A method and system for verifying load recovery based on power system reconfiguration

Abstract

This invention provides a method and system for verifying load restoration quantity based on power system reconfiguration. The method includes: acquiring the topology and load distribution of the power system reconfiguration area; constructing objective functions for multi-period unit operating costs and load restoration quantity related to fault recovery in the reconfiguration area based on the topology and load distribution; generating a coupled constraint cutting plane based on the linear solvable range of the objective functions, and iteratively solving for the load restoration quantity of the power system under different operating conditions using Taylor expansion; verifying whether the node voltage and system frequency corresponding to the load restoration quantity meet the standard requirements according to GBT 40613-2021 standard; and for load restoration quantities that meet the standard, performing optimal decision-making by combining the basic cost-load mapping function and environmental factor correction coefficients to output the final load restoration scheme. This invention reduces the decision-making difficulty of load restoration quantity during power system reconfiguration and ensures the safe and stable operation of the power system during reconfiguration.

Description

Technical Field

[0001] This invention relates to the field of load restoration quantity verification technology, and in particular to a method and system for verifying load restoration quantity based on power system reconfiguration. Background Technology

[0002] In the initial stage of power system reconstruction after a fault occurs and is cleared, the selection of load restoration quantity faces multiple technical challenges: load characteristics are highly uncertain due to factors such as weather and time of day, traditional static modeling methods are difficult to predict accurately, which can easily cause the restoration quantity to deviate from the actual demand, the design of economic indicators lacks flexibility, and insufficient assessment of implicit costs leads to deviations in economic benefits.

[0003] Furthermore, existing security verification methods have significant shortcomings, particularly in their focus on static stability after topology reconstruction while neglecting dynamic security issues such as transient overvoltages and frequency fluctuations during the recovery process. In other words, they prioritize static stability while ignoring dynamic risks like transient overvoltages. In some scenarios, the scheduling and control center's decision-making relies excessively on human experience, ignoring the dynamic constraints of real-time network conditions, which may lead to equipment overload risks. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for verifying load recovery based on power system reconfiguration, aiming to solve the problem of rapid self-healing of the system after a smart grid fault and improve the efficiency of power dispatch decision-making.

[0005] In a first aspect, the present invention provides a method for verifying load recovery based on power system reconfiguration, the method comprising:

[0006] Obtain the topology and load distribution of the power system reconfiguration area, and construct objective functions for the multi-period unit operating cost and load restoration amount of the fault recovery in the reconfiguration area based on the topology and load distribution;

[0007] Based on the linear solution range of the objective function, a coupled constraint cutting plane based on the recovery amount is generated, and the load recovery amount of the power system under different operating conditions is solved iteratively through Taylor expansion.

[0008] According to the GBT 40613-2021 standard, verify whether the node voltage and system frequency corresponding to the load restoration amount meet the standard requirements;

[0009] For load restoration amounts that meet the standards, an optimal decision is made by combining the basic cost-load mapping function and environmental factor correction coefficients to output the final load restoration plan.

[0010] In some embodiments, the objective function is constructed according to the following formula:

[0011] ;

[0012] Construct the constraints for the objective function using the following formula:

[0013] ;

[0014] in, The startup cost of unit i, The startup state of unit i, if For hot standby of the unit, if For unit startup, For the operating cost of unit i, This represents the actual output of unit i at present. Let h be the unit cost coefficient related to the output of unit i, and h be the penalty coefficient for unrestored load. Let j be the load carried by the path station j at time t. The recovery priority weight for load node j is... To characterize the unit's output The strength of the constraints on system power balance, Here, t represents the unit's minimum output, t represents the load recovery time, and T represents the maximum time required for load recovery as specified by the control center. This represents the maximum value of the load recovery. For the line Active power on the side, For the line Maximum transmission capacity on the side The reactive power output for charging the unit's balancing circuit. G represents the reactive power of the line under no-load conditions, G represents the rated generating units put into power system reconfiguration, and N represents the number of target grid lines participating in power system reconfiguration.

[0015] In some embodiments, the step of generating a coupled constraint cutting plane based on the linear solvable range of the objective function, and iteratively solving for the load recovery amount of the power system under different operating conditions via Taylor expansion, includes:

[0016] The expression for the coupling constraint cutting plane is:

[0017] ;

[0018] in, As an auxiliary variable for calculating unit start-up costs, The load recovery priority weight of load node j in the k-th iteration is... To characterize the unit output in the k-th iteration The constraint strength on the system power balance, where k is the iteration number. This is a system voltage function used to describe the nonlinear relationship between generator output and node voltage. For the active power output decision variables of the unit in the current iteration, This is the lower limit threshold for voltage safety. This is a transpose.

[0019] In some embodiments, the step of verifying whether the node voltage and system frequency corresponding to the load restoration amount meet the standard requirements according to GBT 40613-2021 includes:

[0020] The node voltage over-limit judgment value is calculated according to the following formula:

[0021] ;

[0022] in, Let be the voltage limit threshold judgment value of node i at time t. Let be the per-unit voltage value of node i at time t. This represents the per-unit voltage value at the starting node of the line. This is the upper limit of voltage safety. Let be the per-unit voltage value of node i. and These are the per-unit values ​​of resistance and reactance of the line between nodes i and i-1, respectively. , Let be the per-unit values ​​of active power and reactive power of the load restoration at node n at time t. , They are respectively Always access node The per-unit values ​​of active power and reactive power of energy storage equipment;

[0023] Determine whether the node voltage over-limit judgment value during the load restoration period is within the first preset range. If it is within the first preset range, it meets the standard; if it is not within the first preset range, it does not meet the standard.

[0024] Determine if the system frequency deviation meets the following formula. If it does, the system meets the standard; otherwise, it does not.

[0025] ;

[0026] Where H is the inertial time constant, This is the frequency deviation value. This refers to the change in unit output. Let be the change in load power, and D be the damping coefficient.

[0027] In some embodiments, the step of making an optimal decision on the load restoration amount that meets the criteria, combining the basic cost-load mapping function and the environmental factor correction coefficient, to output the final load restoration plan includes:

[0028] Make the optimal decision based on the following formula:

[0029] ;

[0030] in, For total cost, This is the cost-load mapping function. This is the environmental factor correction coefficient. , Here, represents the cost slope coefficient, and represents the marginal cost of the first load segment and the second load segment, respectively. The load values ​​of the first load segment are all less than the load values ​​of the second load segment. Let J be the load to be restored at node j. The baseline load threshold for node j. For ambient temperature, As the reference temperature, Energy consumption for generator auxiliary starting equipment. , , These are the weight parameters.

[0031] Secondly, the present invention provides a load recovery quantity verification system based on power system reconfiguration, the system comprising:

[0032] The objective function construction module is used to obtain the topology and load distribution of the power system reconfiguration area, and to construct objective functions for the multi-period unit operating cost and load restoration amount of the fault recovery in the reconfiguration area based on the topology and load distribution.

[0033] The constraint module is used to generate a coupled constraint cutting plane based on the recovery amount according to the linear solution range of the objective function, and to solve the load recovery amount of the power system under different operating conditions through Taylor expansion iteratively.

[0034] The verification module is used to verify whether the node voltage and system frequency corresponding to the load restoration amount meet the standard requirements according to the GBT 40613-2021 standard.

[0035] The decision module is used to make optimal decisions on the load restoration amount that meets the standards, combining the basic cost-load mapping function and environmental factor correction coefficients, so as to output the final load restoration plan.

[0036] Thirdly, the present invention provides a storage medium that stores one or more programs, which, when executed by a processor, implement the above-described method for verifying load recovery based on power system reconfiguration.

[0037] Fourthly, the present invention provides an electronic device, the electronic device comprising a memory and a processor, wherein:

[0038] The memory is used to store computer programs;

[0039] When the processor executes the computer program stored in the memory, it implements the above-mentioned method for verifying load recovery based on power system reconfiguration.

[0040] In summary, the load recovery quantity verification method based on power system reconfiguration described above is a valuable supplement to the current power system rapid self-healing and load recovery decision-making system. By employing generalized Benders decomposition to establish the target function for load recovery cost in the area to be reconfigured, iteratively solving the problem using a coupled constraint cutting plane algorithm based on load recovery quantity, and utilizing the basic cost-load mapping function and environmental factor correction coefficients to determine the load recovery quantity, the decision-making difficulty of load recovery quantity during power system reconfiguration is reduced. This rationalizes various economic indicators of power system load recovery, improves the decision-making efficiency of the dispatch control center regarding load recovery quantity during power grid reconfiguration, and ensures the safe and stable operation of the power system during reconfiguration. Attached Figure Description

[0041] Figure 1 This is a flowchart of a load recovery quantity verification method based on power system reconfiguration proposed in an embodiment of the present invention;

[0042] Figure 2 This is one specific form of power system reconfiguration area topology and load distribution provided in an embodiment of the present invention;

[0043] Figure 3 This is an example of the iterative solution process of the coupled constraint cutting plane algorithm based on load recovery amount for the objective function within the linear solvable range according to an embodiment of the present invention;

[0044] Figure 4 A voltage curve of a node during load recovery according to an embodiment of the present invention;

[0045] Figure 5 A frequency curve of a node during load recovery according to an embodiment of the present invention;

[0046] Figure 6 This is a schematic diagram of the structure of a load recovery verification system based on power system reconfiguration proposed in an embodiment of the present invention.

[0047] The following detailed description, in conjunction with the accompanying drawings, will further illustrate the present invention. Detailed Implementation

[0048] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, 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. Unless otherwise defined, the technical or scientific terms used herein should have the ordinary meaning understood by those skilled in the art. The terms "comprising" and similar expressions used herein mean that the element or object preceding the word covers the element or object listed after the word and its equivalents, but does not exclude other elements or objects.

[0049] like Figure 1 As shown, an embodiment of the present invention proposes a method for verifying load recovery based on power system reconfiguration. This method includes steps S101 to S104, wherein:

[0050] Step S101: Obtain the topology and load distribution of the power system reconfiguration area, and construct objective functions for the multi-period unit operating cost and load restoration amount of the fault recovery in the reconfiguration area based on the topology and load distribution;

[0051] It should be noted that, for the load restoration amount in traditional power system reconfiguration areas, only a weak constraint relationship is established between the "actual output" of the starting power source in that area and the "balance amount" of load restoration, neglecting to measure unit output from an economic perspective. The constraints on system power balance, especially the recovery path including lines within the maximum time T required for load restoration as specified by the control center. To determine the maximum effective transmission capacity, this step optimizes the objective function by introducing multi-period unit operating costs and load recovery amounts. This is done while ensuring the reactive power output of the unit's balancing lines matches the reactive power of the lines under no-load conditions, and also comprehensively considering unit start-up and shutdown costs. The dynamic coupling relationship between the recovery path and line transmission efficiency is restored, which also serves as a characterization of unit output. The need for optimization and verification of the system's power balance and regional topology adjustment capabilities, as well as load recovery.

[0052] Specifically, in some embodiments, such as Figure 2 As shown, G1 to G4 are generating units, T1 to T4 are step-up transformers, A1 to A15 are substations, B1 to B4 are upstream substations, and L1 to L15 are substation loads. This illustrates one specific form of power system reconfiguration topology and load distribution. The objective function constructed based on this specific form is expressed as follows:

[0053] ;

[0054] Construct the constraints for the objective function using the following formula:

[0055] ;

[0056] in, The startup cost of unit i, The startup state of unit i, if For hot standby of the unit, if For unit startup, For the operating cost of unit i, This represents the actual output of unit i at present. Let h be the unit cost coefficient related to the output of unit i, and h be the penalty coefficient for unrestored load. Let j be the load carried by the path station j at time t. The recovery priority weight for load node j is... To characterize the unit's output The strength of the constraints on system power balance, Here, t represents the unit's minimum output, t represents the load recovery time, and T represents the maximum time required for load recovery as specified by the control center. This represents the maximum value of the load recovery. For the line Active power on the side, For the line Maximum transmission capacity on the side The reactive power output for charging the unit's balancing circuit. G represents the reactive power of the line under no-load conditions, G represents the rated generating units put into power system reconfiguration, and N represents the number of target grid lines participating in power system reconfiguration.

[0057] Step S102: Generate a coupled constraint cutting plane based on the linear solution range of the objective function, and solve the load recovery amount of the power system under different operating conditions through Taylor expansion iteratively.

[0058] It should be noted that, as Figure 3 The diagram illustrates the solution process of the coupled constraint cutting plane algorithm based on load recovery amount for the objective function within the linear solvable range. Specifically, the expression for the coupled constraint cutting plane is:

[0059] ;

[0060] in, As an auxiliary variable for calculating unit start-up costs, The load recovery priority weight of load node j in the k-th iteration is... To characterize the unit output in the k-th iteration The constraint strength on the system power balance, where k is the iteration number. This is a system voltage function used to describe the nonlinear relationship between generator output and node voltage. For the active power output decision variables of the unit in the current iteration, This is the lower limit threshold for voltage safety. This is a transpose.

[0061] In summary, by introducing auxiliary calculation variables for unit start-up costs... By dynamically coupling the linear solution range of the objective function with the restitution quantity, and constructing a coupling constraint cutting plane, the system voltage function is... The nonlinear constraints describing the load output and node voltage are transformed into a tractable linear form. After Taylor expansion, the solution is iteratively obtained, which effectively solves the convergence problem of the traditional cutting plane method under complex operating conditions. It can adapt to different system operating conditions and realize the rapid generation of recovery schemes. It retains the rigor of load recovery planning and significantly improves the computational efficiency through iterative optimization.

[0062] Step S103: According to GBT 40613-2021 standard, verify whether the node voltage and system frequency corresponding to the load restoration amount meet the standard requirements;

[0063] It should be pointed out that, as Figure 4 and Figure 5 As shown, in order to determine whether the voltage and power meet the standards, the node voltage over-limit judgment value needs to be calculated according to the following formula:

[0064] ;

[0065] in, Let be the voltage limit threshold judgment value of node i at time t. Let be the per-unit voltage value of node i at time t. This represents the per-unit voltage value at the starting node of the line. This is the upper limit of voltage safety. Let be the per-unit voltage value of node i. and These are the per-unit values ​​of resistance and reactance of the line between nodes i and i-1, respectively. , Let be the per-unit values ​​of active power and reactive power of the load restoration at node n at time t. , They are respectively Always access node The per-unit values ​​of active power and reactive power of energy storage equipment;

[0066] Determine whether the node voltage over-limit judgment value during the load restoration period is within the first preset range. If it is within the first preset range, it meets the standard; if it is not within the first preset range, it does not meet the standard.

[0067] Determine if the system frequency deviation meets the following formula. If it does, the system meets the standard; otherwise, it does not.

[0068] ;

[0069] Where H is the inertial time constant, This is the frequency deviation value. This refers to the change in unit output. Let be the change in load power, and D be the damping coefficient.

[0070] Step S104: For the load restoration amount that meets the standard, make an optimal decision by combining the basic cost-load mapping function and the environmental factor correction coefficient to output the final load restoration plan.

[0071] Specifically, in this step, the optimal decision is made according to the following formula: the scheme with the lowest total cost is selected as the final load restoration scheme, and then the per-unit values ​​of active power and reactive power of the load restoration amount are output:

[0072] ;

[0073] in, For total cost, This is the cost-load mapping function. This is the environmental factor correction coefficient. , Here, represents the cost slope coefficient, and represents the marginal cost of the first load segment and the second load segment, respectively. The load values ​​of the first load segment are all less than the load values ​​of the second load segment. Let J be the load to be restored at node j. The baseline load threshold for node j. For ambient temperature, As the reference temperature, Energy consumption for generator auxiliary starting equipment. , , These are the weight parameters.

[0074] It should be noted that the first load segment is the low load segment, and the second load segment is the high load segment. For example, in a certain area, there are two load segments: the first load segment is 70,000 kW, and the second load segment is 70,000 to 150,000 kW. The coefficient for the first segment is 0.98, and the coefficient for the second segment is 1.12. The 70,000 kW load in the first load segment is restored sequentially through three stations: A, B, and C. Station A restores 20,000 kW, station B restores 30,000 kW, and station C restores 20,000 kW. If the standard electricity price is 320 yuan / 10,000 kW, then the coefficient is 0.98. The startup cost is calculated at 320 yuan / 10,000 kW. The second load segment consists of three stations: D, E, and F, with costs of 40,000 yuan / 10,000 yuan / kW for station D, 30,000 yuan / kW for station E, and 10,000 yuan / kW for station F. Assuming the path recovers to station D, the total load across A, B, C, and D is 110,000 yuan / kW. At this point, the load is in the second load segment, and the cost is calculated as 1.12. The startup cost is calculated at 320 yuan per 10,000 kilowatts.

[0075] By introducing a cost-load mapping function Environmental factor correction coefficient A decision-making method for optimizing load restoration quantities that meet the standards has been developed, which changes the limitations of traditional load restoration quantities that are subject to single cost constraints. This improves the regional adaptability and scalability of the decision-making process, and the final decision-making results take into account both economic efficiency and engineering feasibility, providing an intelligent decision support tool for regional power grid reconfiguration.

[0076] In summary, the calculation and processing based on load restoration quantity verification methods during power system reconfiguration is a valuable supplement to the current power system rapid self-healing and load restoration decision-making system. By employing generalized Benders decomposition to establish the objective function for load restoration cost in the area to be reconfigured, iteratively solving the problem using a coupled constraint cutting plane algorithm based on load restoration quantity, and utilizing the basic cost-load mapping function and environmental factor correction coefficients to determine the load restoration quantity, the decision-making difficulty of load restoration quantity during power system reconfiguration is reduced. This rationalizes various economic indicators of power system load restoration, improves the decision-making efficiency of the dispatch control center on load restoration quantity during power grid reconfiguration, and ensures the safe and stable operation of the power system during reconfiguration.

[0077] like Figure 6 As shown, an embodiment of the present invention also proposes a load recovery quantity verification system based on power system reconfiguration, the system comprising:

[0078] The objective function construction module 10 is used to obtain the topology and load distribution of the power system reconfiguration area, and to construct objective functions for the multi-period unit operating cost and load restoration amount of the fault recovery in the reconfiguration area based on the topology and load distribution.

[0079] The constraint module 20 is used to generate a coupled constraint cutting plane based on the recovery amount according to the linear solvable range of the objective function, and to solve the load recovery amount of the power system under different operating conditions through Taylor expansion iteratively.

[0080] The verification module 30 is used to verify whether the node voltage and system frequency corresponding to the load restoration amount meet the standard requirements according to the GBT 40613-2021 standard.

[0081] The decision module 40 is used to make an optimal decision on the load restoration amount that meets the criteria, combining the basic cost-load mapping function and the environmental factor correction coefficient, so as to output the final load restoration plan.

[0082] In another aspect, the present invention also proposes a storage medium on which one or more programs are stored, which, when executed by a processor, implement the above-described method for verifying load recovery based on power system reconfiguration.

[0083] In another aspect, the present invention also proposes an electronic device, including a memory and a processor, wherein the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory to realize the above-mentioned load recovery quantity verification method based on power system reconfiguration.

[0084] Those skilled in the art will understand that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can mean any means that can contain stored, communicated, propagated, or transmitted programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0085] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0086] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0087] While embodiments of the present invention have been described in detail above, it will be apparent to those skilled in the art that various modifications and variations can be made to these embodiments. However, it should be understood that such modifications and variations fall within the scope and spirit of the invention as set forth in the claims. Furthermore, the invention described herein may have other embodiments and can be implemented or carried out in various ways.

Claims

1. A method for verifying load recovery quantity based on power system reconfiguration, characterized in that, The method includes: Obtain the topology and load distribution of the power system reconfiguration area, and construct objective functions for the multi-period unit operating cost and load restoration amount of the fault recovery in the reconfiguration area based on the topology and load distribution; Construct the objective function based on the following formula: ； Construct the constraints for the objective function using the following formula: ； in, The startup cost of unit i, The startup state of unit i, if For hot standby of the unit, if For unit startup, For the operating cost of unit i, This represents the actual output of unit i at present. Let h be the unit cost coefficient related to the output of unit i, and h be the penalty coefficient for unrestored load. Let j be the load carried by the path station j at time t. The recovery priority weight for load node j is... To characterize the unit's output The strength of the constraints on system power balance, Here, t represents the unit's minimum output, t represents the load recovery time, and T represents the maximum time required for load recovery as specified by the control center. This represents the maximum value of the load recovery. For the line Active power on the side, For the line Maximum transmission capacity on the side The reactive power output for charging the unit's balancing circuit. G represents the reactive power of the line when it is unloaded, G represents the rated generating unit put into power system reconfiguration, and N represents the number of target grid lines participating in power system reconfiguration. Based on the linear solution range of the objective function, a coupled constraint cutting plane based on the recovery amount is generated, and the load recovery amount of the power system under different operating conditions is solved iteratively through Taylor expansion. According to the GBT 40613-2021 standard, verify whether the node voltage and system frequency corresponding to the load restoration amount meet the standard requirements; For load restoration amounts that meet the standards, an optimal decision is made by combining the basic cost-load mapping function and environmental factor correction coefficients to output the final load restoration plan; Make the optimal decision based on the following formula: ； in, For total cost, This is the cost-load mapping function. This is the environmental factor correction coefficient. , Here, represents the cost slope coefficient, and represents the marginal cost of the first load segment and the second load segment, respectively. The load values ​​of the first load segment are all less than the load values ​​of the second load segment. Let J be the load to be restored at node j. The baseline load threshold for node j. For ambient temperature, As the reference temperature, Energy consumption for generator auxiliary starting equipment. , , These are the weight parameters.

2. The method for verifying load recovery based on power system reconfiguration according to claim 1, characterized in that, The steps of generating a coupled constraint cutting plane based on the linear solution range of the objective function, and iteratively solving for the load recovery amount of the power system under different operating conditions via Taylor expansion, include: The expression for the coupling constraint cutting plane is: ； in, As an auxiliary variable for calculating unit start-up costs, The load recovery priority weight of load node j in the k-th iteration is... To characterize the unit output in the k-th iteration The constraint strength on the system power balance, where k is the iteration number. This is a system voltage function used to describe the nonlinear relationship between generator output and node voltage. For the active power output decision variables of the unit in the current iteration, This is the lower limit threshold for voltage safety. This is a transpose.

3. The method for verifying load recovery based on power system reconfiguration according to claim 2, characterized in that, The steps for verifying whether the node voltage and system frequency corresponding to the load restoration amount meet the standard requirements according to GBT 40613-2021 include: The node voltage over-limit judgment value is calculated according to the following formula: ； in, Let be the voltage limit threshold judgment value of node i at time t. Let be the per-unit voltage value of node i at time t. This represents the per-unit voltage value at the starting node of the line. This is the upper limit of voltage safety. Let be the per-unit voltage value of node i. and These are the per-unit values ​​of resistance and reactance of the line between nodes i and i-1, respectively. , Let be the per-unit values ​​of active power and reactive power of the load restoration at node n at time t. , They are respectively Always access node The per-unit values ​​of active power and reactive power of energy storage equipment; Determine whether the node voltage over-limit judgment value during the load restoration period is within the first preset range. If it is within the first preset range, it meets the standard; if it is not within the first preset range, it does not meet the standard. Determine if the system frequency deviation meets the following formula. If it does, the system meets the standard; otherwise, it does not. ； Where H is the inertial time constant, This is the frequency deviation value. This refers to the change in unit output. Let be the change in load power, and D be the damping coefficient.

4. A load recovery quantity verification system based on power system reconfiguration, used to implement the load recovery quantity verification method based on power system reconfiguration as described in any one of claims 1-3, characterized in that, The system includes: The objective function construction module is used to obtain the topology and load distribution of the power system reconfiguration area, and to construct objective functions for the multi-period unit operating cost and load restoration amount of the fault recovery in the reconfiguration area based on the topology and load distribution. The constraint module is used to generate a coupled constraint cutting plane based on the recovery amount according to the linear solution range of the objective function, and to solve the load recovery amount of the power system under different operating conditions through Taylor expansion iteratively. The verification module is used to verify whether the node voltage and system frequency corresponding to the load restoration amount meet the standard requirements according to the GBT 40613-2021 standard. The decision module is used to make optimal decisions on the load restoration amount that meets the standards, combining the basic cost-load mapping function and environmental factor correction coefficients, so as to output the final load restoration plan.

5. A storage medium, characterized in that, The storage medium stores one or more programs that, when executed by a processor, implement the load recovery verification method based on power system reconfiguration as described in any one of claims 1-3.

6. An electronic device, characterized in that, The electronic device includes a memory and a processor, wherein: The memory is used to store computer programs; When the processor executes the computer program stored in the memory, it implements the load recovery verification method based on power system reconfiguration as described in any one of claims 1-3.

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