SOP outlet voltage control method in low-voltage distribution area flexible internet

Abstract

The invention discloses an SOP outlet voltage control method in a low-voltage distribution area flexible internet, and the method comprises the steps: taking a current SOP outlet voltage as an initial value, setting the parameters of an ant colony algorithm, including the number of ants and the number of iterations, carrying out the path search of the ant colony based on the SOP through employing a spanning tree algorithm, and generating a radial topology. And performing load flow calculation on the radial topology, and performing power balance judgment and node voltage constraint verification based on a load flow calculation result to ensure that the power is balanced to meet the node voltage constraint so as to ensure the stable operation of the power system. Searching and iteration of a topology scheme are carried out by utilizing an ant colony algorithm, through continuous iterative optimization, a radial topology which meets constraint conditions and has optimal SOP outlet voltage is found, and the radial topology is taken as a final control result. According to the invention, the control precision and the response speed of the SOP outlet voltage can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power distribution networks, and in particular to a method for controlling a SOP outlet voltage in a flexible interconnection network of a low-voltage power distribution station area. Background Art

[0002] With the rapid development of the power industry and the in-depth promotion of smart grid construction, the flexible interconnection technology of low-voltage distribution substations has been widely used and valued. The flexible interconnection technology of low-voltage distribution substations aims to achieve flexible interconnection between low-voltage distribution substations through advanced power electronics technology and communication technology, so as to improve power supply reliability, improve power quality, and optimize resource allocation. However, in practical applications, how to effectively control the SOP (Soft Open Point, i.e., smart operating point or soft switching point) outlet voltage to ensure the stable operation of the power system has become an urgent problem to be solved. Summary of the invention

[0003] The purpose of this application is to provide a method for controlling the SOP outlet voltage in a flexible interconnection network of a low-voltage distribution station area, which can improve the control accuracy and response speed of the SOP outlet voltage.

[0004] The technical solution provided by this application is:

[0005] In a first aspect, the present application provides a method for controlling the SOP outlet voltage in a low-voltage distribution station area flexible interconnection network, comprising the following steps:

[0006] Step 1: Initialization settings:

[0007] The current SOP outlet voltage in the low-voltage distribution station area flexible interconnection is used as the initial value of the SOP outlet voltage, and the parameters of the ant colony algorithm are set, including the number of ants and the number of iterations, and the initial value of the number of iterations is set to 1;

[0008] In this step, the current SOP outlet voltage is used as the initial value of the SOP outlet voltage. This initial value will serve as the basis for algorithm search and optimization.

[0009] Step 2: The ant colony uses the spanning tree algorithm based on SOP to search for paths and generate a radial topology;

[0010] Step 3: Calculate the power flow for the current radial topology;

[0011] Step 4: Determine whether the power flow calculation results meet the power balance constraints and node voltage constraints;

[0012] If the power balance constraint is not met, or the node voltage is lower than the voltage lower limit, reduce the load powered by the low-voltage distribution station area flexible interconnection network, and go to step 3 to recalculate the power flow until the power flow calculation result meets the power balance constraint and the voltage of each node meets the node voltage constraint, record the current radial topology, and go to step 5; if the node voltage is higher than the voltage upper limit, abandon the current radial topology and jump to step 5;

[0013] Step 5: Topology solution search and iteration:

[0014] Determine whether the maximum number of iterations has been reached; if not, update the pheromone and return to step 2 to continue iterating; if reached, record the SOP outlet voltage under the current radial topology as the final result.

[0015] The SOP outlet voltage under the current radial topology refers to the SOP outlet voltage obtained by performing power flow calculation on the current radial topology.

[0016] In a possible implementation, in step 4, the power balance constraint formula is:

[0017]

[0018] In the formula, and Node Flow to Node Active power and reactive power; Node The set of path head nodes for the end nodes; Node The path end node set of the head end node; For Node Voltage; For Node Flow to Node The current; and Node and The path formed resistance and reactance; and Node The sum of the active power and reactive power injected into the and Node Active power and reactive power injected by distributed generation (DG); and Inject SOP into any node in the radial topology Active power and reactive power; and Node The active power and reactive power consumed by the load.

[0019] In a possible implementation, in step 2, the ant colony uses a spanning tree algorithm to perform path search, and the transition probability formula is:

[0020]

[0021] in, Represents an ant slave node To Node The transition probability of For the node The set of adjacent nodes; express Time Path The pheromone concentration on Indicates the path The heuristic factor on Indicates the path The newly introduced target factor value is used to reflect the path performance on targets other than those considered by pheromone concentration and heuristic factors; , and They are the adjustment parameters of pheromone importance, heuristic factor importance and the newly introduced target factor importance.

[0022] In a possible implementation, the The update formula is:

[0023]

[0024] in, express Time Path pheromone concentration on; express The pheromone evaporation rate at each moment; Indicates Ants in time On the path The amount of pheromones left on the body.

[0025] In a possible implementation, the pheromone enhancement mechanism is used for important or urgent paths, and the pheromone amount calculation formula is:

[0026]

[0027] in, express Time Path The amount of pheromone enhancement on the path importance or urgency.

[0028] In a possible implementation, the The calculation formula is:

[0029]

[0030] in, Representation Node To Node Voltage drop, The table shows adjustment factors that change over time, reflecting the impact of environmental changes or historical data.

[0031] In a possible implementation, the It is calculated by weighting the quantized values ​​of other objectives.

[0032] In a second aspect, the present application provides an electronic device, including: a memory and a processor;

[0033] The memory is used to store computer programs;

[0034] The processor is used to call the computer program to execute the method as described above.

[0035] In a third aspect, the present application provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed on an electronic device, the electronic device implements the method as described above.

[0036] In a fourth aspect, the present application provides a computer program product, including a computer program, and when the computer program is executed on an electronic device, the electronic device implements the method as described above.

[0037] The specific implementation methods of the second to fourth aspects of the present application can refer to the implementation methods of the first aspect, which will not be repeated here.

[0038] Beneficial effects:

[0039] The present application provides a method for controlling the SOP outlet voltage in a flexible interconnection network of a low-voltage distribution substation, and the present application embodiment provides a method for controlling the SOP outlet voltage in a flexible interconnection network of a low-voltage distribution substation. The method utilizes the heuristic search characteristics and global optimization capabilities of the ant colony algorithm, combined with the spanning tree algorithm, to achieve intelligent control of the SOP outlet voltage under the background of flexible interconnection of low-voltage distribution substations. , improves the control accuracy and response speed of the SOP outlet voltage, and provides more reliable technical support for the stable operation of the power system. DETAILED DESCRIPTION

[0040] In order to enable those skilled in the art to better understand the present application, the technical solution of the present application will be clearly and completely described below in conjunction with the embodiments of the present application.

[0041] The embodiment of the present application provides a method for controlling the SOP outlet voltage in a flexible interconnection network of a low-voltage distribution station area. The current SOP outlet voltage is used as the initial value, and the parameters of the ant colony algorithm are set, including the number of ants and the number of iterations. The ant colony is based on SOP and uses a spanning tree algorithm to search for paths and generate a radial topology. The radial topology is subjected to flow calculation, and power balance judgment and node voltage constraint verification are performed based on the flow calculation results to ensure that the power balance satisfies and satisfies the node voltage constraints to ensure the stable operation of the power system. The ant colony algorithm is used to search and iterate the topology scheme, and through continuous iterative optimization, a radial topology that satisfies the constraints and has the optimal SOP outlet voltage is found, and it is used as the final control result.

[0042] The embodiments of the present application are further described in detail below.

[0043] The embodiment of the present application provides a method for controlling the SOP outlet voltage in a low-voltage distribution station area flexible interconnection network, comprising the following steps:

[0044] Step 1: Initialization settings:

[0045] Taking the current SOP outlet voltage in the low-voltage distribution station area flexible interconnection network as the initial value, set the parameters of the ant colony algorithm, including the number of ants and the number of iterations, and set the initial value of the number of iterations to 1;

[0046] Number of ants: Determine the number of ants to be released in the flexible interconnection network of the distribution station area. This number will affect the size of the search space and the computational complexity of the algorithm.

[0047] Iterations: Set the number of iterations the algorithm runs to ensure that the algorithm has enough time to converge to a solution while avoiding unnecessarily long calculations.

[0048] Initial value of iteration number: Initialize the iteration number to 1, indicating the first run of the algorithm.

[0049] In the initialization setting, the current SOP outlet voltage in the flexible interconnection network of the low-voltage distribution station area is used as the initial value, and the parameters of the ant colony algorithm, such as the number of ants and the number of iterations, are reasonably set. At the same time, the spanning tree algorithm is used based on SOP to iterate the ant colony to generate a radial topology, which has the following benefits:

[0050] Improve search efficiency: By setting the number of ants, the size of the search space can be controlled, thereby balancing the breadth and depth of the search. The appropriate number of ants can ensure that the search process is neither too broad and inefficient, nor too few ants that miss potential optimal solutions.

[0051] Ensure algorithm convergence: The number of iterations ensures that the algorithm has enough time to find the optimal solution. A sufficient number of iterations ensures that the algorithm fully explores the search space, thereby increasing the possibility of finding the global optimal solution.

[0052] Reduce computational cost: Although increasing the number of iterations can improve the algorithm's search performance, too many iterations will also increase the computational cost. Therefore, setting the number of iterations reasonably can reduce unnecessary computational overhead while ensuring algorithm performance.

[0053] Adapt to dynamic changes: Using the current SOP outlet voltage as the initial value can make the algorithm more adaptable to the real-time state of the distribution system. When the system state changes, the algorithm can search from the current state instead of starting from scratch, thereby speeding up the search and improving the adaptability of the solution.

[0054] Step 2: The ant colony uses the spanning tree algorithm based on SOP to search for paths and generate a radial topology;

[0055] Generate a suitable topology: The radial topology generated based on the spanning tree algorithm can ensure the stability and reliability of the distribution system. The radial topology can reduce the propagation range of faults, improve the self-healing ability of the system, and simplify the fault location and isolation process.

[0056] Step 3: Calculate the power flow for the current radial topology;

[0057] Step 4: Determine whether the power flow calculation results meet the power balance constraints and node voltage constraints;

[0058] If the power balance constraint is not met, or the node voltage is lower than the voltage lower limit, reduce the load powered by the low-voltage distribution station area flexible interconnection network, and go to step 3 to recalculate the power flow until the power flow calculation result meets the power balance constraint and the voltage of each node meets the node voltage constraint, record the current radial topology, and go to step 5; if the node voltage is higher than the voltage upper limit, abandon the current radial topology and jump to step 5;

[0059] In some embodiments, it is determined whether the power flow calculation result satisfies the following power balance constraint formula:

[0060]

[0061] In the formula, and Node Flow to Node Active power and reactive power; Node The set of path head nodes for the end nodes; Node The path end node set of the head end node; For Node Voltage; For Node Flow to Node The current; and Node and The path formed resistance and reactance; and Node The sum of the active power and reactive power injected into the and Node Active power and reactive power injected by distributed generation (DG); and Inject SOP into any node in the radial topology Active power and reactive power; and Node The active power and reactive power consumed by the load.

[0062] The above-mentioned power balance constraint formula provided in the present application takes into account the influence of resistance and reactance on active and reactive power transmission, and clearly distinguishes the power injected into the node by SOP and DG, and the power flowing from the node to other nodes; the power balance constraint formula is aimed at radial topology, adapts to the structure of radial power grid through simplified steps, and reduces the complexity of calculation.

[0063] If it is not satisfied, the load powered by the flexible interconnection network of the low-voltage distribution station area is reduced and the power flow calculation is re-performed until the power balance constraint is met and power balance is achieved.

[0064] Since the power balance constraint is not met, it indicates that the following situations may have occurred:

[0065] Voltage instability: The voltage at some nodes in the power grid may exceed the safe operating range, causing unstable operation or damage to equipment.

[0066] Overload: Some lines or transformers may be subjected to power exceeding their rated capacity, posing a risk of overload.

[0067] Power imbalance: A mismatch between power generation and load that can result in frequency deviation or voltage instability.

[0068] Reduce the load powered by the low-voltage distribution area flexible interconnection network. For example, the load originally powered by the low-voltage distribution area flexible interconnection network can be connected to other backup power supplies. Of course, in addition to this method, there are other ways to achieve load reduction:

[0069] (1) Control non-critical loads through remote control or automatic demand response (ADR) systems to reduce their power consumption.

[0070] (2) Use distributed energy (such as solar energy and wind energy) to meet part of the load and reduce dependence on the main power grid.

[0071] (3) Redistribute the load by changing the topology of the power grid, such as adding or reducing certain lines.

[0072] (4) Whenever possible, increase power generation to meet load demand.

[0073] (5) Use energy storage systems (such as batteries) to store energy during low-load periods and release energy during high-load periods to balance the grid load.

[0074] In the flexible interconnection network of low-voltage distribution substations, the radial topology is used to calculate the power flow and adjust the load to achieve power balance, which has the following technical benefits:

[0075] Improve grid stability: By ensuring that power balance constraints are met, potential problems such as voltage instability and overload can be avoided, thereby enhancing grid stability and reliability. This helps prevent equipment damage and grid collapse, ensuring the continuity and security of power supply.

[0076] Optimize resource allocation: When power imbalance is found, the allocation and utilization of resources can be optimized by reducing the load powered by the flexible interconnection network of low-voltage distribution stations or taking other measures to balance the power. This can not only reduce energy waste, but also improve the operating efficiency of the power grid.

[0077] Enhanced flexibility: The proposed load reduction strategies (such as remote control, automatic demand response, distributed energy utilization, grid topology changes and energy storage system applications) provide greater flexibility for the system. These strategies can be selected and adjusted according to actual conditions and needs to adapt to different grid operation scenarios and conditions.

[0078] Reduced operating costs: By precisely controlling load and power output, the operating costs of the power grid can be reduced. For example, through the application of energy storage systems, energy can be stored during low electricity price periods and released during high electricity price periods, thereby reducing the cost of purchasing electricity. At the same time, reducing equipment damage and maintenance needs can also reduce maintenance costs.

[0079] Node voltage constraint check:

[0080] The voltage constraint of each node in the low-voltage distribution substation area flexible interconnection network is checked. If the node voltage is lower than the voltage lower limit, the load powered by the low-voltage distribution substation area flexible interconnection network continues to be reduced.

[0081] Node voltage constraints ensure that the voltage of each node in the low-voltage distribution area flexible interconnection network is maintained within a safe range to prevent voltage collapse or equipment damage. The following are the instructions:

[0082] Preventing voltage collapse:

[0083] In the power system, if the voltage of a node is too low, the node and its connected equipment may not work properly. In serious cases, it may even cause voltage collapse, affecting the stability of the entire system.

[0084] Protect your device:

[0085] If power equipment works in an unstable voltage environment for a long time, it may be damaged, shortening its service life and increasing maintenance and replacement costs.

[0086] Ensure power supply quality:

[0087] Voltage stability directly affects the quality of power supply. Verifying node voltage constraints can ensure that users receive stable and reliable power supply.

[0088] Meet the operation standards:

[0089] Power systems usually have strict operating standards, including voltage range and fluctuation limits. Verifying node voltage constraints is an important measure to ensure that the system meets these standards.

[0090] The node voltage constraint can be given, for example, in the following form:

[0091] (1) The node voltage constraint range is usually defined by the minimum and maximum voltage values, such as ±10% of the rated voltage.

[0092] (2) The voltage constraint may be given in the form of voltage deviation, which is the percentage deviation from the rated voltage.

[0093] If the node voltage is higher than the upper voltage limit, the topology solution is abandoned at the current SOP output voltage, and the process jumps to the following steps to search and iterate the topology solution again.

[0094] Reduce the load powered by the low-voltage distribution area flexible interconnection network. For example, the load originally powered by the low-voltage distribution area flexible interconnection network can be connected to other backup power supplies. Of course, in addition to this method, there are other ways to achieve load reduction:

[0095] (1) Control non-critical loads through remote control or automatic demand response (ADR) systems to reduce their power consumption.

[0096] (2) Use distributed energy (such as solar energy and wind energy) to meet part of the load and reduce dependence on the main power grid.

[0097] (3) Redistribute the load by changing the topology of the power grid, such as adding or reducing certain lines.

[0098] (4) Whenever possible, increase power generation to meet load demand.

[0099] (5) Use energy storage systems (such as batteries) to store energy during low-load periods and release energy during high-load periods to balance the grid load.

[0100] Node voltage constraint verification is a key link to ensure the stable operation of the flexible interconnection network of low-voltage distribution substations. By verifying node voltage constraints and taking necessary load reduction measures, the following technical benefits can be achieved:

[0101] Enhanced system stability: Verification of node voltage constraints can ensure that the voltage of each node is maintained within a safe range, effectively preventing voltage collapse or equipment damage, thereby greatly enhancing the stability of the entire system.

[0102] Optimize load distribution: When the node voltage is lower than the voltage lower limit, the load distribution can be optimized by reducing the load powered by the flexible interconnection network of the low-voltage distribution station area, so that the system can allocate power resources more reasonably and improve power supply efficiency.

[0103] Reduce the risk of failure: Timely load reduction can avoid equipment failure due to low voltage, reduce power outages and maintenance costs caused by failures, and improve the reliability and availability of power supply.

[0104] Support multiple load reduction strategies: In addition to connecting the load to other backup power sources, it also supports multiple load reduction strategies such as remote control, automatic demand response, distributed energy utilization, grid topology changes and energy storage system applications. These strategies can be flexibly selected according to actual conditions and needs to improve the flexibility and adaptability of the system.

[0105] Step 5: Topology solution search and iteration:

[0106] Determine whether the maximum number of iterations has been reached; if not, update the pheromone and return to step 2 to continue iterating; if reached, record the SOP outlet voltage under the current radial topology as the final result.

[0107] The SOP outlet voltage under the current radial topology refers to the SOP outlet voltage obtained by performing power flow calculation on the current radial topology.

[0108] Each iteration updates the pheromone according to the results of the previous iteration and the algorithm rules, thereby guiding the ants to prefer paths with higher quality (such as low loss, low cost, and high stability) in subsequent searches.

[0109] The above spanning tree algorithm is used to generate a radial topology to ensure that there are no loops in the network and to improve the stability and reliability of the system.

[0110] In the ant colony algorithm, a spanning tree algorithm such as Prim's algorithm or Kruskal's algorithm can be used to assist in building a radial topology. When ants are searching for a path, they follow the spanning tree algorithm to ensure that the final generated topology is radial.

[0111] The ant colony algorithm searches for the optimal path by simulating the behavior of ants looking for food. The ant colony algorithm starts from any node of the low-voltage distribution substation flexible interconnection network, initializes the pheromone concentration on each path of the low-voltage distribution substation flexible interconnection network, and the pheromone represents the attractiveness of the path. Ants are randomly placed on some nodes of the network. Each ant represents a potential path searcher, and the minimum spanning tree is gradually constructed until all nodes are covered. Each ant selects the node to visit next based on the transition probability. Ants move in the network and gradually build a path from the starting point to the end point, that is, a radial topology. During the search process, ants will continuously update the pheromone concentration to reflect the advantages and disadvantages of different paths. Finally, through multiple iterations, the ant colony algorithm will converge to an optimal or nearly optimal topological structure.

[0112] The following is an explanation of the concepts of nodes, edges, distances, costs and SOPs in the flexible interconnection network of the pressure distribution substation area.

[0113] Node:

[0114] In the flexible interconnected network of low-voltage distribution substations, nodes represent various connection points in the power grid, which can be substations, distribution transformers, user access points, etc.

[0115] In the ant colony algorithm, nodes are possible stopover points for ants when searching for paths.

[0116] Edge:

[0117] In the low-voltage distribution substation flexible interconnection network, an edge represents a transmission line or a power channel connecting two nodes, also referred to as a path in this application.

[0118] In the ant colony algorithm, an edge is the path that an ant takes to move from one node to another.

[0119] Distance:

[0120] In the context of an electric grid, distance usually refers to the physical length of the transmission line or the electrical distance between two nodes.

[0121] Cost:

[0122] Cost can include line loss, equipment investment and other aspects, which are used to measure the advantages and disadvantages of a certain topology or path.

[0123] In the ant colony algorithm, cost can be used as an important consideration when selecting a path, reflecting the economy and efficiency of the path, and the cost differences of different paths are reflected by dynamically adjusting the pheromone concentration.

[0124] SOP(Soft Open Point):

[0125] SOP is an intelligent operating point in the flexible interconnected network of low-voltage distribution substations, with functions such as regulating power flow and controlling voltage.

[0126] During the optimization process, the position and state of the SOP (such as open or closed) will affect the power flow distribution and voltage level of the entire network.

[0127] In each iteration, the outlet voltage of the SOP is calculated and verified according to the current topology.

[0128] If the voltage constraint or other constraints (such as power balance constraint, node voltage constraint, etc.) are not met, the topology needs to be adjusted.

[0129] When adjusting the topology, the power flow distribution and voltage level can be affected by changing the state of the SOP (such as opening or closing), thereby finding the optimal topology that meets all constraints.

[0130] In summary, by combining the spanning tree algorithm, ant colony algorithm with the flexible interconnection network of low-voltage distribution substations and SOP, the intelligent control of the SOP outlet voltage can be achieved and the stability and reliability of the power system can be improved.

[0131] Specific implementation process:

[0132] Initialization: Initialize the pheromone concentration on each path of the flexible interconnection network in the distribution station area.

[0133] This is equivalent to providing an initial attractiveness distribution for the ants to search for paths.

[0134] The initial value of the pheromone concentration can be set according to factors such as the cost of the path to reflect the initial advantages and disadvantages of different paths. The higher the pheromone concentration, the better the path (for example, the lower the cost).

[0135] Ant placement: Ants are randomly placed on some nodes of the network, and each ant represents a potential path searcher.

[0136] Construct a minimum spanning tree: Build the minimum spanning tree step by step until all nodes are covered. Use Prim's algorithm or Kruskal's algorithm to assist the construction process.

[0137] Path search: Each ant selects the node to visit next based on the transition probability and constructs a path from the starting point to the end point, that is, a radial topology.

[0138] Pheromone update: Dynamically update the pheromone concentration based on the quality of the path taken by the ants.

[0139] Iterative optimization: Repeat the above process until the stopping condition is met and finally the optimal radial topology is obtained.

[0140] The important parameters are described as follows:

[0141] (1) Dynamic pheromone update

[0142] formula:

[0143]

[0144] express Time Path The pheromone concentration on.

[0145] express Time Path The pheromone concentration on represents the updated value of the pheromone concentration.

[0146] express The pheromone evaporation rate at a moment, a A parameter that may be varied to control the rate at which pheromones decay. The pheromone evaporation rate can represent dynamic changes in grid operation, such as load changes, which may cause certain paths to become less attractive.

[0147] Indicates Ants in time On the path The amount of pheromone left on the path reflects the quality of the path.

[0148] The above formula describes the dynamic update process of pheromones. Pheromones not only decrease due to evaporation, but also increase due to the walking of ants. Dynamically adjusted evaporation rate The algorithm is allowed to adjust the degree of pheromone retention in real time according to the network status, thereby improving the adaptability and flexibility of the algorithm.

[0149] (2) Pheromone enhancement mechanism

[0150] formula:

[0151] express Time Path The amount of pheromone enhancement on the path importance or urgency.

[0152] Pheromone enhancement mechanisms work by adding an extra pheromone to important or urgent pathways. ,The enhanced pheromone amount will be substituted into the pheromone update formula to calculate the updated pheromone concentration, and then substituted into the transfer probability and calculation formula to give priority to important or urgent paths, speed up the search and optimization of these paths, and improve the response speed and efficiency of the algorithm in processing key tasks.

[0153] The importance or urgency of a path can be determined by:

[0154] 2.1) Stability requirements of power systems

[0155] Voltage stability: The stability of the voltage on a path is a direct indicator of its importance. If the voltage stability involved in a path is poor, prone to fluctuations or beyond the safe range, then the importance of this path is higher.

[0156] Power flow: The stability and balance of power flow on the path are also key factors. If a path carries a large amount of power flow and is critical to the power balance of the grid, its urgency and importance are high.

[0157] 2.2) Load Priority

[0158] Critical loads: For paths that supply power to critical facilities (such as hospitals, data centers, etc.), their importance is naturally higher, as any power interruption may lead to serious consequences.

[0159] Load density: Some areas may be high load areas due to high residential or commercial density. The power supply paths in these areas are usually of higher importance.

[0160] 2.3) Network topology

[0161] Topological criticality: In a network topology, certain paths may be particularly important because they connect key nodes or serve as the main power supply channels.

[0162] Redundant path: As a backup or redundant path, although it may not be the optimal path under normal circumstances, its importance will increase dramatically when the primary path has problems.

[0163] 2.4) Historical operation data

[0164] Failure frequency: Paths that have historically experienced frequent failures or issues may be marked as high urgency because they may need to be prioritized for maintenance or optimization.

[0165] Load change trends: By analyzing historical load data and trends, it is possible to predict which paths may become more important or urgent in the future.

[0166] 2.5) Real-time monitoring and analysis

[0167] Real-time monitoring: The real-time monitoring system can dynamically identify which paths are currently becoming urgent due to voltage, frequency and other issues.

[0168] Predictive analysis: Using predictive models to analyze the operating status of the power grid can identify paths where problems may occur in advance, thereby improving their urgency rating.

[0169] 2.6) Environmental and external factors

[0170] Weather impacts: Extreme weather conditions may affect the operation of the grid, increasing the stability and importance of certain paths.

[0171] Emergencies: Natural disasters or other emergencies may cause certain paths to rapidly increase in importance and urgency.

[0172] In the ant colony algorithm, the above factors can be converted into parameters in the algorithm in the following ways:

[0173] Each path is scored based on the factors listed above.

[0174] The score is converted into a pheromone enhancement value. The higher the importance and urgency of the path, the higher its pheromone enhancement value. The larger it is, the more it affects the ants’ path selection and optimization process.

[0175] In this way, the ant colony algorithm can more intelligently identify and manage critical paths in the power grid, improving the overall performance and reliability of the grid.

[0176] (3) Adaptive heuristic information

[0177] formula:

[0178]

[0179] Indicates the path The heuristic factor on Representation Node To Node Voltage drop, Represents an adjustment factor that changes over time, reflecting the impact of environmental changes or historical data.

[0180] The heuristic information is calculated based on the voltage drop between nodes and the dynamic adjustment factor, which enables the algorithm to dynamically adjust the search strategy according to environmental changes and historical experience, improving the efficiency and robustness of the algorithm.

[0181] (4) Newly introduced target factors.

[0182] path The newly introduced target factor value , used to reflect the path performance on targets other than those considered by pheromone concentration and heuristic factors;

[0183] The value of can be determined in the following way:

[0184] Define goals: First, you need to clarify what other optimization goals are, such as reliability, time, stability, etc.

[0185] Quantitative indicators: These goals are quantified into indicators that can be calculated. For example, reliability can be quantified as the inverse of the path failure rate, time can be quantified as the transmission delay of the path, and stability can be quantified as the voltage stability of the path.

[0186] Weight assignment: Assign weights to each objective based on its importance. The weights can be determined by expert experience, historical data, or the optimization algorithm itself.

[0187] Calculate the target factor value: Calculate the target factor value corresponding to each path based on the quantified indicators and the assigned weights For example, if the reliability, time and stability of the path are respectively , and Indicates that, then It can be expressed as a weighted sum or a comprehensive score of these indicators.

[0188] (5) Multi-objective optimization

[0189] formula:

[0190]

[0191] Represents an ant slave node To Node The transition probability.

[0192] , and They are the adjustment parameters of pheromone importance, heuristic factor importance and the newly introduced target factor importance.

[0193] The above formula uses multi-objective optimization to determine the ant's transfer probability by combining pheromone concentration, heuristic information, and new target factors. Multi-objective optimization allows the algorithm to consider multiple performance indicators such as cost, time, and reliability at the same time, thereby providing a more comprehensive and balanced optimization solution.

[0194] The ant colony algorithm optimizes the power flow distribution by continuously adjusting the network topology. For example, by adding or reducing certain lines, the path of power flow can be changed, thereby affecting the node voltage and SOP outlet voltage to meet the constraints and goals of power system operation. As the algorithm iterates and converges, the SOP outlet voltage will gradually stabilize at an optimal or near-optimal value.

[0195] The embodiment of the present application uses the ant colony algorithm to search and iterate the topology solution, which has the following advantages:

[0196] Global optimization capability: The ant colony algorithm has a powerful global search capability and can consider all possible topologies in the distribution network, rather than just being limited to the local optimal solution. This helps to discover a more efficient and stable radial topology that meets the constraints of the SOP outlet voltage and node voltage.

[0197] Adaptability: The pheromone update mechanism in the ant colony algorithm enables the algorithm to adaptively adjust the search direction and select the next search path based on historical search experience (i.e., pheromone concentration) and heuristic information (such as voltage drop). This adaptability enables the algorithm to search for the optimal solution more intelligently.

[0198] Robustness: The ant colony algorithm is not sensitive to initial conditions. Even when the initial conditions are poor, it can gradually converge to the optimal solution through iteration. In addition, the algorithm is also highly robust to changes in network structure and can flexibly respond to changes in network topology.

[0199] Flexibility: The ant colony algorithm can be combined with a variety of heuristic algorithms, such as Prim's algorithm or Kruskal's algorithm, to construct a minimum spanning tree. This flexibility enables the algorithm to be adjusted and optimized according to different application scenarios and requirements.

[0200] Optimize power flow distribution: By continuously adjusting the network topology through the ant colony algorithm, the power flow distribution can be optimized, making the power flow more reasonable and efficient, which helps to reduce network losses, improve power supply quality, and enhance system stability.

[0201] Easy to expand and integrate: As a general optimization algorithm, the ant colony algorithm can be easily integrated and expanded with other power system optimization algorithms or software platforms, making the algorithm more widely applicable and more scalable in practical applications.

[0202] Visualization and decision support: The radial topology structure obtained through the ant colony algorithm search can provide intuitive decision support for power system planners and operators. At the same time, the algorithm's visualization interface can display the search process and results, making it easier for personnel to understand and analyze.

[0203] The embodiment of the present application also provides an electronic device, including: a memory and a processor;

[0204] The memory is used to store computer programs;

[0205] The processor is used to call the computer program to execute the method as described above.

[0206] An embodiment of the present application further provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed on an electronic device, the electronic device implements the method as described above.

[0207] An embodiment of the present application further provides a computer program product, including a computer program. When the computer program is executed on an electronic device, the electronic device implements the method as described above.

[0208] The embodiments of the present application also provide a specific implementation method of an electronic device, a computer-readable storage medium, and a computer program product, which can refer to the specific embodiments of the above method and will not be described in detail here.

[0209] Obviously, those skilled in the art should understand that the above-mentioned units or steps of the present application can be implemented by a general-purpose computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, and optionally, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. In this way, the present application is not limited to any specific combination of hardware and software.

[0210] The above description of the embodiments of the present application is only a partial embodiment of the present application, which is used to enable professionals in the field to implement or use the content of the present application, and is not used to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A method for controlling the SOP outlet voltage in a low-voltage distribution station area flexible interconnection network, characterized in that: include: Step 1: Initialization settings: The current SOP outlet voltage in the low-voltage distribution station area flexible interconnection is used as the initial value of the SOP outlet voltage, and the parameters of the ant colony algorithm are set, including the number of ants and the number of iterations, and the initial value of the number of iterations is set to 1; Step 2: The ant colony uses the spanning tree algorithm based on SOP to search for paths and generate a radial topology; Step 3: Calculate the power flow for the current radial topology; Step 4: Determine whether the power flow calculation results meet the power balance constraints and node voltage constraints; If the power balance constraint is not met, or the node voltage is lower than the voltage lower limit, reduce the load powered by the low-voltage distribution station area flexible interconnection network, and go to step 3 to recalculate the power flow until the power flow calculation result meets the power balance constraint and the voltage of each node meets the node voltage constraint, record the current radial topology, and go to step 5; if the node voltage is higher than the voltage upper limit, abandon the current radial topology and jump to step 5; Step 5: Topology solution search and iteration: Determine whether the maximum number of iterations has been reached; If it is not reached, the pheromone is updated and the process returns to step 2 to continue the iteration; if it is reached, the SOP outlet voltage under the current radial topology is recorded as the final result.

2. The method according to claim 1, characterized in that In step 4, the power balance constraint formula is: ； In the formula, and Node Flow to Node Active power and reactive power; Node The set of path head nodes for the end nodes; Node The path end node set of the head end node; For Node Voltage; For Node Flow to Node The current; and Node and The path formed resistance and reactance; and Node The sum of the active power and reactive power injected into the and Node Active power and reactive power injected by distributed generation; and Inject SOP into any node in the radial topology Active power and reactive power; and Node The active power and reactive power consumed by the load.

3. The method according to claim 1, characterized in that In step 2, the ant colony uses the spanning tree algorithm to search for paths, and the transition probability formula is: ； in, Indicates ant slave node To Node The transition probability of For the node The set of adjacent nodes; express Time Path The pheromone concentration on Indicates the path The heuristic factor on Indicates the path The newly introduced target factor value is used to reflect the path performance on targets other than those considered by pheromone concentration and heuristic factors; , and They are the adjustment parameters of pheromone importance, heuristic factor importance and the newly introduced target factor importance.

4. The method according to claim 3, characterized in that Said The update formula is: ； in, express Time Path pheromone concentration on; express The pheromone evaporation rate at each moment; Indicates Ants in time On the path The amount of pheromones left on the body.

5. The method according to claim 4, characterized in that The pheromone enhancement mechanism is adopted for important or urgent paths, and the pheromone quantity calculation formula is: ； in, express Time Path The amount of pheromone enhancement on the path importance or urgency.

6. The method according to claim 4, characterized in that Said The calculation formula is: ； in, Representation Node To Node Voltage drop, The table shows adjustment factors that change over time, reflecting the impact of environmental changes or historical data.

7. The method according to claim 4, characterized in that Said It is calculated by weighting the quantitative values ​​of multiple other objectives.

8. An electronic device, characterized in that: include: Memory and processor; The memory is used to store computer programs; The processor is configured to call the computer program to execute the method according to any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed on an electronic device, the electronic device implements the method according to any one of claims 1 to 7.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed on an electronic device, the electronic device implements the method according to any one of claims 1 to 7.

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