Active power distribution network vulnerability evaluation and weak link identification method

Abstract

The invention relates to the technical field of power system analysis, and discloses an active power distribution network vulnerability evaluation and weak link identification method, which comprises the following steps of: firstly, constructing an equivalent sparse graph model of a power distribution network according to an actual topological structure and parameters of the active power distribution network, and then, considering the influence of degrees of adjacent nodes and power flow distribution information; calculating an improved betweenness index of each node and an improved degree index of the line; then considering the influence of each load on actual operation, designing and calculating a node voltage out-of-limit index, finally determining a weight coefficient of each evaluation index by adopting an analytic hierarchy process, and calculating a comprehensive vulnerability index of each node and line according to the weight coefficient of each index; the comprehensive vulnerability indexes of the nodes and the lines are arranged in a descending order, the vulnerable nodes and the vulnerable lines are determined, the improved node degree and line degree indexes provide a finer and more comprehensive view angle for evaluating the vulnerability of the power distribution network, and the operation safety and reliability of the power distribution network can be improved.

Description

Technical Field

[0001] The invention belongs to the technical field of power system analysis, and in particular relates to a method for vulnerability assessment and weak link identification of an active distribution network. Background Art

[0002] With the rapid development of the industrial age, governments around the world have encouraged the development of renewable energy, such as wind and solar energy, to varying degrees to solve global environmental problems. The use of these new energy sources has become an important means for human society to save energy, reduce emissions, and live a green and low-carbon life. However, these new energy generation methods, especially the access to distributed generation, have brought many challenges to the distribution network, including security and vulnerability issues. After the distributed power source is connected to the distribution network, the voltage distribution of the power grid will change. In steady-state conditions, the voltage near the grid connection point increases due to the reduction of transmission power on the feeder and the output of reactive power by the distributed power source. The degree of voltage increase is related to the installation location and capacity of the distributed power source.

[0003] In addition, the output power of distributed power sources is highly volatile and uncertain, which can easily cause voltage fluctuations in the distribution network. For example, natural energy power generation systems are affected by changes in external energy input, cogeneration units are affected by changes in heating requirements, and the owners of distributed power equipment may perform random start and stop operations, which can all lead to voltage fluctuations.

[0004] Therefore, the distribution network often becomes fragile due to its own reasons or external interference, resulting in unstable power supply. The main purpose of vulnerability assessment is to find out the vulnerable points and vulnerable links in the power grid so as to better formulate and invest in preventive measures. At present, many researchers and scholars have explored vulnerability analysis as the main feature of blackouts to explain the root cause of chain reaction failure. Although the structure of urban distribution networks is basically mature, the load is concentrated in some areas, and there may be insufficient local power supply capacity. Some transformers and lines still have heavy overload problems and have not yet fully met the N-1 standard, resulting in weak links in the distribution network, an increase in the frequency of power outages in the distribution network, and the system is no longer safe, stable and reliable.

[0005] In order to evaluate the vulnerability of the distribution network and identify the weak links, scientific methods and technical means are needed. In recent years, with the development of computer technology and artificial intelligence, some new evaluation methods have been proposed and applied, such as the evaluation model based on neural networks. However, the current risk assessment index system of active distribution networks is still not perfect, and it is impossible to deeply measure and classify the various evaluation indicators of the distribution network, thereby providing a valuable theoretical basis for the generation decision of the distribution network.

[0006] In summary, the present invention proposes a method for vulnerability assessment and weak link identification of active distribution network, aiming to meet the above challenges and improve the safety and reliability of distribution network. The present invention establishes a complete assessment system from three aspects: nodes, lines and overall voltage level. The present invention adopts scientific methods and technical means, including building models, calculating indicators, evaluating voltage stability, determining weights and comprehensive evaluation, to identify vulnerable links in distribution network. Summary of the invention

[0007] The present invention aims to solve the problems in the above-mentioned prior art, namely, the increased safety vulnerability, the difficulty in controlling voltage fluctuations, the imperfect risk assessment index system, the widespread problem of heavy overload, and the lack of scientific and effective assessment methods. These problems together lead to inaccurate identification of the vulnerability and weak links of the distribution network, affecting the safe and stable operation of the distribution network and the formulation of preventive measures.

[0008] To achieve the above object, the present invention provides the following technical solutions:

[0009] A method for vulnerability assessment and weak link identification of an active distribution network comprises the following steps:

[0010] S1. According to the actual topological structure and parameters of the active distribution network, an equivalent sparse graph model of the distribution network is constructed;

[0011] S2, considering the influence of adjacent node degrees and power flow distribution information, calculate the improved betweenness index of each node and the improved degree index of the line;

[0012] S3. Considering the impact of each load on the actual operation, design and calculate the node voltage over-limit index, and quantitatively evaluate the risk of voltage instability in the distribution network;

[0013] S4. Use the hierarchical analysis method to determine the weight coefficient of each evaluation index. According to the weight coefficient of each index, calculate the comprehensive vulnerability index of each node and line; arrange the comprehensive vulnerability index of each node and line in descending order to determine the vulnerable nodes and lines.

[0014] Preferably, in step S1, basic components for constructing an equivalent sparse graph model of a distribution network include nodes, lines, and distributed power sources.

[0015] Node: A node is a basic connection point in a power system, representing each substation, distribution room, load point, or access point of a distributed power source in the power grid. In a distribution network model, a node usually represents a physical location in the power grid and is the basis of the power grid topology. Nodes are connected to each other through lines.

[0016] Line: Line is a conductive path connecting various nodes for transmitting electrical energy. In the distribution network model, the line represents the transmission line or distribution line, which has electrical characteristics such as resistance, inductance and capacitance, and has an important impact on the stability and power quality of the power system.

[0017] Distributed power sources: Distributed power sources refer to small power sources connected to the distribution network, such as solar photovoltaic panels, wind turbines, small hydroelectric generators, fuel cells, etc. These power sources are usually small in scale and can be flexibly connected to the distribution network to provide local power supply or support the stable operation of the power grid.

[0018] In the distribution network model, these components are used to simulate and analyze the actual operation of the power grid, including the flow of electric energy, voltage distribution, load changes, and the impact of the access of distributed power sources on the power grid. By mathematically modeling and simulating these components, researchers can evaluate the performance of the distribution network, optimize the grid structure, and improve power supply efficiency and reliability.

[0019] Preferably, in step S2, the improved betweenness index of each node and the improved degree index of the line are calculated by the following steps;

[0020] S201: Considering the network sparsity of the distribution network, combined with the cohesion fusion theory, the improved betweenness index of node i is calculated according to the number of connected edges of each node i, the average node degree of the system, and the set of all nodes with edges to each node i. The calculation formula is as follows:

[0021]

[0022] Where: D i is the number of edges connected to node i; is the average node degree of the system; V ad is the set of all nodes that have edges with node i;

[0023] S202: Considering the importance of nodes connected by the line, according to the reactance value of line i, using the average node degree of the system nodes, determine the new degrees of the first and last nodes of the node pair connected by the line, and calculate the improved degree index of line i by combining the line length and reactance value. The calculation formula is as follows:

[0024]

[0025] Where: D Li is the reactance value of line i, is the average node degree of the system nodes, D Nli1 , D Nli2 Line l i The new degrees of the first and last nodes of a connected node pair.

[0026] Preferably, in step S3, the node voltage over-limit index is designed and calculated, and the risk of voltage instability in the distribution network is quantitatively evaluated by the following steps:

[0027] S301, propose a node voltage over-limit index: define a node voltage over-limit index to reflect whether the node voltage exceeds the specified limit range and the severity of the impact of the exceeding degree on the distribution network;

[0028] S302, determine the voltage deviation limit: according to the provisions of the 10kV power grid, determine that the voltage deviation limit is 7%;

[0029] S303, construct voltage over-limit expression: the expression of node voltage over-limit index is:

[0030]

[0031] Where: U i is the per-unit voltage value of line i.

[0032] As a preferred embodiment, it is known from the node voltage over-limit index expression that when the voltage value is 1.0pu, the index is 0, and as the voltage gradually shifts, the voltage over-limit value also increases.

[0033] Preferably, in step S4, the specific steps of determining the weight coefficients of each evaluation index by using the hierarchical analysis method and calculating the comprehensive vulnerability index of each node and line according to these weight coefficients are as follows:

[0034] S401, normalization processing: normalize each vulnerability assessment indicator. The normalization processing line is completed by taking the maximum value of each indicator as the benchmark value and then dividing each indicator value by the maximum value of the indicator. The normalization expression is:

[0035]

[0036] S402. Establishment of node / line comprehensive vulnerability index: The normalized complex network conceptual node betweenness index D Ni 、Line degree index B Ni and node voltage over-limit index N URi The comprehensive vulnerability index of node / line i is expressed as follows:

[0037] N i =(ω1D Ni +ω2D Li +ω3N URi );

[0038] Among them, ω1 is the weight coefficient of the node betweenness index, ω2 is the weight coefficient of the line degree index, and ω3 is the weight coefficient of the node voltage over-limit index.

[0039] S403, sorting to determine vulnerable nodes and lines: Use the hierarchical analysis method to determine the weight coefficient of each evaluation index, and arrange them in descending order according to the calculated comprehensive vulnerability index of each node and line, and determine the nodes and lines with higher comprehensive vulnerability indexes as vulnerable nodes and lines.

[0040] Compared with the prior art, the technical effects and advantages of the present invention are:

[0041] The vulnerability assessment and weak link identification method of active distribution network is based on the actual topological structure and parameters of the distribution network, and an equivalent sparse graph model including nodes, lines, distributed power sources and other components is constructed; the influence of the degree of adjacent nodes and the power flow distribution information are considered to calculate the improved betweenness index of each node and the improved degree index of the line; the node voltage over-limit index is designed and calculated to quantitatively evaluate the risk of voltage instability of the distribution network under specific operating conditions; the analytic hierarchy process (AHP) is used to determine the weight coefficient of each evaluation index; the comprehensive vulnerability index of each node and line is calculated according to the weight coefficient; the comprehensive vulnerability index is arranged in descending order to determine the vulnerable nodes and lines in the distribution network.

[0042] By identifying vulnerable nodes and lines, targeted measures can be taken to enhance the stability of these links, thereby improving the safety and reliability of the entire distribution network. Quantitative assessment of voltage instability risks can help prevent cascading failures and large-scale power outages, and reduce economic losses and social impacts caused by failures. It provides a theoretical basis for the generation of distribution network decisions, helps optimize resource allocation, and improves grid operation efficiency. This method combines computer technology and artificial intelligence to promote the intelligent management of distribution networks and lay the foundation for the intelligent upgrade of future power grids. By conducting regular vulnerability assessments, grid maintenance and overhaul strategies can be adjusted in a timely manner, extending equipment life and reducing maintenance costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 A step diagram of a vulnerability assessment and weak link identification method for active distribution networks. DETAILED DESCRIPTION

[0044] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0045] The following is combined with Figure 1 To further explain this application in detail,

[0046] The present application embodiment discloses a method for controlling voltage of a microgrid in a substation based on improved deep reinforcement learning theory, including:

[0047] S1. According to the actual topological structure and parameters of the active distribution network, an equivalent sparse graph model of the distribution network is constructed, including nodes, lines, distributed power sources and other components;

[0048] S2, considering the influence of adjacent node degrees and power flow distribution information, calculate the improved betweenness index of each node and the improved degree index of the line;

[0049] S3. Considering the impact of various loads on actual operation, design and calculate node voltage over-limit indicators, and quantitatively evaluate the risks of distribution network failures and serious power outages under certain operating conditions.

[0050] S4. Use the analytic hierarchy process (AHP) to determine the weight coefficient of each evaluation index. According to the weight coefficient of each index, calculate the comprehensive vulnerability index of each node and line; arrange the comprehensive vulnerability index of each node and line in descending order to determine the vulnerable nodes and lines.

[0051] During the specific implementation process, the vulnerability assessment and weak link identification of the active distribution network are carried out through the following steps:

[0052] Specifically, in step S2, the improved betweenness index of each node and the improved degree index of the line are calculated by the following steps;

[0053] S201: In view of the fact that the distribution network is relatively sparse compared to the transmission network, the cohesion fusion theory is considered. When calculating the node degree, the influence of other nodes around the node also needs to be considered. Therefore, an improved node degree calculation method is proposed:

[0054]

[0055] Where: D i is the number of edges connected to node i; is the average node degree of the system; V ad is the set of all nodes that have edges with node i.

[0056] S202: The degree of an edge or line is also used to evaluate the importance of the line, because it can represent the importance of the nodes connected by the line. The higher the degree of the two connected nodes, the more important the line is in the network. However, when considering the importance of the line, the line length is also an important factor. Therefore, in the improved line degree calculation, the line length needs to be considered, and its expression is:

[0057]

[0058] Where: D Li is the reactance value of line i, is the average node degree of the system nodes, D Nli1 , D Nli2 Line l i The new degrees of the first and last nodes of a connected node pair.

[0059] Specifically, in step S3: design and calculate the node voltage over-limit index, and quantitatively evaluate the voltage instability risk of the distribution network. This is carried out through the following steps:

[0060] S301: Propose a node voltage over-limit index. The node voltage over-limit reflects the impact and severity when its value is not within the limit range. Since the voltage deviation of the 10kV power grid is 7%, the node voltage over-limit expression is:

[0061]

[0062] Where: U i is the per-unit voltage value of line i. From formula (3), it can be obtained that when the voltage value is 1.0pu, the index is 0. As the voltage gradually shifts, its voltage limit value also increases.

[0063] Specifically, in step S4, the following steps are performed to determine the weight coefficient of each evaluation index using the analytic hierarchy process (AHP), and the comprehensive vulnerability index of each node and line is calculated according to the weight coefficient of each index; the comprehensive vulnerability index of each node and line is arranged in descending order to determine the vulnerable nodes and lines:

[0064] S401: Normalize each vulnerability assessment indicator. Normalization can be done by taking the maximum value of each indicator as the reference value and then dividing each indicator value by the reference value. The normalization expression is:

[0065]

[0066] S402: Establishment of comprehensive vulnerability index of nodes / lines, and the concept of complex network node betweenness index D Ni 、Line degree index B Ni and node voltage over-limit index N URi The comprehensive vulnerability index expression of node / line i is:

[0067] N i =(ω1D Ni +ω2D Li +ω3N URi) (5)

[0068] S403: Obtain comprehensive vulnerability indexes of nodes and lines according to the hierarchical analysis method, and find out weak links in the topological network.

[0069] The vulnerability assessment and weak link identification method of the active distribution network, the improved node degree and line degree indicators are based on the traditional degree indicators, by introducing more factors and refining the calculation method to more comprehensively reflect the topological structure and operation characteristics of the distribution network.

[0070] The advantages of the improved node degree indicator are as follows:

[0071] The improved node degree index takes into account the influence of adjacent nodes when calculating, which not only reflects the number of edges connected to the node, but also considers the interaction between nodes in the network, making the index more reflective of the actual importance of the node in the power grid.

[0072] In distribution networks, the network is often sparse. The improved index can better adapt to this characteristic by integrating the cohesion theory, thereby more accurately measuring the centrality and connectivity of nodes in the network.

[0073] The improved node degree can dynamically reflect the state changes of the power grid, including network reconstruction after a fault, which is of great significance for real-time monitoring of power grid vulnerability.

[0074] The advantages of the improved line degree index are as follows:

[0075] The improved line degree metric considers not only the number of nodes connected by a line but also the degree of these nodes, thereby giving more importance to lines connecting important nodes, which have a greater impact on the stability and vulnerability of the power grid.

[0076] When calculating the line degree, adding the line length and reactance value as parameters can reflect the electrical characteristics of the line more carefully, thereby better evaluating its impact on the grid performance.

[0077] The improved line degree metric helps to identify the fault propagation paths in the power grid, which is important for understanding the fault propagation mechanism and vulnerability of the power grid under extreme conditions.

[0078] Through the above improvements, the new degree index can more accurately reflect the vulnerability of the distribution network in the following aspects: Considering the interaction between nodes and lines, providing a more comprehensive topological analysis, so as to more accurately identify the key nodes and key lines in the power grid. Dynamically reflect the performance of the power grid under different operating conditions, and provide support for analyzing the vulnerability of the power grid under extreme weather or other interference. By identifying the critical path of fault propagation, it helps to understand the fault propagation mechanism of the power grid, so as to strengthen the weak links of the power grid in a targeted manner.

[0079] In summary, the improved node degree and line degree indicators provide a more refined and comprehensive perspective for assessing the vulnerability of distribution networks, which helps to improve the operational safety and reliability of distribution networks.

[0080] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for vulnerability assessment and weak link identification of active distribution network, characterized in that: The steps include: S1. According to the actual topological structure and parameters of the active distribution network, an equivalent sparse graph model of the distribution network is constructed; S2, considering the influence of adjacent node degrees and power flow distribution information, calculate the improved betweenness index of each node and the improved degree index of the line; S3. Considering the impact of each load on the actual operation, design and calculate the node voltage over-limit index, and quantitatively evaluate the risk of voltage instability in the distribution network; S4. Use the hierarchical analysis method to determine the weight coefficient of each evaluation index. According to the weight coefficient of each index, calculate the comprehensive vulnerability index of each node and line; arrange the comprehensive vulnerability index of each node and line in descending order to determine the vulnerable nodes and lines.

2. The method for vulnerability assessment and weak link identification of an active distribution network according to claim 1, characterized in that: In step S1, the components of constructing an equivalent sparse graph model of a distribution network include nodes, lines, and distributed power sources.

3. The method for vulnerability assessment and weak link identification of an active distribution network according to claim 1, characterized in that: In step S2, the improved betweenness index of each node and the improved degree index of the line are calculated by the following steps; S201: Considering the network sparsity of the distribution network, combined with the cohesion fusion theory, the improved betweenness index of node i is calculated according to the number of connected edges of each node i, the average node degree of the system, and the set of all nodes with edges to each node i. The calculation formula is as follows: Where: D i is the number of edges connected to node i; is the average node degree of the system; V ad is the set of all nodes that have edges with node i; S202: Considering the importance of nodes connected by the line, according to the reactance value of line i, using the average node degree of the system nodes, determine the new degrees of the first and last nodes of the node pair connected by the line, and calculate the improved degree index of line i by combining the line length and reactance value. The calculation formula is as follows: Where: D Li is the reactance value of line i, is the average node degree of the system nodes, D Nli1 , D Nli2 Line l i The new degrees of the first and last nodes of a connected node pair.

4. The method for vulnerability assessment and weak link identification of an active distribution network according to claim 1, characterized in that: In step S3, the node voltage over-limit index is designed and calculated, and the quantitative assessment of the voltage instability risk of the distribution network is carried out through the following steps: S301, propose a node voltage over-limit index: define a node voltage over-limit index to reflect whether the node voltage exceeds the specified limit range and the severity of the impact of the exceeding degree on the distribution network; S302, determine the voltage deviation limit: according to the provisions of the 10kV power grid, determine that the voltage deviation limit is 7%; S303, construct voltage over-limit expression: the expression of node voltage over-limit index is: Where: U i is the per-unit voltage value of line i.

5. The method for vulnerability assessment and weak link identification of an active distribution network according to claim 4, characterized in that: It can be seen from the node voltage over-limit index expression that when the voltage value is 1.0pu, the index is 0. As the voltage gradually shifts, the voltage over-limit value also increases.

6. The method for vulnerability assessment and weak link identification of an active distribution network according to claim 1, characterized in that: In step S4, the weight coefficients of each evaluation index are determined by using the hierarchical analysis method, and the specific steps of calculating the comprehensive vulnerability index of each node and line according to these weight coefficients are as follows: S401, normalization processing: normalize each vulnerability assessment indicator. The normalization processing line is completed by taking the maximum value of each indicator as the benchmark value and then dividing each indicator value by the maximum value of the indicator. The normalization expression is: S402. Establishment of node / line comprehensive vulnerability index: The normalized complex network conceptual node betweenness index D Ni 、Line degree index B Ni and node voltage over-limit index N URi to conduct synthesis; Weights are assigned to these indicators, which reflect the importance of each indicator in the comprehensive assessment. The comprehensive vulnerability index expression of node / line i is: <h2 style=";text-align:left;direction:ltr">N<h2 style=";text-align:left;direction:ltr"> i <h2 style=";text-align:left;direction:ltr"> (ω1D)<h2 style=";text-align:left;direction:ltr"> Ni <h2 style=";text-align:left;direction:ltr"> +ω2D<h2 style=";text-align:left;direction:ltr"> Li <h2 style=";text-align:left;direction:ltr"> +ω3N<h2 style=";text-align:left;direction:ltr"> URi <h2 style=";text-align:left;direction:ltr"> ); Among them, ω1 is the weight coefficient of the node betweenness index, ω2 is the weight coefficient of the line degree index, and ω3 is the weight coefficient of the node voltage over-limit index; S403. Sorting to determine vulnerable nodes and lines: Use the hierarchical analysis method to determine the weight coefficient of each evaluation index, and arrange them in descending order according to the calculated comprehensive vulnerability index of each node and line, and determine the nodes and lines with higher comprehensive vulnerability indexes as vulnerable nodes and lines.

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