaic power supplies in the power distribution network to be evaluated are planned or newly built power supplies.
4. The photovoltaic access distribution network safety assessment method based on the random power flow method as claimed in claim 1, wherein the step (2) is to correctly describe and simulate the probability process for the problem which is random in nature; for the problem of certainty that the problem is not random in nature, an artificial probability process is constructed in advance, certain parameters of the artificial probability process are just the solution of the required problem, namely the problem without random nature is converted into the problem with random nature, the photovoltaic output at a certain moment follows Beta distribution corresponding to the moment, and the load follows normal distribution.
5. The photovoltaic access distribution network safety assessment method based on the random power flow method according to claim 1, wherein the renewable energy output level and the load level according to which the power flow is calculated in step (3) are obtained by sampling from probability distribution fitted or modeled based on historical data, and the photovoltaic output level and the load level formed by each sampling are combined to be used as a basic boundary of the power flow calculation.
6. The photovoltaic access power distribution network safety evaluation method based on the random power flow method as claimed in claim 1, wherein the step (4) considers that when relevant nodes and equipment in the power distribution network have faults and a photovoltaic power supply is accessed in the power distribution network, the power distribution network keeps the capability of safe operation such as line power flow and node voltage not to exceed the limit; important or sensitive node numbers of expected accidents are extracted and form an accident set, and the failure rate of the accident set is recorded, wherein the accident nodes or equipment in the expected accident set only relate to one place, namely, the provided safety assessment method is developed under the N-1 scene.
7. The photovoltaic access distribution network safety evaluation method based on the random power flow method as claimed in claim 1, wherein the step (5) is to perform power flow calculation under each sampling boundary according to whether the sampled photovoltaic and load power values and element states have faults or not, and repeat the calculation process to obtain the power flow distribution under each sampling scene; analyzing the safety of the planning scheme by combining the safety behavior indexes, and extracting a statistical rule and probability indexes from the safety behavior indexes to be used as a basis for evaluating the planning scheme; and (5) converting the power distribution network power flow calculation after photovoltaic access into a power flow calculation process of a conventional power distribution network frame after determining the external boundaries of photovoltaic output and load levels.
8. The photovoltaic access distribution network safety assessment method based on the random power flow method as claimed in claim 1, wherein the index in step (6) is a power flow calculation analysis index, and the power flow calculation analysis index comprises a line power flow out-of-limit proportion and grid power and electric energy loss; the indexes are in the form of determined values, and because the active power and the reactive power in the network have no coupling or are only in weak coupling relation, two behavior indexes are defined: an active power index and a reactive power index; in the step (6), four behavior indexes are defined in total, including four indexes of active power behavior, reactive power behavior, power out-of-limit behavior and average deviation degree of voltage.
9. The method for evaluating the safety of the photovoltaic access distribution network based on the random power flow method as claimed in claim 8,
(1) the active power behavior index is as follows: the index for measuring the active power overload degree of the feeder line is calculated according to the following formula:
Figure FDA0003377287760000021
in the formula: w is apIs an active power weight factor; piIs the active power flow in line i; pi maxAn upper limit value of active power of the line i; alpha is the line set with active power overload;
(2) reactive power behavior index: the indexes for measuring the out-of-limit degree of the voltage and the reactive power are calculated according to the following formula:
Figure FDA0003377287760000031
in the formula: w is auIs a voltage weight factor; u shapekIs the voltage modulus of node k;
Figure FDA0003377287760000032
is the voltage modulus limit of node k; beta is a node set with the voltage modulus out of limit; w is aqIs a reactive power weight factor; qkIs the value of reactive power injected into node k;
Figure FDA0003377287760000033
is the reactive power limit for injection node k; gamma is a node set with out-of-limit reactive power;
alpha, beta and gamma are all limited to out-of-limit lines or nodes; w is ap、wu、wqThe parameters can be adjusted, the values of the parameters are related to the operation experience and the importance of related lines and nodes under different out-of-limit conditions, and the values are 1 under the condition of lacking of actual data;
(3) power out-of-limit probability: the safety analysis is carried out by using a random power flow algorithm, and the obtained power flow is a time-varying value, so that the power out-of-limit condition cannot be measured by only 'yes' or 'no', and is represented by a probability index; accordingly, a power threshold crossing index is defined and calculated according to the following formula:
Figure FDA0003377287760000034
in the formula: n is the total volume of the sampling sample of the Monte Carlo simulation method; n isiThe number of samples is the number of times of power out-of-limit of the line i in the sampling samples;
(4) average degree of voltage deviation: because the number of nodes of the distribution network system is large, in order to better represent the voltage condition of the whole system, particularly the voltage drop phenomenon, the average deviation degree of the voltage is defined and calculated according to the following formula:
Figure FDA0003377287760000035
in the formula: k is a set of all nodes in the distribution network system; u shapekThe voltage value of the node k is the average value of the random power flow; u shapeNThe rated voltage value of the distribution network system is obtained; and m is the number of nodes of the system.
10. The photovoltaic access power distribution network safety evaluation method based on the random power flow method as claimed in claim 9, wherein the step (7) compares the index calculation result of the grid to be evaluated with the basic grid before photovoltaic access or the grid adopting corresponding modification and improvement measures, so as to analyze the influence of the photovoltaic access on the power distribution network safety operation capability; in the step (7), the influence of photovoltaic access on the operation safety of the power distribution network is described by combining the comprehensive calculation result of the behavior index and the comparison of the existence of photovoltaic access, and the influence on the power distribution network by the photovoltaic power supply of a specific scale after being accessed can be analyzed by combining the influence on the power distribution network and the operation condition of the photovoltaic power supply of a specific scale, so that the adaptability of the power distribution network to the photovoltaic power supply and the capability of the grid frame to be evaluated to be further accessed to the photovoltaic power supply are analyzed.
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