Power grid black-start method based on new energy automobile battery swap station

Abstract

The invention discloses a power grid black-start method based on a new energy automobile battery swap station, and the method comprises the steps: constructing a weighted undirected power grid structure diagram based on the connection relation between the battery swap station and a power transmission line; performing power grid static characteristic analysis on the weighted undirected power grid structure chart to obtain a power grid layout; based on the power grid layout, performing charging optimization on the target grid frame by adopting a starting power supply and sub-grid parallel starting mode to obtain an optimized charging scheme; simulating a power grid black-start process based on the optimized charging scheme, and capturing the influence of a power grid topological structure on the power grid charging process; optimizing the black start process of the power grid by adopting community division and the modularity value to obtain an optimized black start model of the power grid; according to the method, the static and dynamic characteristics of the complex network of the power grid are analyzed, the potential of the battery swap station in the aspect of optimizing the starting power supply layout is researched, and the recovery efficiency and reliability of the power grid after a large-scale power failure accident are improved.

Description

Technical Field

[0001] The present application relates to the field of power grid black start, and in particular to a power grid black start method based on a new energy vehicle battery swap station. Background Art

[0002] After a large-scale power outage, rapid restoration of grid functions is critical to mitigate its far-reaching impact on the economy and society. The efficiency of grid restoration is often limited by the lack of starting power points and the limitations of their layout. Coupled with multiple factors such as equipment aging, inadequate maintenance, and natural disasters, the uncertainty of the grid restoration process has increased significantly, and it has posed a severe challenge to the stability and reliability of the system. These compound factors have seriously hindered the process of restoring the grid to normal power supply. At the same time, with the acceleration of urbanization and the widespread adoption of electric vehicles, the construction of electric vehicle swap stations has shown a rapid growth trend, providing an innovative solution for the black start of the grid. These swap stations have opened up new possibilities for the rapid restoration of the grid with their wide geographical distribution and energy storage systems that can quickly respond to grid failures. Restoration of the grid after a large power outage is an urgent and complex task, and its core goal is to quickly restore power supply to mitigate its far-reaching impact on the economy and society. In the process of grid restoration, the number and geographical distribution of starting power sources are key factors that determine the speed and effectiveness of restoration. If the number of starting power sources is insufficient, key areas may not be fully covered, resulting in the inability to synchronize grid restoration work. Especially when starting a subnet at a long distance, it may cause a large-scale flow of power flow, increase the risk of grid structure vulnerability, overvoltage and system oscillation. In addition, if the starting power distribution is unreasonable, it may cause the line charging distance to be too long, too many operating devices, and make the communication and coordination links complicated, thereby increasing the operation risk and reducing the success rate of the operation. These problems may lead to slow progress or inefficiency in grid restoration work.

[0003] In recent years, with the rapid development of the new energy vehicle industry, the global sales of electric vehicles have continued to grow. This trend has also significantly promoted the construction of electric vehicle battery swap stations, and the future development prospects are broad. Taking China as an example, according to statistics in August 2024, China has built a total of 3,817 battery swap stations, with nearly 1,000 new stations added in the year from August 2023 to August 2024 alone. CATL plans to build 10,000 battery swap stations. The geographical distribution of electric vehicle battery swap stations is becoming more and more extensive, adding potential starting power sources to the power grid and expanding its potential. As an emerging auxiliary facility of the power grid, the battery swap station can work with a variety of power sources including new energy power stations and thermal power plants to provide auxiliary power to nearby substations. This significantly enhances the configuration flexibility and emergency response capabilities of the starting power supply when a large-scale power outage occurs in the power grid. In terms of technical feasibility, the energy storage system equipped with the battery swap station can quickly respond to power grid failures and provide immediate power support, thereby accelerating the power grid recovery process. In terms of technical compatibility, the equipment of the battery swap station can be seamlessly connected with the control and protection system of the power grid to ensure coordinated operation during the recovery period. The flexibility and adaptability of battery swap stations enable them to adjust their configuration according to different power demands and operate stably under various environmental conditions, which further enhances the reliability of grid restoration. From an economic benefit perspective, battery swap stations reduce economic losses caused by power outages, reduce dependence on traditional power sources, and effectively reduce operating costs. At the same time, the active support of existing policies for renewable energy and smart grid technologies provides additional economic incentives for the black start application of battery swap stations. These characteristics enable electric vehicle battery swap stations to largely break through the restrictions on the number and geographical location of starting power sources, providing a broader space for optimizing the layout of starting power sources. Summary of the invention

[0004] In view of the above-mentioned deficiencies in the prior art, the present invention provides a grid black start method based on a new energy vehicle battery swap station, which solves the problems of unreasonable distribution of starting power supply, long line charging distance, and too many operating devices in traditional grid black start, which makes communication and coordination links complicated.

[0005] In order to achieve the above-mentioned invention object, the technical solution adopted by the present invention is: a grid black start method based on a new energy vehicle battery swap station, comprising:

[0006] S1. Based on the connection relationship between the power swap stations and the transmission lines, a right-free undirected power grid structure diagram is constructed;

[0007] S2, analyzing the static characteristics of the power grid on the authorized undirected power grid structure diagram to obtain the power grid layout;

[0008] S3, based on the grid layout, the charging of the target grid is optimized by starting the power supply and the subnet in parallel, and the optimized charging scheme is obtained;

[0009] S4, simulating the black start process of the power grid based on the optimized charging scheme to capture the impact of the power grid topology on the power grid charging process;

[0010] S5, optimizing the black start process of the power grid by using community division and modularity value, and obtaining an optimized black start model of the power grid;

[0011] S6. Use the optimized power grid black start model to perform a black start on the target grid after the power outage.

[0012] Further: In S1, the weighted undirected power grid structure diagram S is described by the power exchange station V and the transmission line E;

[0013] Among them, the battery swap station V = {v1,v2,...,v O}, transmission line E={e1,e2,...,e P}, O represents the number of power swap stations, P represents the number of transmission lines, and any two-tuple corresponding to a node on a transmission line is represented by e x = {v i ,v j}.

[0014] Further: S2 includes:

[0015] S21. The power grid is visualized through the Fruchtenbaum-Reingold layout algorithm. The physical distance between nodes is matched with the connection density by iteratively calculating the force on each node to obtain the distribution of the power exchange stations in the power grid.

[0016] S22, visualize the power grid through the Circular layout algorithm, and identify the connection strength and direction between the nodes in the power grid based on the connection density of the nodes in the network;

[0017] S23. The distribution of battery swap stations in the power grid, and the connection strength and direction between the power grid nodes are taken together as the power grid layout.

[0018] Further: The optimized charging scheme in S3 includes:

[0019] S31. Based on the grid layout, the grid is divided into I subnets according to the optimal community method, and a starting power supply is set for each subnet;

[0020] The setting standard of the starting power supply is: within each subnet, the sum of the distances to each battery swap station is the shortest;

[0021] S32, charging the target grid by starting the power supply and the subnet in parallel.

[0022] Further: In S4, the FEF model is used to capture the impact of the grid topology on the grid charging process. The FEF model is expressed as:

[0023]

[0024] F(t)+E(t)=N

[0025]

[0026] Among them, τ represents the charging rate, γ represents the power-off rate, both τ and γ are positively correlated with F(t) and E(t), N is the number of sites in the target grid, E(t) and F(t) represent the number of energized sites and power-off sites at time t, respectively.

[0027] Further: S5 includes:

[0028] S51, dividing the nodes into different communities according to the degree of connection between the nodes in the power grid;

[0029] S52. The geometric center of each community is used as a potential starting power source point to obtain an optimized power grid black start model.

[0030] Further: In S51, the most closely connected node mode in the power grid is selected for community division, and the modularity value Q is used to quantify the quality of community division. The expression of the modularity value Q is:

[0031]

[0032] Among them, A ij is an element in the adjacency matrix, used to indicate whether there is an edge connection between node i and node j, k i and k j denote the degrees of node i and node j respectively, δ(c i ,c j ) is a function for determining whether nodes i and j belong to the same community.

[0033] The beneficial effects of the present invention are:

[0034] 1. This application explores the path optimization of new energy vehicle battery swap stations for black start recovery of the power grid, opening up new possibilities for the rapid recovery of the power grid;

[0035] 2. The charging of the target grid is optimized by starting the power supply and subnet in parallel, shortening the distance of power transmission and reducing the shortest path length between nodes, thereby accelerating the transmission rate of information and power, which not only reduces time delay and energy loss, but also improves network efficiency; at the same time, the optimized power point distribution helps to effectively control the transfer of power flow, reduce the risk of overvoltage and system oscillation, and thus enhance the stability and synchronization of the power grid during the recovery process;

[0036] 3. By using the CNM community partitioning algorithm to reveal the inherent hierarchical structure and modular characteristics of the power grid topology, we can iteratively seek the optimal community aggregation solution. This optimal power grid subnet partitioning strategy helps to improve the speed and efficiency of the parallel restoration process of multiple subnets;

[0037] 4. In the optimized subnet (i.e. community), finding the geometric center as the starting power point can ensure that the average distance of energy and information flow from the starting power point to other nodes in the subnet is the shortest, thereby maximizing efficiency. By reducing the interdependence between subnets, the stability and reliability risks caused by large-scale transfer of power flows and faults between subnets can be reduced, thereby reducing the risk of a complete collapse of the entire power grid due to local faults. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 The flowchart of the black start method of the power grid based on the new energy vehicle battery swap station.

[0039] Figure 2 A visualization of a power grid using the Fruchtenbaum-Reingold layout algorithm.

[0040] Figure 3 A visualization of a power grid using the Circular layout algorithm.

[0041] Figure 4 : is a distribution histogram of the shortest path length in the network in the embodiment.

[0042] Figure 5 Schematic diagram of the shortest distance from each node to the startup power supply in the embodiment.

[0043] Figure 6 Graph showing the shortest distance distribution from a node to a startup power source in an embodiment.

[0044] Figure 7 Schematic diagram of the state transformation of the FEF model system.

[0045] Figure 8 It is a dynamic process diagram of node charging during the power grid recovery process in the embodiment.

[0046] Fig. 9It is a dynamic process diagram of charging of the starting power supply after optimization in the embodiment. DETAILED DESCRIPTION

[0047] The specific implementation modes of the present invention are described below so that those skilled in the art can understand the present invention. However, it should be clear that the present invention is not limited to the scope of the specific implementation modes. For those of ordinary skill in the art, as long as various changes are within the spirit and scope of the present invention as defined and determined by the attached claims, these changes are obvious, and all inventions and creations utilizing the concept of the present invention are protected.

[0048] like Figure 1 As shown, in one embodiment of the present invention, a black start method of a power grid based on a new energy vehicle battery swap station is provided, comprising:

[0049] S1. Based on the connection relationship between the power swap stations and the transmission lines, a right-free undirected power grid structure diagram is constructed;

[0050] S2, analyzing the static characteristics of the power grid on the authorized undirected power grid structure diagram to obtain the power grid layout;

[0051] S3, based on the grid layout, the charging of the target grid is optimized by starting the power supply and the subnet in parallel, and the optimized charging scheme is obtained;

[0052] S4, simulating the black start process of the power grid based on the optimized charging scheme to capture the impact of the power grid topology on the power grid charging process;

[0053] S5, optimizing the black start process of the power grid by using community division and modularity value, and obtaining an optimized black start model of the power grid;

[0054] S6. Use the optimized power grid black start model to perform a black start on the target grid after the power outage.

[0055] The grid topology is the basis for exploring the network characteristics of the grid recovery process. In this embodiment S1, the undirected grid structure diagram S is described by the power exchange station V and the transmission line E;

[0056] Among them, the battery swap station V = {v1,v2,...,v O}, transmission line E={e1,e2,...,e P}, O represents the number of power swap stations, P represents the number of transmission lines, and any two-tuple corresponding to a node on a transmission line is represented by e x = {v i ,v j}, the adjacency matrix of the power grid is G, and the element g on the i-th row and j-th column of G is ij , used to reflect the electrical connection strength between nodes, g ijPositively correlated with voltage and capacity.

[0057] Using different complex network node layout algorithms can make the network topology characteristics more intuitive. S2 includes:

[0058] S21. The power grid is visualized through the Fruchtenbaum-Reingold layout algorithm. The physical distance between nodes is matched with the connection density by iteratively calculating the force on each node to obtain the distribution of the power exchange stations in the power grid.

[0059] S22, visualize the power grid through the Circular layout algorithm, and identify the connection strength and direction between the nodes in the power grid based on the connection density of the nodes in the network;

[0060] S23. The distribution of battery swap stations in the power grid, and the connection strength and direction between the power grid nodes are taken together as the power grid layout.

[0061] A visualization of a power grid using the Fruchtenbaum-Reingold layout algorithm, such as Figure 2 As shown in the figure, the algorithm simulates the gravitational and repulsive forces acting on objects in the physical world. It evenly distributes the power grid by iteratively calculating the force on each node, so that the physical distance between nodes matches the connection density, thereby intuitively demonstrating the synchronization characteristics of the power grid.

[0062] A visualization of a power grid using the Circular layout algorithm, such as Figure 3 As shown, based on the degree of connection between nodes in the network, the algorithm arranges the nodes at different positions on the circumference, which can quickly identify the connection pattern between nodes and display the connection strength and direction of the power grid, helping to identify synchronous propagation paths and potential bottlenecks.

[0063] In one example of the present invention, the method of step S2 is used to visualize a certain power grid, the network diameter of the power grid is 22, the average shortest path length is 8.2, and the network shortest path length distribution histogram is shown in FIG. Figure 4 More than half of the shortest paths in the power grid are longer than 8, which reflects that the power grid is widely distributed and the connections between nodes are relatively scattered, resulting in more intermediate nodes for power transmission. This situation is particularly unfavorable during the black start process, because long paths mean that power restoration takes longer, while increasing uncertainty and risk during the restoration process. In addition, because the restoration of multiple areas needs to be considered at the same time, the widely distributed power grid areas also increase the demand for startup power resources during the startup process.

[0064] The grid recovery process is closely related to the number and distribution of starting power sources. The optimized charging scheme in S3 includes:

[0065] S31. Based on the grid layout, the grid is divided into I subnets according to the optimal community method, and a starting power supply is set for each subnet;

[0066] The setting standard of the starting power supply is: within each subnet, the sum of the distances to each battery swap station is the shortest;

[0067] S32, charging the target grid by starting the power supply and the subnet in parallel.

[0068] In an example of the present invention, the actual power grid uses a method of multiple startup power sources and multiple subnets to start in parallel to charge the target grid, which significantly shortens the charging distance between the node and the power source. The longest charging distance is reduced to 8, and the average shortest path length is reduced to 3.6. The shortest distance from each node to the above startup power source group is shown in Figure 5 , distribution diagram see Figure 6 At the same time, it can be seen that in the target grid, the node-to-startup power supply has a large distribution of distances, and there are many nodes with long distances. In fact, the insufficient number and location of the starting power supply affects the efficiency and stability of the grid startup. For example, during the grid restoration process, a weakly connected AC large ring network or electromagnetic ring network is formed, which leads to a large-scale transfer of power flow, triggering system oscillation and local overvoltage, and some equipment and lines tripping. In addition, the protection devices of some nodes are accidentally activated, causing some live equipment to trip and lose power again, which increases the difficulty of the grid connection and ring closing operation.

[0069] Optimizing the distribution and number of power supply points can shorten the distance of power transmission and reduce the shortest path length between nodes, thereby speeding up the transmission rate of information and power. This not only reduces time delays and energy losses, but also improves network efficiency. At the same time, optimized power supply point distribution helps to effectively control the transfer of power flow, reduce the risk of overvoltage and system oscillation, and thus enhance the stability and synchronization of the power grid during the recovery process.

[0070] In some embodiments of the present invention, a mathematical model for describing and analyzing the black start process of a power grid is proposed, namely, a FEF model. The schematic diagram of the FEL model is shown in FIG. Figure 7 shown.

[0071] In the FEL model, the sites of the target grid are divided into two main categories: one is the energized site in the energized state (Energized, referred to as E), which means that the site is charged through the transmission line; the other is the power-off site in the power-off state (Failure, referred to as F), including the black start initial state and the accidental power-off state after charging.

[0072] The FEF model is based on the following assumptions:

[0073] Charging rate τ: It is reasonable to assume that the charging of the adjacent powered nodes to the current node is a Poisson process, and the corresponding time is exponentially distributed. This parameter setting mainly considers the risk of failure in the process of charging the nodes through the transmission line by the powered power source and substation during the actual power grid recovery process, such as equipment failure, communication control system failure, etc. This parameter is positively correlated with the uncharged site variable F(t) and the charging site variable E(t).

[0074] Power failure rate γ: It is reasonable to assume that the accidental power failure of the powered node is a Poisson process, and the corresponding time is exponentially distributed. This parameter setting mainly considers the risk of power failure of the powered node again during the actual power grid recovery process, such as accidental tripping caused by system oscillation and overvoltage. This parameter is positively correlated with the charging station variable E(t).

[0075] The charging dynamics of the power grid are characterized by the probability equation that describes the rate of change of the node's probability of being charged. Starting from the state probability of a single node, a set of individual-based ordinary differential equations are established to describe the change of variables over time, which can be specifically expressed as:

[0076]

[0077]

[0078] F(t)+E(t)=N

[0079]

[0080] Where N is the number of sites in the target grid.

[0081] For the above example, the FEF model is used for simulation. Based on the actual starting power supply, the charging rate is set to 0.9 and the power failure rate is set to 0.1. The dynamic process of node charging during the grid recovery process is shown in Figure 8 , the time for 70.7% of the nodes in the whole network to be charged is 3.9 unit time. The simulation results show that with the increase of the probability of successful node charging, the charging process of the power grid is smoother and faster.

[0082] Specifically, S5 includes:

[0083] S51, using the CNM community partitioning algorithm, through a continuous node merging and iterative process, the target grid network is partitioned into communities;

[0084] In S51, the most closely connected nodes in the power grid are selected for community division, and the modularity value Q is used to quantify the quality of community division. The expression of the modularity value Q is:

[0085]

[0086] Among them, A ijis an element in the adjacency matrix, used to indicate whether there is an edge connection between node i and node j, k i and k j denote the degrees of node i and node j respectively, δ(c i ,c j ) is a function for determining whether nodes i and j belong to the same community; when nodes i and j belong to the same community, the value is 1, otherwise it is 0.

[0087] S52. The geometric center of each community is used as a potential starting power source point to obtain an optimized power grid black start model.

[0088] The system simulation is performed for the optimized new startup power supply group. When other parameters are set unchanged (charging rate 0.9, power failure rate 0.1), the dynamic process of node charging during the power grid recovery process is shown in Fig. 9 The time for 70.7% of the nodes to be charged is 2.75 unit time. The simulation results show that the charging process of the optimized grid nodes is more stable and the speed is greatly improved.

[0089] The solution proposed in this application is not only feasible in theory, but also shows obvious advantages in practical applications. It helps to improve the recovery efficiency and overall reliability of the power grid when facing large-scale power outages. It explores the potential of battery swap stations as black start power sources, points out their advantages in geographical distribution, technical compatibility and economic benefits, and provides a new perspective for power grid restoration.

[0090] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A black start method for a power grid based on a new energy vehicle battery swap station, characterized in that: include: S1. Based on the connection relationship between the power swap stations and the transmission lines, a right-free undirected power grid structure diagram is constructed; S2, analyzing the static characteristics of the power grid on the authorized undirected power grid structure diagram to obtain the power grid layout; S3, based on the grid layout, the charging of the target grid is optimized by starting the power supply and the subnet in parallel, and the optimized charging scheme is obtained; S4, simulating the black start process of the power grid based on the optimized charging scheme to capture the impact of the power grid topology on the power grid charging process; S5, optimizing the black start process of the power grid by using community division and modularity value, and obtaining an optimized black start model of the power grid; S6. Use the optimized power grid black start model to perform a black start on the target grid after the power outage.

2. The black start method of the power grid based on the new energy vehicle battery swap station according to claim 1 is characterized in that: In S1, the structure diagram S of the weighted undirected power grid is described by the power exchange station V and the transmission line E; Among them, the battery swap station V = {v1,v2,...,v O }, transmission line E={e1,e2,...,e P }, O represents the number of power swap stations, P represents the number of transmission lines, and any two-tuple corresponding to a node on a transmission line is represented by e x = {v i ,v j }.

3. The black start method of the power grid based on the new energy vehicle battery swap station according to claim 1 is characterized in that S2 include: S21. The power grid is visualized through the Fruchtenbaum-Reingold layout algorithm. The physical distance between nodes is matched with the connection density by iteratively calculating the force on each node to obtain the distribution of the power exchange stations in the power grid. S22, visualize the power grid through the Circular layout algorithm, and identify the connection strength and direction between the nodes in the power grid based on the connection density of the nodes in the network; S23. The distribution of battery swap stations in the power grid, and the connection strength and direction between the power grid nodes are taken together as the power grid layout.

4. The black start method of the power grid based on the new energy vehicle battery swap station according to claim 1 is characterized in that: The optimized charging scheme in S3 includes: S31. Based on the grid layout, the grid is divided into I subnets according to the optimal community method, and a starting power supply is set for each subnet; The setting standard of the starting power supply is: within each subnet, the sum of the distances to each battery swap station is the shortest; S32, charging the target grid by starting the power supply and the subnet in parallel.

5. The black start method of the power grid based on the new energy vehicle battery swap station according to claim 1 is characterized in that: In S4, the FEF model is used to capture the impact of the grid topology on the grid charging process. The FEF model is expressed as: Among them, τ represents the charging rate, γ represents the power-off rate, both τ and γ are positively correlated with F(t) and E(t), N is the number of sites in the target grid, E(t) and F(t) represent the number of energized sites and power-off sites at time t, respectively.

6. The black start method of the power grid based on the new energy vehicle battery swap station according to claim 1, characterized in that S5 include: S51, using the CNM community partitioning algorithm, through a continuous node merging and iterative process, the target grid network is partitioned into communities; S52. The geometric center of each community is used as a potential starting power source point to obtain an optimized power grid black start model.

7. The method for black start of a power grid based on a new energy vehicle battery swap station according to claim 6, characterized in that: In S51, the most closely connected nodes in the power grid are selected for community division, and the modularity value Q is used to quantify the quality of community division. The expression of the modularity value Q is: Among them, A ij is an element in the adjacency matrix, used to indicate whether there is an edge connection between node i and node j, k i and k j denote the degrees of node i and node j respectively, δ(c i ,c j ) is a function for determining whether nodes i and j belong to the same community.

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