Active power distribution network fault reconstruction method and device based on crossover algorithm

Abstract

A kind of active distribution network fault reconstruction method and device based on crossover algorithm, method includes: according to the original data and fault information of obtained distribution network, determine the line to be cut off, disconnect all the tie switches of distribution network, determine the topology of distribution network, generate the adjacency matrix of distribution network, the connectivity of topological graph is judged, determine the connected sub-block of each tie switch connection;Determine the tie switch combination of open-loop connectivity of connected sub-block using the preset power threshold, determine the connected graph corresponding to each tie switch combination, according to the connection relationship between connected graph and the grid connection point of distribution network, determine the connected graph belonging to island in connected graph;According to the objective function and constraint condition in distribution network reconstruction optimization model, iterative optimization is carried out using minimum spanning tree algorithm and hybrid algorithm, to determine the island boundary and outage node, obtain distribution network reconstruction result.The present application reduces the outage load and outage range, and reduces the network loss as far as possible, optimizes distribution network reconstruction.

Description

Technical Field

[0001] This invention relates to the field of distribution network reconfiguration technology, and more particularly to an active distribution network fault reconfiguration method and apparatus based on a cross-connection algorithm. Background Technology

[0002] In recent years, environmentally friendly technologies such as renewable energy power generation and electric vehicles have been vigorously developed and promoted. As a crucial component of the power system, the distribution network acts as a bridge between the main grid and loads. The large-scale integration of distributed generation and electric vehicle charging stations will have a significant impact on the planning and operation of the distribution network.

[0003] Against this backdrop, the operation mode of distribution networks is gradually shifting from the traditional passive mode to an active mode. The C6.11 project group of the Distribution and Distributed Generation Committee of the International Conference on Large Electric Systems (CIGRE) proposed the concepts of active distribution network (ADN) and distributed energy resources (DER). An active distribution network refers to a distribution system that can effectively manage power flow using flexible network technologies to actively control and manage distributed energy resources connected to the distribution network. Distributed energy resources mainly include distributed generation (DG), electrical energy storage (EES), and controllable load (CL). As a relatively new concept, active distribution networks are currently in their early stages of development, and many related issues require further research. Summary of the Invention

[0004] To address the problems existing in the prior art, the main objective of this invention is to provide an active distribution network fault reconfiguration method and apparatus based on a cross-connection algorithm, thereby reducing outage loads and outage ranges and accurately reconfiguring the active distribution network.

[0005] To achieve the above objectives, embodiments of the present invention provide an active distribution network fault reconfiguration method based on a crossover algorithm, the method comprising:

[0006] Based on the acquired raw data and fault information of the distribution network, the lines to be disconnected are determined, and all tie switches of the distribution network are disconnected using the lines to be disconnected to determine the topology of the distribution network.

[0007] The adjacency matrix of the distribution network is generated using the topology graph, and the connectivity of the topology graph is determined using the adjacency matrix of the distribution network to identify the connected sub-blocks connected by each tie switch.

[0008] The connection switch combination of open-loop connection of connected sub-block is determined by using a preset power threshold. The connection switch combination is traversed to determine the connection graph corresponding to each connection switch combination. Based on the connection graph and the connection point of the distribution network, the connection graph belonging to the island is determined in the connection graph.

[0009] Based on the connected graph belonging to the islands and the objective function and constraints in the preset distribution network reconfiguration optimization model, the minimum spanning tree algorithm and hybrid algorithm are used for iterative optimization to determine the island boundaries and outage nodes. Based on the island boundaries and outage nodes, the distribution network reconfiguration results are obtained.

[0010] Optionally, in one embodiment of the present invention, the raw data includes the original network structure, node load, branch impedance, and distributed power supply parameters.

[0011] Optionally, in one embodiment of the present invention, determining which connected graphs belong to islands in the connected graph based on the connection relationship between the connected graph and the grid connection point of the distribution network includes:

[0012] If the connectivity graph is not connected to the grid connection point of the distribution network, then the corresponding connectivity graph is determined to be a connectivity graph belonging to an island.

[0013] If the connectivity graph is connected to the grid connection point of the distribution network, then the constraints in the distribution network reconfiguration optimization model are used to determine the uncontrollable load outage of the tie switch combination with the minimum outage power, and based on the outage determination result, the connectivity graph belonging to the island is determined in the connectivity graph.

[0014] Optionally, in one embodiment of the present invention, determining which connected graphs belong to islands based on the power outage determination result includes:

[0015] If the power outage assessment result indicates that there is an uncontrollable load power outage, then determine the scope of the uncontrollable load power outage, and use the scope of the uncontrollable load power outage to determine its connection branch with the distribution network connection point;

[0016] By using connecting branches, we can identify the connected graphs that belong to isolated islands.

[0017] This invention also provides an active distribution network fault reconfiguration device based on a crossover algorithm, the device comprising:

[0018] The topology module is used to determine the lines to be disconnected based on the acquired raw data and fault information of the distribution network, and to disconnect all tie switches of the distribution network using the lines to be disconnected to determine the topology of the distribution network.

[0019] The connected sub-block module is used to generate the adjacency matrix of the distribution network using the topology graph, and to use the adjacency matrix of the distribution network to determine the connectivity of the topology graph and identify the connected sub-blocks connected to each tie switch.

[0020] The connectivity graph module is used to determine the connection switch combinations of open-loop connectivity of the connected sub-blocks using a preset power threshold, traverse the connection switch combinations, determine the connectivity graph corresponding to each connection switch combination, and determine the connectivity graph belonging to the island in the connectivity graph based on the connection relationship between the connectivity graph and the grid connection point of the distribution network.

[0021] The reconfiguration result module is used to perform iterative optimization using the minimum spanning tree algorithm and a hybrid algorithm based on the connected graph belonging to the island and the objective function and constraints in the preset distribution network reconfiguration optimization model, to determine the island boundaries and outage nodes, and to obtain the distribution network reconfiguration result based on the island boundaries and outage nodes.

[0022] Optionally, in one embodiment of the present invention, the raw data includes the original network structure, node load, branch impedance, and distributed power supply parameters.

[0023] Optionally, in one embodiment of the present invention, the connected graph module includes:

[0024] The unconnected unit is used to determine that if the connected graph is not connected to the grid connection point of the distribution network, the corresponding connected graph is a connected graph belonging to an island.

[0025] The power outage judgment unit is used to determine the uncontrollable load power outage of the tie switch combination with the smallest power outage power if the connectivity graph is connected to the grid connection point of the distribution network, by using the constraints in the distribution network reconfiguration optimization model, and to determine the connectivity graph belonging to the island based on the power outage judgment result.

[0026] Optionally, in one embodiment of the present invention, the power outage determination unit includes:

[0027] The connecting branch subunit is used to determine the uncontrollable load power outage range if the power outage judgment result is that there is an uncontrollable load power outage, and to determine the connecting branch of the uncontrollable load power outage range to the grid connection point of the distribution network.

[0028] Connectivity graph sub-units are used to identify islands within a connected graph by utilizing connecting branches.

[0029] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the above-described method.

[0030] The present invention also provides a computer-readable storage medium storing a computer program that performs the above-described methods by a computer.

[0031] The present invention also provides a computer program product, including a computer program / instructions, which, when executed by a processor, implement the steps of the above-described method.

[0032] This invention obtains a topology graph from the original data and fault information of the distribution network, and determines the connected graph belonging to islands by combining the adjacency matrix and connectivity judgment. Using a preset distribution network reconfiguration optimization model, the distribution network reconfiguration result is obtained. Thus, while reducing the power outage load and the power outage range, the network loss is minimized as much as possible, and the distribution network reconfiguration is optimized. Attached Figure Description

[0033] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0034] Figure 1 This is a flowchart of an active distribution network fault reconfiguration method based on a cross-connection algorithm, according to an embodiment of the present invention.

[0035] Figure 2 This is a flowchart illustrating the process of determining a connected graph belonging to an island in an embodiment of the present invention;

[0036] Figure 3 This is a flowchart for determining the connected graph belonging to an island in another embodiment of the present invention;

[0037] Figure 4 This is a schematic diagram of a five-node distribution network model in an embodiment of the present invention;

[0038] Figure 5 This is a flowchart of the power distribution network reconfiguration process in an embodiment of the present invention;

[0039] Figure 6 This is a flowchart of the hybrid algorithm in an embodiment of the present invention;

[0040] Figure 7 This is a schematic diagram of an active distribution network fault reconfiguration device based on a cross-connection algorithm according to an embodiment of the present invention;

[0041] Figure 8 This is a schematic diagram of the connected graph module in an embodiment of the present invention;

[0042] Figure 9 This is a schematic diagram of the power outage detection unit in an embodiment of the present invention;

[0043] Figure 10 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0044] This invention provides an active distribution network fault reconfiguration method and apparatus based on a cross-connection algorithm.

[0045] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0046] Distribution networks are typically designed as closed-loop systems operating in an open-loop configuration, containing numerous sectionalizing switches (normally closed) and a small number of tie switches (normally open). Distribution network reconfiguration refers to minimizing power outages by controlling sectionalizing and tie switches when the distribution network topology changes due to faults or maintenance, while maintaining the radial structure of the distribution network. When the distribution network contains distributed generation (DG), the possibility of islanding must also be considered. Due to the presence of distributed generation, active distribution networks need to consider the randomness of renewable energy generation output, the output of energy storage devices, and the impact of controllable load power adjustments during reconfiguration. When the distribution network includes electric vehicle charging stations, the role of vehicle-to-grid (V2G) during reconfiguration must also be considered.

[0047] like Figure 1 The diagram shows a flowchart of an active distribution network fault reconfiguration method based on a cross-connection algorithm according to an embodiment of the present invention. The execution entity of the active distribution network fault reconfiguration method based on the cross-connection algorithm provided in this embodiment includes, but is not limited to, a computer. This invention obtains a topology graph from the original data and fault information of the distribution network, determines the connected graph belonging to islands by combining the adjacency matrix and connectivity judgment, and obtains the distribution network reconfiguration result using a preset distribution network reconfiguration optimization model. This reduces the outage load and outage range while minimizing network losses and optimizing the distribution network reconfiguration. The method shown in the diagram includes:

[0048] Step S1: Based on the acquired raw data and fault information of the distribution network, determine the lines to be disconnected, and use the lines to be disconnected to disconnect all the tie switches of the distribution network to determine the topology of the distribution network.

[0049] Step S2: Use the topology graph to generate the adjacency matrix of the distribution network, and use the adjacency matrix of the distribution network to determine the connectivity of the topology graph and identify the connected sub-blocks connected by each tie switch.

[0050] Step S3: Use the preset power threshold to determine the connection switch combination of the open-loop connection of the connected sub-block, traverse the connection switch combination, determine the connection graph corresponding to each connection switch combination, and determine the connection graph belonging to the island in the connection graph according to the connection relationship between the connection graph and the grid connection point of the distribution network.

[0051] Step S4: Based on the connected graph belonging to the island and the objective function and constraints in the preset distribution network reconfiguration optimization model, iterative optimization is performed using the minimum spanning tree algorithm and hybrid algorithm to determine the island boundary and power outage nodes, and the distribution network reconfiguration result is obtained based on the island boundary and power outage nodes.

[0052] As an embodiment of the present invention, the raw data includes the original network structure, node load, branch impedance, and distributed power supply parameters.

[0053] Specifically, raw data and fault information of the distribution network can be obtained through manual input or by retrieving data from a database. This includes the original network structure, node loads, branch impedances, specific parameters of distributed power sources, and the predicted output of renewable energy generators. Based on the fault information, the lines that need to be disconnected, i.e., the lines to be disconnected, are the lines supplying power to the location of the fault. After disconnecting the lines to be disconnected, all tie switches in the distribution network are then turned off to obtain the distribution network topology.

[0054] Furthermore, the preset power thresholds include the minimum allowable power of the controllable load and the maximum allowable power of the energy storage device. By setting the controllable load power to the minimum allowable value and the energy storage device output power to the maximum allowable value, all combinations of interconnecting switches that open-loop connect the connected sub-blocks are generated, and a corresponding connectivity graph is generated for each combination. Specifically, by traversing all combinations of interconnecting switches that open-loop connect the connected sub-blocks, a connectivity graph corresponding to each combination can be obtained.

[0055] As an embodiment of the present invention, such as Figure 2 As shown, based on the connection relationship between the connectivity graph and the grid connection point of the distribution network, the connectivity graphs that belong to islands are identified as follows:

[0056] Step S31: If the connectivity graph is not connected to the grid connection point of the distribution network, then the corresponding connectivity graph is determined to be a connectivity graph belonging to an island.

[0057] Step S32: If the connectivity graph is connected to the grid connection point of the distribution network, then the constraints in the distribution network reconfiguration optimization model are used to determine the uncontrollable load power outage of the tie switch combination with the smallest power outage power, and based on the power outage determination result, the connectivity graph belonging to the island is determined in the connectivity graph.

[0058] In this embodiment, as Figure 3 As shown, based on the power outage determination results, the connected graphs identified as belonging to isolated islands include:

[0059] Step S321: If the power outage judgment result is that there is an uncontrollable load power outage, then determine the uncontrollable load power outage range, and use the uncontrollable load power outage range to determine its connection branch with the distribution network connection point;

[0060] Step S322: Using connecting branches, determine the connected graph that belongs to the islands in the connected graph.

[0061] The process involves determining whether the generated connectivity graph is connected to the main grid, i.e., the connection relationship between the connectivity graph and the grid connection point of the distribution network. If not connected, the connectivity graph is considered an island, the tie switch remains closed, and islanding optimization is then performed. Specifically, the method for determining whether the generated connectivity graph is connected to the main grid is as follows: Randomly select a point in the connectivity graph and determine whether it is connected to the grid connection point.

[0062] Furthermore, the pre-defined distribution network reconfiguration optimization model includes constraints and objective functions, specifically: topology constraints, distributed generation output constraints, controllable load adjustment constraints, energy storage device output constraints, power flow constraints, and voltage constraints. Among these, the power flow constraints and voltage constraints in the distribution network reconfiguration optimization model are used to calculate the switch combination corresponding to the minimum outage power. Specifically, based on the power flow constraints and voltage constraints, it is determined whether there are uncontrollable load outages under the extreme settings of renewable energy sources; that is, the power flow calculation results are used to determine whether there is a reduction in uncontrollable load power.

[0063] Furthermore, if a controllable load power decreases, the outage area and its connecting branch to the main grid are determined, the branch is disconnected, the power grid is split, and the area where the outage occurs is designated as an island. The topology map is then regenerated in step S1, followed by subsequent steps S2. Additionally, the remaining portion is directly used as the backbone network for optimization calculations.

[0064] Furthermore, in the above steps, for cases where there is no controllable load power reduction and the remaining part of the obtained backbone network is used as input, the input distribution network diagram is treated as an island. Considering all objective functions and constraints in the model, a hybrid algorithm based on Prim's spanning tree algorithm and chaotic particle swarm optimization is used to iteratively optimize the controllable load and energy storage device settings, and determine the island boundaries and uncontrollable load nodes that experience power outages, i.e., the island boundaries and power outage nodes. This yields the distribution network reconfiguration results. Specifically, the distribution network reconfiguration results include reconfiguration schemes for handling faults, including switch opening and closing status, island division, energy storage output, load power outages, etc.

[0065] In a specific embodiment of the present invention, considering the stochastic nature of renewable energy power generation, a multi-objective optimization model is established, using controllable load power and energy storage device power as controllable variables, while also taking into account the impact of electric vehicle charging and discharging. A reconfiguration strategy incorporating island partitioning is proposed, and the optimization model is iteratively solved using the Prim algorithm and a chaotic particle swarm optimization algorithm to optimize the reconfiguration scheme.

[0066] In this embodiment, the most important objective of distribution network reconfiguration is to reduce the outage load and the outage area, while minimizing network losses as much as possible. On the other hand, due to the limited energy storage capacity in the system, the output of energy storage devices should also be minimized while meeting requirements. Since reactive power in the distribution network is mainly compensated centrally on the load side, active power is the primary consideration here. Active distribution network reconfiguration includes three optimization objectives:

[0067] 1) Power outage capacity f1 considering the importance of the load:

[0068]

[0069] In the formula: CL (controllable load) is the set of controllable loads, P i0 For the original power of the controllable load, P i P represents the adjusted power of controllable loads during the reconfiguration process; CUT represents the set of uncontrollable loads that have experienced power outages. j0 For uncontrollable load power; λ i , λ j This represents the load importance level coefficient.

[0070] 2) Network loss f2: Power loss of the entire network lines after reconstruction.

[0071] 3) Energy storage equipment output f3:

[0072]

[0073] In the formula: EES (electrical energy storage) is the collection of energy storage devices in the distribution network, P m This refers to the output power of the energy storage device.

[0074] Active distribution networks contain a large number of distributed generation sources, therefore, in addition to traditional distribution network reconfiguration constraints, the constraints brought by distributed generation sources must also be considered. Since renewable energy generation output is stochastic, controllable load power and energy storage device output are treated as controllable variables, while distributed generation output is considered as an uncontrollable variable. The following steps are used to establish a distribution network reconfiguration optimization model:

[0075] 1) Topological constraints:

[0076] g∈G(3)

[0077] In the formula: g represents the topology of the restructured distribution network, and G represents the radial network topology. After restructurement, the distribution network must maintain open-loop operation to avoid the formation of loop networks.

[0078] 2) Distributed generation output constraints:

[0079] P n =μn P n0 ,n∈DG (4)

[0080] In the formula: DG (distributed generation) is a collection of distributed generation equipment, which are all assumed to be renewable energy generation equipment. P n For the actual output of distributed generation, P n0 To predict the output, μ n is the confidence coefficient.

[0081] 3) Controllable load constraint adjustment constraint:

[0082] P i =P i0 (1-ρ)+ρ(1-η)P i0

[0083] i∈CL,η∈[0,1] (5)

[0084] In the formula: ρ is the load controllability coefficient, and η is the controllable load adjustment (reduction) coefficient. Generally, ρ∈[0,1].

[0085] Specifically, when the controllable load of a node is an electric vehicle charging station, the impact of the V2G discharge mode needs to be considered.

[0086] ρ=1+γ,γ∈[0,1] (6)

[0087] In the formula, γ represents the proportion of electric vehicles that can participate in V2G within the charging station during reconfiguration.

[0088] 4) Output constraints of energy storage devices:

[0089] 0≤P k ≤P kmax ,k∈EES (7)

[0090] Where: EES is a collection of energy storage devices, P k P is the output power of the energy storage battery. kmax This represents the maximum output power of the energy storage device.

[0091] 5) Trend constraints:

[0092] |S|≤S max (8)

[0093] In the formula: S represents the power flow of each line, S max This represents the maximum allowable power flow for each line.

[0094] 6) Voltage constraint:

[0095] U min ≤U≤U max (9)

[0096] In the formula: U, U min U max This represents the voltage at each node and its corresponding upper and lower limits.

[0097] Specifically, the active distribution network reconfiguration optimization model for the aforementioned distributed power sources combines distribution network reconfiguration with islanding, performing iterative reconfiguration and gradually decomposing the distribution network in each iteration. First, preliminary reconfiguration and islanding are performed to minimize uncontrollable load outages; then, adjustments are made to distributed energy sources to minimize controllable load power loss and energy storage device output power.

[0098] The entire reconstruction and optimization process involves some concepts and algorithms from graph theory. Based on the known distribution network node and line data, the following two matrices need to be generated according to the distribution network topology during the reconstruction process:

[0099] 1) Adjacency matrix

[0100] The topology of the power distribution network is abstracted as an undirected topological graph G = (V, E), where the vertex set V = {v1, v2, v3, ..., v...} n} represents each node in the distribution network, and the edge set E = {e1, e2, e3, ..., e n} represents the various lines and switches in the power distribution network, represented by 'a'. ij Represents vertex v i With v j The connection state between them can take the value 0 or 1, where 0 represents disconnection and 1 represents connection. Then matrix A = A(G) = (a ij ) n×n This is called the adjacency matrix of graph G.

[0101] like Figure 4 As shown, node 1 is connected to the main network, S is the tie switch (open), and DG is the distributed generation. The line between nodes 3 and 4 is disconnected due to a fault. The adjacency matrix of this distribution network is as follows:

[0102]

[0103] 2) Connected sub-blocks

[0104] The connectivity of the topological graph can be determined based on the adjacency matrix, and the connected sub-blocks of the topological graph can be obtained. Figure 4 The topology of the distribution network in the diagram is not connected under fault conditions and can be divided into two connected sub-blocks, containing nodes 1, 2, and 3 and nodes 4, 5, and 6 respectively. The corresponding adjacency matrices are as follows:

[0105]

[0106] It should be noted that although A1 and A2 have the same mathematical expression, their rows and columns correspond to vertices in different connected sub-blocks.

[0107] After obtaining the connected sub-blocks, the connected sub-blocks connected by the corresponding edges in the topology graph can be determined based on the nodes at both ends of the tie switch in the distribution network. Figure 4 In the power distribution network, nodes 2 and 4 at both ends of the tie switch S are located in different connected sub-blocks. Therefore, closing the tie switch S can connect only the two connected sub-blocks contained in the topology diagram.

[0108] like Figure 5 As shown, the power distribution network reconfiguration process is as follows:

[0109] 1) Input the original data and fault information of the distribution network, including the original network structure, node load, branch impedance, and specific parameters of distributed power sources and the predicted output of renewable energy generators. Then, based on the fault information, determine the lines that need to be disconnected, that is, disconnect the lines that supply power to the location of the fault.

[0110] 2) Disconnect all tie switches and generate a topology diagram.

[0111] 3) Generate the adjacency matrix of the topology graph, determine its connectivity, divide it into connected sub-blocks, and determine the connected sub-blocks connected by each tie switch.

[0112] 4) Set the controllable load power to the minimum allowable value and the energy storage device output power to the maximum allowable value. Generate all interconnecting switch combinations that open-loop connect the connected sub-blocks, and generate a corresponding connectivity diagram for each interconnecting switch combination;

[0113] This involves traversing all the connection switch combinations that open-loop connect connected sub-blocks, with each combination corresponding to a connected graph.

[0114] 5) Determine whether the generated connected graph is connected to the main network. If yes, continue to step 6); if no, the connected graph is an island, keep the connection switch closed, and jump to step 8) to directly perform island partitioning optimization.

[0115] Among them, determining whether the generated connected graph is connected to the main network: take any point in the connected graph and determine whether it is connected to the grid connection point.

[0116] 6) Power flow calculation: Select the switch combination that produces the minimum power outage when closed. Based on power flow constraints and voltage constraints, determine whether there is an uncontrollable load power outage under the limit setting of renewable power sources. Specifically, use the power flow calculation results to determine whether there is a reduction in uncontrollable load power. If not, input the graph into step 8) for optimization calculation; if so, determine the uncontrollable load power outage range, that is, determine the power loss of uncontrollable loads in the power flow calculation results, and proceed to step 7).

[0117] Among them, the switch combination with the minimum power outage power is the switch combination with the minimum power outage power in the power flow calculation results.

[0118] 7) Determine the outage area and its connection to the main grid, disconnect the connection, and split the power grid. Classify the outage area as an isolated region and input it into step 2) for iterative reconstruction; the remaining portion is directly input into step 8) for optimization calculations as part of the main grid.

[0119] 8) Treat the input partial distribution network diagram as an island, consider all objective functions and constraints in the model, and use a hybrid algorithm based on Prim's spanning tree algorithm and chaotic particle swarm optimization to iteratively optimize the controllable load and energy storage device settings, determine the island boundary and the uncontrollable load nodes that are out of power, and obtain the distribution network reconfiguration results.

[0120] The reconfiguration result is the reconfiguration plan to deal with the fault, including switch opening and closing status, islanding, energy storage output, load power outage, etc.

[0121] 9) Summarize the reconfiguration optimization results of each part of the power grid to obtain the optimal reconfiguration scheme.

[0122] It should be noted that if multiple uncontrollable power outage ranges are found in step 5), the original map needs to be split into several parts, and each part not connected to the main network should be regarded as an island existence range and entered into step 2) in order to consider the possibility of island combination reconstruction.

[0123] In this embodiment, as Figure 6 As shown, after the initial regional division of the distribution network, the remaining task is to determine the specific boundaries of each region (i.e., the uncontrollable load nodes that will experience power outages) and the setting of renewable power sources. Treating the regional division problem as an island partitioning problem, and referring to existing research on island partitioning, a hybrid algorithm combining the Prim spanning tree algorithm and the chaotic particle swarm optimization algorithm is adopted to solve the distribution network reconfiguration scheme.

[0124] First, Prim's algorithm is used to transform the boundary partitioning problem of distribution network islands into a problem of finding possible spanning trees of a connected graph, thus traversing all possible island partitioning scenarios. The specific algorithm modifications are mainly as follows: 1) For the portion of the distribution network connected to the main grid, it is considered an island containing a sufficiently large distributed generation (DG), and power balance constraints are not considered. 2) During island partitioning, the DG output is set to the predicted value; the energy storage output is set to the maximum and is also considered DG; all controllable loads are set to the minimum; for controllable loads with zero power, the two ends of the line are merged into one line; electric vehicle charging stations are considered DG based on V2G power.

[0125] As the reconstruction optimization model shows, optimizing the setting of renewable energy is a multi-dimensional and multi-constraint problem. Therefore, traditional intelligent algorithms are prone to premature convergence and getting trapped in local optima. By introducing chaotic search, the global optimization capability of the particle swarm optimization algorithm can be improved. Therefore, after determining all possible reconstruction scenarios, a chaotic particle swarm optimization algorithm is used to optimize the setting of renewable energy and determine the optimal reconstruction scheme.

[0126] The primary task of the distribution network is to supply power. Power outages affect the reliability of the distribution network, so target f1 should be prioritized during optimization. Although network loss f2 causes power loss, it does not affect normal power supply, so its importance is secondary. The output of energy storage batteries f3 can be controlled by setting a power limit, and excessively reducing the output will waste energy storage capacity. Therefore, the importance of the three optimization targets decreases sequentially. A tolerant fully hierarchical method is used to solve the three optimization targets sequentially. After each layer of optimization is completed, a certain tolerance margin is given to the controllable load and the output of energy storage devices before proceeding to the next layer of optimization.

[0127] This invention obtains a topology graph from the original data and fault information of the distribution network, and determines the connected graph belonging to islands by combining the adjacency matrix and connectivity judgment. Using a preset distribution network reconfiguration optimization model, the distribution network reconfiguration result is obtained. Thus, while reducing the power outage load and the power outage range, the network loss is minimized as much as possible, and the distribution network reconfiguration is optimized.

[0128] like Figure 7 The figure shows a schematic diagram of an active distribution network fault reconfiguration device based on a crossover algorithm according to an embodiment of the present invention. The device shown in the figure includes:

[0129] The topology module 10 is used to determine the lines to be disconnected based on the acquired raw data and fault information of the distribution network, and to disconnect all the tie switches of the distribution network using the lines to be disconnected, thereby determining the topology of the distribution network.

[0130] The connected sub-block module 20 is used to generate the adjacency matrix of the distribution network using the topology graph, and to use the adjacency matrix of the distribution network to determine the connectivity of the topology graph and identify the connected sub-blocks connected by each tie switch.

[0131] The connectivity graph module 30 is used to determine the open-loop connected connection switch combination of the connected sub-block using a preset power threshold, traverse the connection switch combination, determine the connectivity graph corresponding to each connection switch combination, and determine the connectivity graph belonging to the island in the connectivity graph according to the connection relationship between the connectivity graph and the grid connection point of the distribution network.

[0132] The reconstruction result module 40 is used to perform iterative optimization using the minimum spanning tree algorithm and a hybrid algorithm based on the connected graph belonging to the island and the objective function and constraints in the preset distribution network reconstruction optimization model, to determine the island boundary and power outage node, and to obtain the distribution network reconstruction result based on the island boundary and power outage node.

[0133] As an embodiment of the present invention, the raw data includes the original network structure, node load, branch impedance, and distributed power supply parameters.

[0134] As an embodiment of the present invention, such as Figure 8 As shown, the connected graph module 30 includes:

[0135] The non-connected unit 31 is used to determine that if the connected graph is not connected to the grid connection point of the distribution network, the corresponding connected graph is a connected graph belonging to an island.

[0136] The power outage judgment unit 32 is used to determine the uncontrollable load power outage of the tie switch combination with the smallest power outage power by using the constraints in the power distribution network reconfiguration optimization model if the connected graph is connected to the grid connection point of the distribution network, and to determine the connected graph belonging to the island in the connected graph based on the power outage judgment result.

[0137] In this embodiment, as Figure 9 As shown, the power outage detection unit 32 includes:

[0138] The connecting branch subunit 321 is used to determine the uncontrollable load power outage range if the power outage judgment result is that there is an uncontrollable load power outage, and to determine the connecting branch of the uncontrollable load power outage range to the grid connection point of the distribution network.

[0139] Connectivity subunit 322 is used to determine the connectivity of islands in the connectivity graph by using connecting branches.

[0140] Based on the same concept as the aforementioned active distribution network fault reconfiguration method based on a cross-algorithm, this invention also provides an active distribution network fault reconfiguration device based on a cross-algorithm. Since the principle of this active distribution network fault reconfiguration device based on a cross-algorithm is similar to that of the active distribution network fault reconfiguration method based on a cross-algorithm, the implementation of this active distribution network fault reconfiguration device based on a cross-algorithm can be found in the implementation of the active distribution network fault reconfiguration method based on a cross-algorithm, and the repetitions will not be repeated.

[0141] This invention obtains a topology graph from the original data and fault information of the distribution network, and determines the connected graph belonging to islands by combining the adjacency matrix and connectivity judgment. Using a preset distribution network reconfiguration optimization model, the distribution network reconfiguration result is obtained. Thus, while reducing the power outage load and the power outage range, the network loss is minimized as much as possible, and the distribution network reconfiguration is optimized.

[0142] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the above-described method.

[0143] The present invention also provides a computer program product, including a computer program / instructions, which, when executed by a processor, implement the steps of the above-described method.

[0144] The present invention also provides a computer-readable storage medium storing a computer program that performs the above-described methods by a computer.

[0145] like Figure 10 As shown, the electronic device 600 may also include: a communication module 110, an input unit 120, an audio processor 130, a display 160, and a power supply 170. It is worth noting that the electronic device 600 does not necessarily need to include these components. Figure 10 All components shown; in addition, the electronic device 600 may also include Figure 10 For components not shown, please refer to existing technologies.

[0146] like Figure 10 As shown, the central processing unit 100, sometimes also referred to as a controller or operating control, may include a microprocessor or other processor device and / or logic device. The central processing unit 100 receives inputs and controls the operation of various components of the electronic device 600.

[0147] The memory 140 may be, for example, one or more of a cache, flash memory, hard drive, removable media, volatile memory, non-volatile memory, or other suitable devices. It may store the aforementioned failure-related information, and also store a program for executing that information. The central processing unit 100 may execute the program stored in the memory 140 to perform information storage or processing, etc.

[0148] Input unit 120 provides input to central processing unit 100. Input unit 120 may be, for example, a keypad or touch input device. Power supply 170 provides power to electronic device 600. Display 160 displays images and text. Display may be, for example, an LCD display, but is not limited thereto.

[0149] The memory 140 can be a solid-state memory, such as a read-only memory (ROM), random access memory (RAM), a SIM card, etc. It can also be a memory that retains information even when power is off, can be selectively erased, and contains more data; examples of this type of memory are sometimes referred to as EPROMs. The memory 140 can also be some other type of device. The memory 140 includes a buffer memory 141 (sometimes referred to as a buffer). The memory 140 may include an application / function storage unit 142 for storing application programs and function programs or processes for executing the operation of the electronic device 600 via the central processing unit 100.

[0150] The memory 140 may also include a data storage unit 143 for storing data, such as contacts, digital data, pictures, sounds, and / or any other data used by the electronic device. The driver storage unit 144 of the memory 140 may include various drivers for the electronic device's communication functions and / or for performing other functions of the electronic device (such as messaging applications, address book applications, etc.).

[0151] The communication module 110 is a transmitter / receiver 110 that transmits and receives signals via antenna 111. The communication module (transmitter / receiver) 110 is coupled to the central processing unit 100 to provide input signals and receive output signals, which can be the same as in a conventional mobile communication terminal.

[0152] Based on different communication technologies, multiple communication modules 110 can be configured in the same electronic device, such as cellular network modules, Bluetooth modules, and / or wireless LAN modules. The communication module (transmitter / receiver) 110 is also coupled to a speaker 131 and a microphone 132 via an audio processor 130 to provide audio output via the speaker 131 and receive audio input from the microphone 132, thereby enabling typical telecommunications functions. The audio processor 130 may include any suitable buffer, decoder, amplifier, etc. Additionally, the audio processor 130 is coupled to a central processing unit 100, enabling on-device recording via the microphone 132 and on-device playback of stored audio via the speaker 131.

[0153] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0154] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0155] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0156] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0157] Specific embodiments have been used to illustrate the principles and implementation methods of this invention. The descriptions of the embodiments above are only for the purpose of helping to understand the method and core ideas of this invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this invention. Therefore, the content of this specification should not be construed as a limitation of this invention.

Claims

1. A method for active distribution network fault reconfiguration based on a crossover algorithm, characterized in that, The method includes: Based on the acquired raw data and fault information of the distribution network, the lines to be disconnected are determined, and all tie switches of the distribution network are disconnected using the lines to be disconnected to determine the topology of the distribution network. The adjacency matrix of the distribution network is generated using the topology graph, and the connectivity of the topology graph is determined using the adjacency matrix of the distribution network to identify the connected sub-blocks connected by each tie switch. Using a preset power threshold, determine the connection switch combination of the open-loop connection of the connected sub-block, traverse the connection switch combination, determine the connection graph corresponding to each connection switch combination, and determine the connection graph belonging to the island in the connection graph according to the connection relationship between the connection graph and the grid connection point of the distribution network. Based on the connected graph belonging to the island and the objective function and constraints in the preset distribution network reconfiguration optimization model, the minimum spanning tree algorithm and the hybrid algorithm are used for iterative optimization to determine the island boundary and the power outage node, and the distribution network reconfiguration result is obtained based on the island boundary and the power outage node.

2. The method according to claim 1, characterized in that, The raw data includes the original network structure, node loads, branch impedances, and distributed power source parameters.

3. The method according to claim 1, characterized in that, Based on the connection relationship between the connectivity graph and the grid connection point of the distribution network, the connectivity graphs that belong to islands are identified in the connectivity graph as follows: If the connectivity graph is not connected to the grid connection point of the distribution network, then the corresponding connectivity graph is determined to be a connectivity graph belonging to an island. If the connectivity graph is connected to the grid connection point of the distribution network, then the constraints in the distribution network reconfiguration optimization model are used to determine the uncontrollable load outage of the tie switch combination with the minimum outage power, and based on the outage determination result, the connectivity graph belonging to the island is determined in the connectivity graph.

4. The method according to claim 3, characterized in that, Based on the power outage assessment results, the connected graphs identified as belonging to isolated islands include: If the power outage judgment result is that there is an uncontrollable load power outage, then the uncontrollable load power outage range is determined, and the connection branch between the uncontrollable load power outage range and the distribution network connection point is determined using the uncontrollable load power outage range; Using the connecting branches, a connected graph belonging to an island is determined in the connected graph.

5. An active distribution network fault reconfiguration device based on a crossover algorithm, characterized in that, The device includes: The topology module is used to determine the lines to be disconnected based on the acquired raw data and fault information of the distribution network, and to disconnect all the tie switches of the distribution network using the lines to be disconnected, thereby determining the topology of the distribution network. The connected sub-block module is used to generate the adjacency matrix of the distribution network using the topology graph, and to use the adjacency matrix of the distribution network to determine the connectivity of the topology graph and identify the connected sub-blocks connected by each tie switch. The connectivity graph module is used to determine the open-loop connected tie switch combinations of the connected sub-blocks using a preset power threshold, traverse the tie switch combinations, determine the connectivity graph corresponding to each tie switch combination, and determine the connectivity graph belonging to the island in the connectivity graph based on the connection relationship between the connectivity graph and the grid connection point of the distribution network. The reconfiguration result module is used to perform iterative optimization using the minimum spanning tree algorithm and a hybrid algorithm based on the connected graph belonging to the island and the objective function and constraints in the preset distribution network reconfiguration optimization model, to determine the island boundaries and outage nodes, and to obtain the distribution network reconfiguration result based on the island boundaries and outage nodes.

6. The apparatus according to claim 5, characterized in that, The raw data includes the original network structure, node loads, branch impedances, and distributed power source parameters.

7. The apparatus according to claim 5, characterized in that, The connected graph module includes: The unconnected unit is used to determine that if the connected graph is not connected to the grid connection point of the distribution network, the corresponding connected graph is a connected graph belonging to an island. The power outage judgment unit is used to determine the uncontrollable load power outage of the tie switch combination with the smallest power outage power by using the constraints in the power distribution network reconfiguration optimization model if the connectivity graph is connected to the grid connection point of the distribution network, and to determine the connectivity graph belonging to the island based on the power outage judgment result.

8. The apparatus according to claim 7, characterized in that, The power outage detection unit includes: The connecting branch subunit is used to determine the uncontrollable load power outage range if the power outage judgment result is that there is an uncontrollable load power outage, and to determine the connecting branch of the uncontrollable load power outage range to the grid connection point of the distribution network. A connected graph subunit is used to determine, using the connecting branches, a connected graph that belongs to an island.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method according to any one of claims 1 to 4.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that enables a computer to execute the method according to any one of claims 1 to 4.

11. A computer program product, comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method according to any one of claims 1 to 4.

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