Core backbone network frame construction method and system based on survivability of power system

Abstract

The invention discloses a core backbone network frame construction method and system based on survivability of an electric power system, and the method comprises the steps: constructing a corresponding electric power directed graph according to a topological structure of the electric power system; performing statistics on historical power flow data of the power system based on the power directed graph, and constructing survivability indexes of a core backbone network frame; constructing a target function of the core backbone network frame by considering the survivability index and the total line length and connectivity of the core backbone network frame; and optimizing the objective function through a particle swarm optimization algorithm to obtain an optimal core backbone network frame of the power system. According to the method, the survivability of the power system is quantitatively evaluated through the survivability evaluation index, and the optimal core backbone network frame is obtained to improve the operation stability of the power system.

Description

Technical Field

[0001] The present application belongs to the field of power system emergency response, and specifically relates to a method and system for constructing a core backbone grid based on the anti-destruction capability of the power system. Background Art

[0002] The resilience of the power system can be understood as the power system's ability to maintain the maximum power supply to key users under unconventional extreme conditions. It contains two connotations: First, in unconventional extreme scenarios, due to deliberateness and strong suddenness, the power system cannot take into account the power demand of most users ("supply guarantee" demand), and it is necessary to ensure the power supply of important users ("care" demand). Second, unconventional extreme events are often highly destructive, and the damage to the power system caused by them often cannot be restored in a short period of time, so it cannot be described by the resilience of the power system. In order to improve the resilience of the power system, the core backbone grid of the power system is often constructed to ensure that the relatively important parts of the power system network structure, including important loads, important power sources, and important lines, can operate stably in extreme scenarios.

[0003] There are two existing methods for constructing the core backbone grid of the power system. One is based on the importance of power grid components. By drawing a directed graph of the power grid topology, the importance of power grid components is ranked based on graph theory, and the components with high importance are included in the backbone grid. However, this method only considers the connection relationship and flow characteristics of power grid components, and does not consider the survival properties of the power grid in extreme scenarios. The core backbone grid constructed does not evaluate the survivability under extreme events from the perspective of anti-destruction. The second is to select important branches from the perspective of the business functions of the power grid branches and construct the backbone grid using the cost-effectiveness method. This method is only helpful in accelerating the recovery speed of the power grid in conventional scenarios, and cannot be applied in extreme scenarios. Its applicability is not high. Summary of the invention

[0004] This application proposes a method and system for constructing a core backbone grid based on the indestructibility of the power system, taking into account the indestructibility of the power system in extreme scenarios to construct an optimal core backbone grid, thereby improving the operating stability of the power system in various scenarios.

[0005] The first aspect of the present application provides a method for constructing a core backbone grid based on power system invulnerability, the method comprising:

[0006] According to the topological structure of the power system, the corresponding power directed graph is constructed;

[0007] Based on the power directed graph, the historical power flow data of the power system is counted to construct the invulnerability index of the core backbone grid;

[0008] By considering the invulnerability index, the total line length and connectivity of the core backbone network, an objective function of the core backbone network is constructed;

[0009] The objective function is optimized by a particle swarm optimization algorithm to obtain the optimal core backbone grid of the power system.

[0010] The above scheme first constructs a power directed graph that can clearly describe the operation status between nodes and lines in the power system based on the topological structure of the power system. Then, through the nodes and lines in the power directed graph, the historical flow data of the power system is statistically analyzed, and the flow balance of the nodes and lines is evaluated to obtain the anti-destruction index that can be used to evaluate the core backbone grid in extreme scenarios. On the basis of satisfying the anti-destruction index as much as possible, the corresponding objective function is constructed with the comprehensive optimization of the anti-destruction index, the total line length and connectivity of the core backbone grid as the goal. Because the shorter core backbone grid is less likely to be affected by extreme events, it is best to build a core backbone grid with a shorter line length while ensuring that the grid has high connectivity and can withstand extreme events. Finally, the particle swarm optimization algorithm is used to optimize the objective function to obtain an accurate optimal core backbone grid of the power system that can ensure stable operation in extreme scenarios, ensure power supply to important users in various scenarios, and improve power quality.

[0011] In a possible implementation method of the first aspect, a corresponding power directed graph is constructed according to the topological structure of the power system, specifically:

[0012] Collect data from each node of the power system to obtain historical power flow data of the power system;

[0013] Constructing the power directed graph according to the historical power flow data of the power system and the topological structure;

[0014] Constructing a node adjacency matrix of the power directed graph according to the adjacency relationship between the nodes in the power directed graph;

[0015] Based on the node adjacency matrix, the connectivity of the paths between the nodes in the power directed graph is evaluated to obtain the natural connectivity of the nodes in the power directed graph.

[0016] The above scheme is based on the power directed graph, and processes the adjacency relationship and connectivity between each node. It evaluates whether other paths of the node can be used as alternative paths to ensure the normal operation of the power system when some paths fail and become unavailable in extreme scenarios. In this way, the natural connectivity of each node is obtained, which is used to evaluate the anti-destruction capability of the power system in extreme scenarios.

[0017] In a possible implementation method of the first aspect, the natural connectivity is specifically:

[0018] Among them, the natural connectivity of the node is specifically expressed as:

[0019]

[0020] In the formula, s i is the natural connectivity of the ith node, N is the total number of nodes, λ i is the characteristic root of the i-th node in the node adjacency matrix.

[0021] In a possible implementation method of the first aspect, historical power flow data of the power system is counted based on the power directed graph to construct a core backbone grid invulnerability index, specifically:

[0022] In view of the resistance, connectivity, safety and recovery of the power system in extreme scenarios, the historical power flow data of the power system is statistically analyzed based on the power directed graph to construct resistance index, connectivity index, safety index and recovery index;

[0023] Among them, resistance indicators include line preservation rate, power preservation rate and load preservation rate; connectivity indicators include grid relative compactness, grid relative cohesion, average power transmission distance and average power transmission margin; safety indicators include line stability margin index, node voltage margin index and power margin index; recovery indicators include generator standby index, load recovery index and number of tie lines index;

[0024] The resistance index, connectivity index, safety index and recovery index are normalized respectively to obtain the indestructibility index.

[0025] The above scheme designs anti-destruction indicators from four aspects: resistance, connectivity, safety and recovery. Taking into account the impact of load loss, power loss, line failure, etc. on the stability of power system operation in extreme scenarios, these indicators can be used to intuitively evaluate the advantages and disadvantages of different grids in extreme scenarios, providing data support for the subsequent construction of the optimal core backbone grid.

[0026] In a possible implementation method of the first aspect, the invulnerability index is specifically:

[0027] The specific formula of the invulnerability index is:

[0028]

[0029] In the formula, S urv is the invulnerability index, ω1, ω2, ω3 are weight coefficients, η is the number of indicators, ψ i is the combination of resistance index, connectivity index, security index and recovery index, s iis the natural connectivity of the ith node, and s0 is the connectivity of the initial grid.

[0030] In a possible implementation method of the first aspect, by considering the invulnerability index, the total line length and connectivity of the core backbone network, an objective function of the core backbone network is constructed, specifically:

[0031] According to the invulnerability index, the total length of the lines of the power system and the switching state of the lines, the objective function is constructed with the comprehensive optimization of the invulnerability index, the total length of the lines of the core backbone grid and the connectivity as the goal;

[0032] According to the power system flow constraints and power system line constraints, the constraints of the core backbone grid are constructed.

[0033] In a possible implementation method of the first aspect, the objective function and the constraint conditions are specifically:

[0034] Among them, the objective function is specifically expressed as:

[0035]

[0036] Where F is the objective function, L1 is the total length of the core backbone grid, L0 is the total length of the power system, and N L is the total number of lines, x i is the switching state of line i, B(i) is the impedance of line i, j is the branch endpoint number of the core backbone network, Q is the set of branch endpoints of the core backbone network, Ψ(j) is the set of resistance index, connectivity index, safety index and recovery index, S urv is the invulnerability index.

[0037] The constraint condition is specifically expressed as follows:

[0038]

[0039] In the formula, l i is the length of line i, N LF is the number of failed lines in the power system after an extreme event in an extreme scenario, H(x,y)≤θ is the power flow inequality constraint of the power system, G(x,y)=0 is the power flow equality constraint of the power system, and Φ(Q) is the connectivity requirement of the core backbone grid.

[0040] In a possible implementation method of the first aspect, the objective function is optimized by a particle swarm optimization algorithm to obtain an optimal core backbone grid of the power system, specifically:

[0041] Using nodes and edges in the power directed graph as particle swarm variables, and updating the particle swarm variables at a preset update speed;

[0042] Based on the constraints of the core backbone network, the current value of the objective function is obtained through the updated particle swarm variables;

[0043] When the updated particle swarm variable meets the preset convergence condition, the current value is used as the optimal solution;

[0044] According to the optimization solution, the optimal core backbone network is constructed.

[0045] In a possible implementation method of the first aspect, the current value of the objective function is obtained by using the updated particle swarm variable, specifically:

[0046] taking the current value of the objective function as a second result;

[0047] Using the updated particle swarm variable to calculate and obtain a first result of the objective function;

[0048] If the first result is less than the second result, the first result is used as the current value of the objective function.

[0049] The second aspect of the present application provides a core backbone grid construction system based on power system invulnerability, the system comprising: a directed graph construction module, an invulnerability index construction module, an objective function construction module and an optimal core backbone grid construction module;

[0050] The directed graph construction module is used to construct a corresponding power directed graph according to the topological structure of the power system;

[0051] The invulnerability index building module is used to collect statistics on the historical power flow data of the power system based on the power directed graph to build the invulnerability index of the core backbone grid;

[0052] The objective function construction module is used to construct the objective function of the core backbone network by considering the invulnerability index, the total line length and connectivity of the core backbone network;

[0053] The optimal core backbone grid construction module is used to optimize the objective function through a particle swarm optimization algorithm to obtain the optimal core backbone grid of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the technical solution of the present application, the drawings required for use in the implementation manner will be briefly introduced below. Obviously, the drawings described below are only some implementation manners of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0055] Figure 1 It is a specific flow chart of a method for constructing a core backbone grid based on power system invulnerability provided by a certain embodiment of the present application;

[0056] Figure 2 It is a specific structural diagram of a core backbone grid construction system based on the anti-destruction property of the power system provided in a certain embodiment of the present application. DETAILED DESCRIPTION

[0057] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0058] It should be understood that the step numbers used in this article are only for the convenience of description and are not intended to limit the order in which the steps are executed.

[0059] First embodiment

[0060] The core backbone grid of the power system includes relatively important parts of the power system network structure, including important loads, important power sources, and important lines. When the power system is subjected to extreme events from extreme scenarios, such as extreme natural disasters, the power supply to key users is often maintained through the core backbone grid, so that the power system can take into account the power needs of important users even when failures occur, and maintain the operational stability of the system. Therefore, how to construct an optimal core backbone grid for the purpose of significantly improving the anti-destruction capability of the power system, so that the power system can maintain power supply to important users to the greatest extent and accelerate the restoration of normal operation of the power grid in both conventional and extreme scenarios, is the main research purpose of the embodiments of this application.

[0061] like Figure 1 As shown, Figure 1 A specific flow chart of a method for constructing a core backbone grid based on the invulnerability of a power system is provided for a certain embodiment of the present application. The method for constructing a core backbone grid based on the invulnerability of a power system of the present embodiment includes steps S1 to S4, which are described in detail as follows:

[0062] Step S1, constructing a corresponding power directed graph according to the topological structure of the power system.

[0063] In the embodiment of the present application, data is collected from each node and line of the power system to obtain historical power flow data of the power system and draw the topological structure of the power system. Then, based on the topological structure, a power directed graph that can reflect the topological and power flow characteristics of the power system is constructed.

[0064] Exemplarily, the power directed graph is defined as G = (V, E), where G represents a set of nodes V and lines E, and satisfies the node υ i ∈V, line e i =(υ i , j )∈E, line e i The direction is from node v i To node v j , the total number of nodes is N B =|V|, the total number of lines is N L =|E|.

[0065] After defining the power directed graph, a node adjacency matrix of the power directed graph is constructed to reflect the adjacency relationship between nodes. The specific expression is:

[0066]

[0067] Among them, the characteristic root of the node adjacency matrix A is λ i , i=1,2,...,N.

[0068] Based on the power directed graph, it can be seen that the more different paths that remain connected between any two nodes in the graph, the greater the probability that the two nodes can still remain connected through another alternative path when some of the paths fail. Correspondingly, it can be approximately considered that the grid of the entire power system has better invulnerability. Therefore, natural connectivity is defined as an indicator for quantitatively evaluating the redundancy of alternative paths between all nodes in the network structure. According to the characteristic root of the node adjacency matrix A, the natural connectivity of each node can be obtained, and the specific expression is:

[0069]

[0070] In the formula, s i is the natural connectivity of the ith node, N is the total number of nodes, λ i is the characteristic root of the i-th node in the node adjacency matrix.

[0071] Because the above-mentioned node adjacency matrix and natural connectivity between nodes are common to the topological structures of most power systems, these evaluation indicators have good versatility and can be applied to most power grids.

[0072] Optionally, when drawing a directed electric power graph, the embodiment of the present application only considers the transmission network and directly connected nodes above the 35kV voltage level, does not consider the distribution network and related nodes below the 35kV voltage level, and also ignores the ground branches of the power grid.

[0073] Step S2, based on the power directed graph, statistics are collected on the historical power flow data of the power system to construct the invulnerability index of the core backbone grid.

[0074] In the embodiment of the present application, the evaluation of the invulnerability of the power system is quantified from four aspects, namely: resistance, connectivity, safety and recovery. Through these four aspects, four different indicators are constructed for the core backbone grid, namely resistance index, connectivity index, safety index and recovery index, which are used to evaluate the constructed core backbone grid to intuitively show the advantages and disadvantages of different grids.

[0075] In view of the resistance, connectivity, safety and resilience of the power system in extreme scenarios, the historical power flow data of the power system is statistically analyzed based on the power directed graph to construct resistance index, connectivity index, safety index and resilience index.

[0076] Among them, resistance indicators include line preservation rate, power preservation rate and load preservation rate; connectivity indicators include grid relative density, grid relative cohesion, average power transmission distance and average power transmission margin; safety indicators include line stability margin index, node voltage margin index and power supply power margin index; recovery indicators include generator standby index, load recovery index and number of interconnection lines index.

[0077] Specifically, the line preservation rate, the relative density of the grid, the relative cohesion of the grid, the average power transmission distance and the average power transmission margin are obtained based on the flow data statistics of the nodes and lines in the power directed graph.

[0078] The line preservation rate D i (1), the specific expression is:

[0079]

[0080] Among them, N LF is the number of failed lines in the power system after the extreme event, N L is the total number of lines in the power system.

[0081] The power conservation rate D i (2), the specific expression is:

[0082]

[0083] Where W BFis the amount of power loss in the power system after the impact of an extreme event, W B is the total number of power sources in the power system.

[0084] The load preservation rate D i (3), the specific expression is:

[0085]

[0086] Among them, LO BF is the load loss amount of the power system after the extreme event, LO B is the total number of loads in the power system.

[0087] The relative tightness K of the grid i (1), the specific expression is:

[0088]

[0089] In the formula, K i Indicates that there are K nodes around node i i neighboring nodes, and there are t i lines, C0 is the grid density of the power system, N B is the total number of nodes, N BF is the total number of nodes affected by the extreme event.

[0090] The relative cohesion degree K of the grid i (2), the specific expression is:

[0091]

[0092] Where K0 is the grid cohesion of the power system, It is the number of weighted edges when the equivalent impedance of the power line is the smallest.

[0093] The average transmission distance of electric energy K i (3), the specific expression is:

[0094] The average transmission distance of electric energy K i (3), the specific expression is:

[0095]

[0096] Where D path (i) is the electrical distance of the i-th power flow transmission path, which is the sum of the reactance values ​​of all branches on the path.

[0097] The average power transmission margin K i (4), the specific expression is:

[0098]

[0099] Where ΔP path (i) is the active power margin of the i-th power transmission path, P max (i), P path (i) are the active power over-limit value and real-time value of the i-th power flow transmission path respectively.

[0100] The generator standby index H i (1), the specific expression is:

[0101]

[0102] In the formula, G max (i), G(i) is the maximum installed capacity and actual output of the i-th generator, N G is the number of generators in the power system.

[0103] The load recovery index H i (2), the specific expression is:

[0104]

[0105] Where P m is the maximum active power of the current core backbone network, and P is the actual active power of the current core backbone network.

[0106] The contact line number index H i (3), the specific expression is:

[0107]

[0108] Where N LL is the number of interconnection lines in the current core backbone grid, L(i) is the total length of the ith interconnection line, and L0 is the total length of the power system lines.

[0109] Then, the resistance index D i , connectivity index K i , Safety index U i and the recovery index H i Normalize to form a new normalized index Among them, i ∈[0,1],i=1,...,N B , which is a collection of resistance indicators, connectivity indicators, security indicators and resilience indicators.

[0110] According to the normalized index, the anti-destruction index of the power system for the core backbone grid is constructed, and the specific formula is:

[0111]

[0112] In the formula, S urv is the invulnerability index, ω1, ω2, ω3 are weight coefficients, η is the number of indicators, ψ i is the combination of resistance index, connectivity index, security index and recovery index, s i is the natural connectivity of the ith node, and s0 is the connectivity of the initial grid. Among them, the weight coefficient needs to satisfy

[0113] In the embodiment of the present application, η is taken as 10, ||Ψ i || ∞ =max|Ψ i |.

[0114] Step S3, constructing an objective function of the core backbone network frame according to the invulnerability index and taking the total length of the core backbone network frame as the shortest.

[0115] In the embodiment of the present application, the designed core backbone grid not only needs to meet the anti-destruction index and high connectivity, but also needs to consider the total length of the lines in the grid. Generally speaking, a shorter core backbone grid is less likely to be affected by extreme events, so a core backbone grid with a shorter line length is constructed as much as possible.

[0116] According to the invulnerability index, the total length of the lines of the power system and the switching state of the lines, the objective function is constructed with the comprehensive optimization of the invulnerability index, the total length of the lines of the core backbone grid and the connectivity as the goal. The specific expression is:

[0117]

[0118] Where F is the objective function, L1 is the total length of the core backbone grid, L0 is the total length of the power system, and N L is the total number of lines, x i is the switching state of line i, B(i) is the impedance of line i, j is the branch endpoint number of the core backbone network, Q is the branch endpoint set of the core backbone network, Ψ(j) is the combination of resistance index, connectivity index, safety index and recovery index, S urv is the invulnerability index.

[0119] The switching status can reflect the connectivity of the core backbone network.

[0120] When constructing the optimal core backbone network through the objective function, the following constraints need to be met:

[0121]

[0122] In the formula, l i is the length of line i, N LF is the number of failed lines in the power system after the impact of extreme events, H(x,y)≤θ is the power flow inequality constraint of the power system, G(x,y)=0 is the power flow equality constraint of the power system, and Φ(Q) is the connectivity requirement of the core backbone grid.

[0123] Among them, the constraints of the core backbone grid are constructed based on the power system's flow constraints and power system's line constraints.

[0124] Step S4, optimizing the objective function by using a particle swarm optimization algorithm to obtain an optimal core backbone grid of the power system.

[0125] In an embodiment of the present application, the nodes and edges in the power directed graph are used as particle swarm variables, and the particle swarm variables are updated at a preset update speed.

[0126] For example, based on the power directed graph G(V, E), using (V i , E i ) as the particle swarm variable,

[0127] Initialize the particle swarm to (V0, E0), and initialize the current minimum value of the objective function to:

[0128]

[0129] The particle swarm variables are updated at the preset update speeds Δv and Δe, that is, the update value of the particle swarm variables is set to (V i +Δυ,E i +Δe), where (Δυ, Δe) represent the speed values ​​of the set of nodes V and lines E respectively.

[0130] Then, based on the constraints of the core backbone network, the current value of the objective function is obtained through the updated particle swarm variables. Then, it is determined whether the current value is less than the minimum value of the objective function, and if it is less than the minimum value, the minimum value of the objective function is updated.

[0131] Specifically, the current value of the objective function is taken as the second result; the first result of the objective function is calculated using the updated particle swarm variable; if the first result is less than the second result, the first result is taken as the current value of the objective function.

[0132] Finally, when the updated particle swarm variable meets the preset convergence condition, the current value is used as the optimal solution;

[0133] Specifically, the convergence condition may be to determine whether the current particle swarm variable exceeds the maximum grid of the power system, that is, the power directed graph G=(V, E). If it exceeds, it means that the optimization algorithm has been completed and the current minimum value of the objective function is output.

[0134] According to the optimization solution, the optimal core backbone network is constructed.

[0135] Implementing the embodiments of the present application has the following beneficial effects:

[0136] The embodiment of the present application first constructs a power directed graph that can clearly describe the operation status between nodes and lines in the power system based on the topological structure of the power system. Then, through the nodes and lines in the power directed graph, the historical flow data of the power system is statistically analyzed, and the flow balance of the nodes and lines is evaluated to obtain the anti-destruction index that can be used to evaluate the core backbone grid in extreme scenarios. On the basis of satisfying the anti-destruction index as much as possible, the corresponding objective function is constructed with the comprehensive optimization of the anti-destruction index, the total line length and connectivity of the core backbone grid as the goal. Because the shorter core backbone grid is less likely to be affected by extreme events, it is best to construct a core backbone grid with a shorter line length while ensuring that the grid has high connectivity and can withstand extreme events. Finally, the particle swarm optimization algorithm is used to optimize the objective function to obtain an accurate optimal core backbone grid of the power system that can ensure stable operation in extreme scenarios, ensure power supply to important users in various scenarios, and improve power quality.

[0137] Second embodiment

[0138] Further, in order to execute the core backbone grid construction system based on the power system invulnerability corresponding to the above method embodiment to achieve corresponding functions and technical effects, Figure 2 A structural diagram of a core backbone grid construction system based on power system invulnerability is provided. For ease of explanation, only the parts related to this embodiment are shown. The core backbone grid construction system based on power system invulnerability provided by the embodiment of the present application includes:

[0139] The directed graph construction module 201 is used to construct a corresponding power directed graph according to the topological structure of the power system.

[0140] In an embodiment of the present application, data is collected from each node of the power system to obtain historical power flow data of the power system; the power directed graph is constructed based on the historical power flow data of the power system and the topological structure; a node adjacency matrix of the power directed graph is constructed based on the adjacency relationship between each node in the power directed graph; based on the node adjacency matrix, the connectivity of the paths between each node in the power directed graph is evaluated to obtain the natural connectivity of each node in the power directed graph.

[0141] The indestructibility index building module 202 is used to collect statistics on the historical power flow data of the power system based on the power directed graph to build the indestructibility index of the core backbone grid.

[0142] In the embodiment of the present application, for the resistance, connectivity, safety and recovery of the power system in extreme scenarios, the historical power flow data of the power system is statistically analyzed based on the power directed graph to construct resistance index, connectivity index, safety index and recovery index. The resistance index, connectivity index, safety index and recovery index are normalized respectively to obtain the invulnerability index.

[0143] Among them, resistance indicators include line preservation rate, power preservation rate and load preservation rate; connectivity indicators include grid relative density, grid relative cohesion, average power transmission distance and average power transmission margin; safety indicators include line stability margin index, node voltage margin index and power supply power margin index; recovery indicators include generator standby index, load recovery index and number of interconnection lines index.

[0144] The objective function construction module 203 is used to construct the objective function of the core backbone network frame according to the invulnerability index and with the goal of minimizing the total length of the lines of the core backbone network frame.

[0145] In an embodiment of the present application, the objective function is constructed based on the indestructibility index, the total length of the lines of the power system and the switching status of the lines, with the goal of minimizing the total length of the lines of the core backbone grid; the constraints of the core backbone grid are constructed based on the power system flow constraints and the power system line constraints.

[0146] The optimal core backbone grid construction module 204 is used to optimize the objective function by using a particle swarm optimization algorithm to obtain an optimal core backbone grid of the power system.

[0147] In an embodiment of the present application, the nodes and edges in the power directed graph are used as particle swarm variables, and the particle swarm variables are updated at a preset update speed; based on the constraints of the core backbone network, the current value of the objective function is obtained through the updated particle swarm variables; when the updated particle swarm variables meet the preset convergence conditions, the current value is used as the optimal solution; according to the optimal solution, the optimal core backbone network is constructed.

[0148] In some embodiments, the directed graph construction module 201 further includes:

[0149] In the embodiment of the present application, data is collected from each node and line of the power system to obtain historical power flow data of the power system and draw the topological structure of the power system. Then, based on the topological structure, a power directed graph that can reflect the topological and power flow characteristics of the power system is constructed.

[0150] Exemplarily, the power directed graph is defined as G = (V, E), where G represents a set of nodes V and lines E, and satisfies the node υ i ∈V, line e i =(υ i , j )∈E, line e i The direction is from node v i To node v j , the total number of nodes is N B =|B|, the total number of lines is N L =|E|.

[0151] After defining the power directed graph, a node adjacency matrix of the power directed graph is constructed to reflect the adjacency relationship between nodes. The specific expression is:

[0152]

[0153] Among them, the characteristic root of the node adjacency matrix A is λ i , i=1,2,...,N.

[0154] Based on the power directed graph, it can be seen that the more different paths that remain connected between any two nodes in the graph, the greater the probability that the two nodes can still remain connected through another alternative path when some of the paths fail. Correspondingly, it can be approximately considered that the grid of the entire power system has better invulnerability. Therefore, natural connectivity is defined as an indicator for quantitatively evaluating the redundancy of alternative paths between all nodes in the network structure. According to the characteristic root of the node adjacency matrix A, the natural connectivity of each node can be obtained, and the specific expression is:

[0155]

[0156] In the formula, s i is the natural connectivity of the ith node, N is the total number of nodes, λ i is the characteristic root of the i-th node in the node adjacency matrix.

[0157] Because the above-mentioned node adjacency matrix and natural connectivity between nodes are common to the topological structures of most power systems, these evaluation indicators have good versatility and can be applied to most power grids.

[0158] Optionally, when drawing a directed electric power graph, the embodiment of the present application only considers the transmission network and directly connected nodes above the 35kV voltage level, does not consider the distribution network and related nodes below the 35kV voltage level, and also ignores the ground branches of the power grid.

[0159] In some embodiments, the invulnerability index building module 202 further includes:

[0160] In the embodiment of the present application, the evaluation of the invulnerability of the power system is quantified from four aspects, namely: resistance, connectivity, safety and recovery. Through these four aspects, four different indicators are constructed for the core backbone grid, namely resistance index, connectivity index, safety index and recovery index, which are used to evaluate the constructed core backbone grid to intuitively show the advantages and disadvantages of different grids.

[0161] In view of the resistance, connectivity, safety and resilience of the power system in extreme scenarios, the historical power flow data of the power system is statistically analyzed based on the power directed graph to construct resistance index, connectivity index, safety index and resilience index.

[0162] Among them, resistance indicators include line preservation rate, power preservation rate and load preservation rate; connectivity indicators include grid relative density, grid relative cohesion, average power transmission distance and average power transmission margin; safety indicators include line stability margin index, node voltage margin index and power supply power margin index; recovery indicators include generator standby index, load recovery index and number of interconnection lines index.

[0163] Specifically, the line preservation rate, the relative density of the grid, the relative cohesion of the grid, the average power transmission distance and the average power transmission margin are obtained based on the flow data statistics of the nodes and lines in the power directed graph.

[0164] The line preservation rate D i (1), the specific expression is:

[0165]

[0166] Among them, N LF is the number of failed lines in the power system after the extreme event, N L is the total number of lines in the power system.

[0167] The power conservation rate D i (2), the specific expression is:

[0168]

[0169] Where W BFis the amount of power loss in the power system after the impact of an extreme event, W B is the total number of power sources in the power system.

[0170] The load conservation rate D i (3), the specific expression is:

[0171]

[0172] Among them, LO BF is the load loss amount of the power system after the extreme event, LO B is the total number of loads in the power system.

[0173] The relative tightness K of the grid i (1), the specific expression is:

[0174]

[0175] In the formula, K i Indicates that there are K nodes around node i i neighboring nodes, and there are t i lines, C0 is the grid density of the power system, N B is the total number of nodes, N BF is the total number of nodes affected by the extreme event.

[0176] The relative cohesion degree K of the grid i (2), the specific expression is:

[0177]

[0178] Where K0 is the grid cohesion of the power system, It is the number of weighted edges when the equivalent impedance of the power line is the smallest.

[0179] The average transmission distance of electric energy K i (3), the specific expression is:

[0180] The average transmission distance of electric energy K i (3), the specific expression is:

[0181]

[0182] Where D path (i) is the electrical distance of the i-th power flow transmission path, which is the sum of the reactance values ​​of all branches on the path.

[0183] The average power transmission margin K i (4), the specific expression is:

[0184]

[0185] In the formula, ΔP path (i) is the active power margin of the i-th power transmission path, P max (i), P path (i) are the active power over-limit value and real-time value of the i-th power flow transmission path respectively.

[0186] The generator standby index H i (1), the specific expression is:

[0187]

[0188] In the formula, G max (i), G(i) is the maximum installed capacity and actual output of the i-th generator, N G is the number of generators in the power system.

[0189] The load recovery index H i (2), the specific expression is:

[0190]

[0191] Where P m is the maximum active power of the current core backbone network, and P is the actual active power of the current core backbone network.

[0192] The contact line number index H i (3), the specific expression is:

[0193]

[0194] Where N LL is the number of interconnection lines in the current core backbone grid, L(i) is the total length of the ith interconnection line, and L0 is the total length of the power system lines.

[0195] Then, the resistance index D i , connectivity index K i , Safety index U i and the recovery index H i Normalize to form a new normalized index Among them, i ∈[0,1],i=1,2,...,N B .

[0196] According to the normalized index, the anti-destruction index of the power system for the core backbone grid is constructed, and the specific formula is:

[0197]

[0198] In the formula, S urv is the invulnerability index, ω1, ω2, ω3 are weight coefficients, η is the number of indicators, ψ i is the combination of resistance index, connectivity index, security index and recovery index, s i is the natural connectivity of the ith node, and s0 is the connectivity of the initial grid. Among them, the weight coefficient needs to satisfy

[0199] In the embodiment of the present application, η is taken as 10, ||Ψ i || ∞ =max|Ψ i |.

[0200] In some embodiments, the objective function construction module 203 further includes:

[0201] In the embodiment of the present application, the designed core backbone grid not only needs to meet the anti-destruction index, but also needs to consider the total length of the lines in the grid. Generally speaking, a shorter core backbone grid is less likely to be affected by extreme events, so a core backbone grid with a shorter line length is constructed as much as possible.

[0202] According to the invulnerability index, the total length of the lines of the power system and the switching state of the lines, the invulnerability index, the total length of the lines of the core backbone grid and the comprehensive optimality of the connectivity are taken as the goal to construct the objective function, and the specific expression is:

[0203]

[0204] Where F is the objective function, L1 is the total length of the core backbone grid, L0 is the total length of the power system, and N L is the total number of lines, x i is the switching state of line i, B(i) is the impedance of line i, j is the branch endpoint number of the core backbone network, Q is the branch endpoint set of the core backbone network, Ψ(j) is the combination of resistance index, connectivity index, safety index and recovery index, S urv is the invulnerability index.

[0205] When constructing the optimal core backbone network through the objective function, the following constraints need to be met:

[0206]

[0207] In the formula, l i is the length of line i, N LFis the number of failed lines in the power system after the impact of extreme events, H(x,y)≤θ is the power flow inequality constraint of the power system, G(x,y)=0 is the power flow equality constraint of the power system, and Φ(Q) is the connectivity requirement of the core backbone grid.

[0208] Among them, the constraints of the core backbone grid are constructed based on the power system's flow constraints and power system's line constraints.

[0209] In some embodiments, the optimal core backbone network construction module 204 further includes:

[0210] In an embodiment of the present application, the nodes and edges in the power directed graph are used as particle swarm variables, and the particle swarm variables are updated at a preset update speed.

[0211] For example, based on the power directed graph G = (V, E), using (V i , E i ) as the particle swarm variable,

[0212] Initialize the particle swarm to (V0, E0), and initialize the current minimum value of the objective function to:

[0213]

[0214] The particle swarm variables are updated at the preset update speeds Δv and Δe, that is, the update value of the particle swarm variables is set to (V i +Δυ,E i +Δe), where (Δυ, Δe) represent the speed values ​​of the set of nodes V and lines E respectively.

[0215] Then, based on the constraints of the core backbone network, the current value of the objective function is obtained through the updated particle swarm variables. Then, it is determined whether the current value is less than the minimum value of the objective function, and if it is less than the minimum value, the minimum value of the objective function is updated.

[0216] Specifically, the current value of the objective function is taken as the second result; the first result of the objective function is calculated using the updated particle swarm variable; if the first result is less than the second result, the first result is taken as the current value of the objective function.

[0217] Finally, when the updated particle swarm variable meets the preset convergence condition, the current value is used as the optimal solution;

[0218] Specifically, the convergence condition may be to determine whether the current particle swarm variable exceeds the maximum grid of the power system, that is, the power directed graph G=(V, E). If it exceeds, it means that the optimization algorithm has been completed and the current minimum value of the objective function is output.

[0219] According to the optimization solution, the optimal core backbone network is constructed.

[0220] Implementing the embodiments of the present application has the following beneficial effects:

[0221] The embodiment of the present application first constructs a power directed graph that can clearly describe the operation status between nodes and lines in the power system based on the topological structure of the power system. Then, through the nodes and lines in the power directed graph, the historical flow data of the power system is statistically analyzed, and the flow balance of the nodes and lines is evaluated to obtain the anti-destruction index that can be used to evaluate the core backbone grid in extreme scenarios. On the basis of satisfying the anti-destruction index as much as possible, the corresponding objective function is constructed with the comprehensive optimization of the anti-destruction index, the total line length and connectivity of the core backbone grid as the goal. Because the shorter core backbone grid is less likely to be affected by extreme events, it is best to ensure that the grid has high connectivity and can withstand extreme events while constructing a core backbone grid with shorter line length. Finally, the particle swarm optimization algorithm is used to optimize the objective function to obtain an accurate optimal core backbone grid of the power system that can ensure stable operation in extreme scenarios, ensure power supply to important users in various scenarios, and improve power quality.

[0222] The specific embodiments described above further describe the purpose, technical solutions and beneficial effects of the present application in detail. It should be understood that the above description is only a specific embodiment of the present application and is not intended to limit the scope of protection of the present application. It is particularly pointed out that for those skilled in the art, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of protection of the present application.

Claims

1. A method for constructing a core backbone grid based on the invulnerability of a power system, characterized in that: include: According to the topological structure of the power system, the corresponding power directed graph is constructed; Based on the power directed graph, the historical power flow data of the power system is counted to construct the invulnerability index of the core backbone grid; By considering the invulnerability index, the total line length and connectivity of the core backbone network, an objective function of the core backbone network is constructed; The objective function is optimized by a particle swarm optimization algorithm to obtain the optimal core backbone grid of the power system.

2. The method for constructing a core backbone grid based on power system invulnerability according to claim 1, characterized in that: According to the topological structure of the power system, a corresponding power directed graph is constructed, specifically: Collect data from each node of the power system to obtain historical power flow data of the power system; Constructing the power directed graph according to the historical power flow data of the power system and the topological structure; Constructing a node adjacency matrix of the power directed graph according to the adjacency relationship between the nodes in the power directed graph; Based on the node adjacency matrix, the connectivity of the paths between the nodes in the power directed graph is evaluated to obtain the natural connectivity of the nodes in the power directed graph.

3. The method for constructing a core backbone grid based on power system invulnerability according to claim 2, characterized in that: The natural connectivity is specifically: Among them, the natural connectivity of the node is specifically expressed as: In the formula, s i is the natural connectivity of the ith node, N is the total number of nodes, λ i is the characteristic root of the i-th node in the node adjacency matrix.

4. The method for constructing a core backbone grid based on power system invulnerability according to claim 1, characterized in that: The statistical analysis of the historical power flow data of the power system based on the power directed graph to construct the invulnerability index of the core backbone grid is specifically as follows: In view of the resistance, connectivity, safety and recovery of the power system in extreme scenarios, the historical power flow data of the power system is statistically analyzed based on the power directed graph to construct resistance index, connectivity index, safety index and recovery index; Among them, resistance indicators include line preservation rate, power preservation rate and load preservation rate; connectivity indicators include grid relative compactness, grid relative cohesion, average power transmission distance and average power transmission margin; safety indicators include line stability margin index, node voltage margin index and power margin index; recovery indicators include generator standby index, load recovery index and number of tie lines index; The resistance index, connectivity index, safety index and recovery index are normalized respectively to obtain the indestructibility index.

5. The method for constructing a core backbone grid based on power system invulnerability according to claim 4, characterized in that: The invulnerability index is specifically: The specific formula of the invulnerability index is: In the formula, S urv is the invulnerability index, ω1, ω2, ω3 are weight coefficients, η is the number of indicators, ψ i is the combination of resistance index, connectivity index, security index and recovery index, s i is the natural connectivity of the ith node, and s0 is the connectivity of the initial grid.

6. The method for constructing a core backbone grid based on power system invulnerability according to claim 1, characterized in that: The objective function of the core backbone network is constructed by considering the invulnerability index, the total line length and connectivity of the core backbone network, which is specifically: According to the invulnerability index, the total length of the lines of the power system and the switching state of the lines, the objective function is constructed with the comprehensive optimization of the invulnerability index, the total length of the lines of the core backbone grid and the connectivity as the goal; According to the power system flow constraints and power system line constraints, the constraints of the core backbone grid are constructed.

7. The method for constructing a core backbone grid based on power system invulnerability according to claim 6, characterized in that: The objective function and constraints are specifically: Among them, the objective function is specifically expressed as: Where F is the objective function, L1 is the total length of the core backbone grid, L0 is the total length of the power system, and N L is the total number of lines, x i is the switching state of line i, B(i) is the impedance of line i, j is the branch endpoint number of the core backbone network, Q is the branch endpoint set of the core backbone network, Ψ(j) is the set of resistance index, connectivity index, safety index and recovery index, S urv is the indestructibility index; The constraint condition is specifically expressed as follows: In the formula, l i is the length of line i, N LF is the number of failed lines in the power system after an extreme event in an extreme scenario, H(x,y)≤θ is the power flow inequality constraint of the power system, G(x,y)=0 is the power flow equality constraint of the power system, and Φ(Q) is the connectivity requirement of the core backbone grid.

8. The method for constructing a core backbone grid based on power system invulnerability according to claim 1, characterized in that: The objective function is optimized by the particle swarm optimization algorithm to obtain the optimal core backbone grid of the power system, specifically: Using nodes and edges in the power directed graph as particle swarm variables, and updating the particle swarm variables at a preset update speed; Based on the constraints of the core backbone network, the current value of the objective function is obtained through the updated particle swarm variables; When the updated particle swarm variable meets the preset convergence condition, the current value is used as the optimal solution; According to the optimization solution, the optimal core backbone network is constructed.

9. The method for constructing a core backbone grid based on power system invulnerability according to claim 8, characterized in that: The current value of the objective function is obtained by updating the particle swarm variable, specifically: taking the current value of the objective function as a second result; Using the updated particle swarm variable to calculate and obtain a first result of the objective function; If the first result is less than the second result, the first result is used as the current value of the objective function.

10. A core backbone grid construction system based on power system invulnerability, characterized in that: include: Directed graph building module, invulnerability index building module, objective function building module and optimal core backbone network building module; The directed graph construction module is used to construct a corresponding power directed graph according to the topological structure of the power system; The invulnerability index building module is used to collect statistics on the historical power flow data of the power system based on the power directed graph to build the invulnerability index of the core backbone grid; The objective function construction module is used to construct the objective function of the core backbone network by considering the invulnerability index, the total line length and connectivity of the core backbone network; The optimal core backbone grid construction module is used to optimize the objective function through a particle swarm optimization algorithm to obtain the optimal core backbone grid of the power system.

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