Power distribution network substation fault full-stop real-time load transfer method, system and equipment and medium

Abstract

The invention discloses a power distribution network transformer substation fault full-stop real-time load transfer method, system and device and a medium. The method comprises the steps that the load capacity of each node of a power distribution network transformer substation is acquired; constructing an objective function and setting constraint conditions based on the obtained total load capacity of the transformer substation of the power distribution network; calculating the target function through an improved particle swarm algorithm to obtain a scheme fitness value, and selecting an optimal load transfer path based on the fitness value; and the selected optimal load transfer path is evaluated, and when a preset constraint condition is met, the load transfer path is adopted to carry out real-time load transfer under the condition that the transformer substation of the power distribution network is fully stopped due to faults. According to the method, the traditional particle swarm algorithm is improved by using the adaptive factor and the weight factor related to the learning factor in the improved particle swarm algorithm, so that the real-time performance of load transfer when the power distribution network substation is fully stopped due to the fault is improved, and the user loss is reduced; and automatic verification and instruction issuing can be realized, so that delay of a traditional manual operation chain is avoided.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power distribution network, and particularly relates to a power distribution network substation fault total outage real-time load transfer method, system, device and medium. BACKGROUND

[0002] The power distribution network substation fault total outage refers to a situation that all lines connected to the substation completely lose power supply due to various reasons such as substation busbar fault, transformer fault, DC power supply abnormality, circuit breaker refusal, external tie-line power failure, etc. The power distribution network substation fault total outage will cause great harm to power grid, public service, social economy and other aspects. In order to reduce the power supply recovery time of the power distribution network substation fault total outage, the prior art has proposed a method for real-time transfer of the related load of the total outage substation. For example, the patent document with the publication number CN116031874 executes an out-line power recovery program by acquiring main grid control system data and distribution network control system data and analyzing the structure of the low-voltage out-line line of the substation. However, the above method still needs to execute fault processing table updating, fault restoration judgment and other programs, and the power recovery is relatively long. The patent document with the publication number CN110137939 identifies the feeder path of the outage substation, then collects initialization calculation parameters and uses a genetic algorithm to solve the primary transfer process, finds the optimal primary transfer scheme, and verifies whether the primary transfer scheme meets the main transformer constraint condition. If the substation does not meet the main transformer constraint, the secondary transfer needs to be considered.

[0003] However, the above method depends on the genetic algorithm, and the convergence speed of the genetic algorithm is slow, and even there is no convergence. Therefore, the genetic algorithm cannot meet the real-time load transfer requirement. Although the convergence speed can be improved by adjusting the crossover and mutation probability, introducing heuristic algorithm, annealing algorithm and the like, the algorithm is complex, and sometimes the real-time requirement of load transfer cannot be met. SUMMARY

[0004] In view of the above existing problems, the present application is proposed.

[0005] Therefore, the present application provides a power distribution network substation fault total outage real-time load transfer method and system to solve the problems of low real-time performance and complex algorithm in the current power distribution network substation fault total outage load transfer.

[0006] To solve the above technical problems, the present application provides the following technical solutions.

[0007] In a first aspect, the present application provides a power distribution network substation fault total outage real-time load transfer method, comprising:

[0008] According to the topology structure of the power distribution network substation, the load of each node of the power distribution network substation is acquired.

[0009] Based on the obtained total load of the power distribution network substation, a target function is constructed and a constraint condition is set;

[0010] The target function is calculated by an improved particle swarm algorithm to obtain a scheme fitness value, and the optimal load transfer path is selected based on the fitness value;

[0011] The selected optimal load transfer path is evaluated, and when the preset constraint condition is met, the load transfer path is used for real-time load transfer under the condition of total stop of the power distribution network substation fault.

[0012] As a preferred scheme of the power distribution network substation fault full stop real-time load transfer method, wherein: based on the obtained total load of the power distribution network substation, a target function is constructed, including:

[0013] The target function is the transfer cost of the power distribution network substation node load;

[0014] The transfer cost is calculated by the transfer time of the power distribution network substation node load, the capacity of the power distribution network substation node load, the average electricity price of the power distribution network substation fault full stop period, and the transfer cost coefficient of the power distribution network substation node load.

[0015] As a preferred scheme of the power distribution network substation fault full stop real-time load transfer method, wherein: the constraint condition includes: the threshold range of the voltage of the power distribution network substation node, the capacity threshold range of the power distribution network substation node load, and the threshold range of the power angle change of the power distribution network substation node.

[0016] As a preferred scheme of the power distribution network substation fault full stop real-time load transfer method, wherein: the target function is calculated by an improved particle swarm algorithm to obtain a scheme fitness value, and the optimal load transfer path is selected based on the fitness value, including:

[0017] Initialize the candidate load transfer path scheme and the scheme adjustment step;

[0018] According to the target function and the constraint condition, the fitness value of each transfer path scheme is calculated;

[0019] Update the load transfer path scheme and the scheme adjustment step;

[0020] Determine whether the scheme falls into a local optimal solution;

[0021] When falling into a local optimal solution, randomly select a load transfer path again, and update the scheme position again using an adaptive factor; then return to the judgment and start again;

[0022] When the iteration number is not trapped in a local optimal solution, it is judged whether the maximum iteration number is reached, and the step of fitness value calculation is returned to start again when the maximum iteration number is not reached, until the iteration is stopped when the maximum iteration number is reached.

[0023] The scheme with the lowest fitness value is selected, and the selected load transfer path is output as the optimal load transfer path based on the scheme.

[0024] The beneficial effects of the preferred technical scheme are that the improved particle swarm algorithm is used to calculate the fitness value and select the optimal path to solve the multi-objective combination optimization problem under complex constraints, and the improved particle swarm algorithm searches through swarm intelligence and efficiently handles such non-convex and discrete optimization problems due to the complex constraints of the objective function.

[0025] As a preferred scheme of the power distribution network substation fault full-stop real-time load transfer method, the scheme whether trapped in a local optimal solution includes:

[0026] The scheme fitness value at M moment is obtained and recorded as the first scheme fitness value FIT1, the scheme fitness value at M+1 moment is obtained and recorded as the second scheme fitness value FIT2, and the scheme fitness value at M+TH moment is obtained and recorded as the TH+1 scheme fitness value FIT TH+1 The scheme fitness value change rate is calculated:

[0027]

[0028] Wherein, ΔFIT represents the scheme fitness value change rate, and TH represents the iteration threshold.

[0029] When the scheme fitness value change rate ΔFIT is less than the scheme fitness value reference change rate ΔFIT ref , it is judged that the scheme is trapped in a local optimal solution.

[0030] As a preferred scheme of the power distribution network substation fault full-stop real-time load transfer method, the iteration threshold TH is positively correlated with the total number N node of load nodes of the power distribution network substation and the total capacity of the node load of the power distribution network substation.

[0031] As a preferred scheme of the power distribution network substation fault full-stop real-time load transfer method, the evaluation of the selected optimal load transfer path includes:

[0032] When the optimal load transfer path needs to meet the main transformer constraint, the node power flow constraint, and the capacity constraint condition, it is considered to meet the load transfer requirement.

[0033] In a second aspect, the present application provides a power distribution network substation fault total stop real-time load transfer system, comprising:

[0034] An acquisition module is configured to acquire the load of each node of the power distribution network substation according to the topology of the power distribution network substation.

[0035] A construction module is configured to construct a target function and set a constraint condition based on the acquired total load of the power distribution network substation.

[0036] An optimization selection module is configured to select an optimal load transfer path for the target function by using an improved particle swarm algorithm.

[0037] An evaluation module is configured to evaluate the selected optimal load transfer path, and when the preset constraint condition is met, the load transfer path is used for real-time load transfer under the condition of the power distribution network substation fault total stop.

[0038] In a third aspect, the present application provides a computer device, comprising:

[0039] a memory and a processor;

[0040] The memory is configured to store computer executable instructions, and the processor is configured to execute the computer executable instructions, so as to implement the steps of the power distribution network substation fault total stop real-time load transfer method.

[0041] In a fourth aspect, the present application provides a computer readable storage medium, which stores computer executable instructions, and the computer executable instructions are executed by a processor to implement the steps of the power distribution network substation fault total stop real-time load transfer method.

[0042] Compared with the prior art, the present application has the following beneficial effects: the present application is based on real-time topology and load mapping, lays a foundation for fast data response, improves the traditional particle swarm algorithm by using the adaptive factor and the weight factor related to the learning factor in the improved particle swarm algorithm, accelerates the convergence speed of the particle swarm algorithm, can lock the optimal solution in the order of magnitude of path combination in seconds, is beneficial to improving the real-time performance of load transfer under the condition of power distribution network substation fault total stop, and reduces user loss; and can automatically check and issue instructions to avoid the delay of traditional manual operation chain. BRIEF DESCRIPTION OF DRAWINGS

[0043] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0044] Figure 1 The overall flowchart of the power distribution network substation fault full stop real-time load transfer method is shown in an embodiment of the present application.

[0045] Figure 2 The flowchart of selecting a load transfer path based on an improved particle swarm algorithm in the power distribution network substation fault full stop real-time load transfer method is shown in an embodiment of the present application.

[0046] Figure 3 The iterative convergence curve when a traditional particle swarm algorithm is used to solve the objective function in the power distribution network substation fault full stop real-time load transfer method is shown in an embodiment of the present application.

[0047] Figure 4 The iterative convergence curve when an improved particle swarm algorithm is used to solve the objective function in the power distribution network substation fault full stop real-time load transfer method is shown in an embodiment of the present application. DETAILED DESCRIPTION

[0048] In order to make the above objectives, characteristics and advantages of the present application more apparent, clear and easy to understand, the specific embodiments of the present application will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work should fall within the protection scope of the present application.

[0049] Embodiment 1, refer to Figure 1 In an embodiment of the present application, a power distribution network substation fault full stop real-time load transfer method is provided, comprising:

[0050] S100: According to the topology structure of the power distribution network substation, the load amount of each node of the power distribution network substation is obtained.

[0051] S200: Based on the obtained total load amount of the power distribution network substation, an objective function is constructed and a constraint condition is set.

[0052] S300: The objective function is calculated by an improved particle swarm algorithm to obtain a scheme fitness value, and the optimal load transfer path is selected based on the fitness value.

[0053] S400: The selected optimal load transfer path is evaluated, and when the preset constraint condition is met, the load transfer path is used for real-time load transfer under the power distribution network substation fault full stop condition.

[0054] It should be noted that the current model design often uses predefined rules or static strategies, such as based on historical case library, rather than dynamic optimization. Like operators need to manually input constraint parameters, each failure needs to recheck system diagram and rule base, which takes several seconds to minutes, is prone to error and low efficiency; for the objective function, simple heuristic or fixed weight target is often used, which cannot adjust the priority based on real-time load, and the model construction stage may need multiple iterations to meet new conditions, further slowing down the subsequent optimization; heuristic algorithm also has the problem of insufficient optimization parameters, which is easy to fall into local optimum or needs a lot of iterations, and the path selection process may need multiple simulation verification.

[0055] To solve the above problems, steps S100-S400 are provided to automatically generate a real-time transfer load scheme for a power distribution network substation fault full stop by improving the particle swarm algorithm.

[0056] Embodiment 2, refer to Figures 1-4 For an embodiment of the present application, based on the above embodiment, a power distribution network substation fault full stop real-time load transfer method is provided.

[0057] In the embodiment of the present application, in step S100, the load of each node of the power distribution network substation is obtained according to the topology structure of the power distribution network substation;

[0058] In an optional embodiment, the telemetry data of the substation, such as current, voltage and power, can be read in real time through the power distribution network SCADA, smart meter (AMI) and load forecasting system, and the node relationship can be automatically mapped based on the topology configuration file, and the load of each node can be calculated.

[0059] In another optional embodiment, the user-transformer-feeder ownership relationship can be obtained by combining user power information and power grid GIS topology, or combining with historical database, and the node load can be calculated by combining real-time total load data.

[0060] In the embodiment of the present application, in step S200, based on the obtained total load of the power distribution network substation, an objective function is constructed, including:

[0061] The objective function is the transfer cost of the node load of the power distribution network substation.

[0062] The transfer cost is calculated by the transfer time of the node load of the power distribution network substation, the capacity of the node load of the power distribution network substation, the average price of the power distribution network substation fault full stop period, and the transfer cost coefficient of the node load of the power distribution network substation.

[0063] Specifically, the objective function is specifically:

[0064]

[0065] wherein F represents a target function, n represents a substation load node number of a distribution network, N node represents a total number of substation load nodes of the distribution network, C n represents a transfer cost of the nth substation load node of the distribution network, T n represents a transfer time of the nth substation load node of the distribution network, P n represents a capacity of the nth substation load node of the distribution network, EP represents an average electricity price during a full outage period of the substation of the distribution network, K n represents a transfer cost coefficient of the nth substation load node of the distribution network;

[0066] It should be noted that the transfer cost is essentially converted into a cost proportional to the electricity price by using the electricity price to quantify the transfer cost, and therefore K n > 1.

[0067] In an optional embodiment, the target function can further include maximization of power supply reliability to shorten user outage time and improve system recovery efficiency.

[0068] In another optional embodiment, the target function can further include minimization of network loss to reduce line loss during the load transfer process, reduce operation cost, and improve the economy of the transfer scheme by calculating the transmission current, resistance, and load transfer duration.

[0069] In the embodiment of the application, the constraint conditions in step S200 include a threshold range of voltage of the substation node of the distribution network, a threshold range of capacity of the substation load node of the distribution network, and a threshold range of power angle variation of the substation node of the distribution network.

[0070] Specifically, the constraint conditions include:

[0071]

[0072] wherein V n represents the voltage of the nth substation node of the distribution network, V nmin represents a lower limit value of the voltage of the nth substation node of the distribution network, V nmax represents an upper limit value of the voltage of the nth substation node of the distribution network, P n represents the capacity of the nth substation load node of the distribution network, P nmin represents a lower limit value of the capacity of the nth substation load node of the distribution network, P nmax represents an upper limit value of the capacity of the nth substation load node of the distribution network, Δδ n represents the power angle variation of the nth substation node of the distribution network, δ nmaxPn represents the upper limit of the power angle change of the nth power distribution network substation node max Pn represents the upper limit of the transfer capacity.

[0073] In an optional embodiment, the constraint can further include a line current thermal stability limit constraint to prevent the line current from exceeding the conductor thermal stability limit after load transfer, thereby avoiding equipment overheating damage or causing arc fault.

[0074] In another optional embodiment, the constraint can further include a regional power supply margin constraint to ensure that the standby capacity of the target power supply region is sufficient to accommodate the new load after load transfer, thereby avoiding overload and triggering a chain failure.

[0075] It should be noted that the setting of step S200 is mainly to find the optimal load transfer path under the satisfaction of safety constraints, and therefore the applicant prefers the transfer cost of the power distribution network substation node load in the objective function. The fundamental goal of load transfer is to minimize user outage loss; it directly quantifies the power loss and economic compensation caused by load shedding, which corresponds to the core demand of power supply continuity; and it can set different cost weights for different levels of load, such as hospitals, residents, and industries, to embed power supply priority strategies and ensure that essential and important loads are transferred first; from the algorithmic point of view, the cost function is simple in form, which can reduce the complexity of the optimization problem and meet the minute-level time requirement of fault recovery.

[0076] In the embodiments of the present application, as shown in Figure 2 the step S300 calculates the scheme fitness value of the objective function by improving the particle swarm algorithm, and selects the optimal load transfer path based on the fitness value, including the following steps A1-A7:

[0077] A1: initialize the candidate load transfer path scheme and the scheme adjustment step;

[0078] that is, initialize the position and speed parameters of the particle swarm;

[0079] A2: calculate the fitness value of each transfer path scheme according to the objective function and the constraint;

[0080] A3: update the load transfer path scheme and the scheme adjustment step;

[0081] that is, update the speed and position of the particle; specifically, the speed of the particle can be updated as follows:

[0082]

[0083] wherein, vi(T+1) represents the speed of the particle i at T+1, Vi(T) represents the velocity of the particle i at the time T, K1 represents a first adjustment coefficient, K2 represents a second adjustment coefficient, L1 represents a first learning factor, L2 represents a second learning factor, r1 represents a first random factor, and r2 represents a second random factor, Xi(T) represents the position of the particle i at the time T, Xi(T) represents the current particle optimal position, Xi(T) represents the global optimal position;

[0084] It should be noted that the above-mentioned:

[0085]

[0086] That is, the weight factor related to the learning factors L1 and L2 can ensure the range of particle search after a single iteration, improve the efficiency of single search of particles, and thus improve the convergence speed of the particle swarm algorithm.

[0087] Updating the position of the particle includes:

[0088]

[0089] wherein, Xi(T) represents the position of the particle i at the time T, Xi(T+1) represents the position of the particle i at the time T+1.

[0090] A4: judging whether the scheme falls into a local optimal solution;

[0091] Further, judging whether the particle falls into a local optimal solution according to the change rate of the particle fitness value can avoid the judgment error caused by judging whether the particle falls into a local optimal solution only according to the size of the particle fitness value in the prior art.

[0092] In the embodiment of the application, judging whether the scheme falls into a local optimal solution in step S300 includes steps A4.1-A4.2:

[0093] A4.1: obtaining the scheme fitness value at the time M and recording it as a first scheme fitness value FIT1, obtaining the scheme fitness value at the time M+1 and recording it as a second scheme fitness value FIT2, and sequentially obtaining the scheme fitness value at the time M+TH and recording it as a TH+1 scheme fitness value FIT TH+1 , and calculating the scheme fitness value change rate:

[0094]

[0095] wherein, ΔFIT represents the scheme fitness value change rate, and TH represents an iteration threshold; the above-mentioned time M needs to ensure that the algorithm has performed a sufficient number of iterations to ensure the optimization effect.

[0096] A4.2: When the scheme fitness value change rate ΔFIT is less than the scheme fitness value reference change rate ΔFIT ref , then it is judged that the scheme falls into a local optimal solution.

[0097] In the embodiments of the present application, the iteration threshold TH in step S300 is positively correlated with the total number N of load nodes of the power distribution network substation and the total capacity of the load of the power distribution network substation. node

[0098] Specifically, the iteration threshold TH is determined according to the following formula:

[0099]

[0100] wherein α1 represents a first proportional coefficient, α2 represents a second proportional coefficient, N ref represents the load node reference value, P ref represents the load total capacity reference value, N node represents the total number of load nodes of the power distribution network substation, and P n represents the capacity of the nth load of the power distribution network substation.

[0101] It should be noted that the more the load nodes carried by the power distribution network substation, the greater the total capacity of the load, and the greater the value of the threshold TH.

[0102] A5: When falling into a local optimal solution, randomly reselecting a load transfer path and updating the scheme position again using an adaptive factor; then returning to the judgment (step A4) to start again;

[0103] Specifically, the particle position is updated again using an adaptive factor, which is represented as:

[0104]

[0105] wherein K3 represents a third adjustment coefficient, which is a random number greater than 1 and less than 2, K3×(M+TH) represents the adaptive factor, represents the position of the particle i at time T, represents the position of the particle i at time T+1, represents the speed of the particle i at time T+1.

[0106] A6: When not falling into a local optimal solution, judging whether the iteration number reaches the maximum iteration number, and returning to the step of calculating the fitness value (step A2) to start again when the maximum iteration number is not reached, until the iteration is stopped when the maximum iteration number is reached.

[0107] A7: Selecting the scheme with the lowest fitness value and outputting the selected load transfer path as the optimal load transfer path based on the scheme. ​

[0108] It should be noted that the improved particle swarm algorithm (IPSO) is selected to calculate the load transfer path fitness value and output the optimal scheme. Compared with other intelligent optimization algorithms, such as the standard particle swarm algorithm, the genetic algorithm, and the ant colony algorithm, the load transfer is a high-dimensional discrete combination optimization, the data nature is adaptive, and it has a parallel computing mechanism, the iteration number is small, and the convergence speed is fast; the inertia weight can be dynamically adjusted to avoid premature convergence of the genetic algorithm or falling into a local optimum of the ant colony algorithm.

[0109] In the embodiments of the present application, the selected optimal load transfer path is evaluated in step S400, including: when the optimal load transfer path needs to meet the main transformer constraint, the node power flow constraint, and the capacity constraint condition at the same time, it is considered that the load transfer requirement is met.

[0110] In an optional embodiment, the evaluation of the selected optimal load transfer path can also verify whether the voltage / frequency fluctuation at the load transfer moment is within the allowed range, to avoid secondary oscillation or collapse caused by switching operation. A simplified electromechanical transient model can be used to calculate the voltage mutation rate and frequency offset when the switching path is closed to judge whether it is within the threshold range.

[0111] In another optional embodiment, the evaluation of the selected optimal load transfer path can also include switching operation timing feasibility evaluation, establishment of a switching operation time matrix, such as circuit breaker opening for 200ms and load switch closing for 500ms, checking for timing conflicts, such as prohibiting closing the bus switch before the ground switch is opened, etc. If the interval between adjacent switching operations is less than a set threshold, such as 100ms, it is determined that the timing is not feasible, and the path is re-optimized.

[0112] It should be noted that the closed-loop verification of step S400 can ensure that the above overall scheme is actually operable and strictly controls safety risks; thereby finally realizing fast fault isolation and load lossless migration, minimizing user power loss, and improving the self-healing ability of the distribution network.

[0113] It should also be noted that since the objective function of the real-time load transfer when the distribution network substation fails to stop and the classical Ackley inverse function are both multi-valley functions, the Ackley inverse function is used as the objective function for simulation, and some parameters are set as follows: the first learning factor L1 and the second learning factor L2 are both 1.4, the random factors r1 and r2 are both greater than 1, the maximum iteration number is 200 times, K1=1, K2=2, α1=2, and α2=1.5. Figure 3 and Figure 4 The iterative convergence curves of the traditional particle swarm algorithm and the improved particle swarm algorithm of the present application for solving the objective function are shown, respectively. Figure 3The curve in the figure tends to converge after 42 iterations, while the curve in the figure tends to converge after 26 iterations Figure 4 The curve in the figure tends to converge after 42 iterations, while the curve in the figure tends to converge after 26 iterations It can be seen that the improved particle swarm algorithm of the present application converges relatively faster, is suitable for real-time load transfer of the power distribution network substation in the case of complete failure, can restore power supply to the load more quickly, and reduces user loss.

[0114] Embodiment 3, the above is a schematic scheme of a power distribution network substation complete failure real-time load transfer method. It should be noted that the technical scheme of the power distribution network substation complete failure real-time load transfer system belongs to the same concept as the technical scheme of the power distribution network substation complete failure real-time load transfer method described above. The technical scheme of the power distribution network substation complete failure real-time load transfer system in this embodiment is not described in detail. The details can be seen from the description of the technical scheme of the power distribution network substation complete failure real-time load transfer method described above.

[0115] The embodiment also provides another power distribution network substation complete failure real-time load transfer system, which comprises:

[0116] The acquisition module is configured to acquire the load of each node of the power distribution network substation according to the topology of the power distribution network substation;

[0117] The construction module is configured to construct a target function and set a constraint condition based on the obtained total load of the power distribution network substation;

[0118] The optimization selection module is configured to select an optimal load transfer path for the target function by using the improved particle swarm algorithm;

[0119] The evaluation module is configured to evaluate the selected optimal load transfer path, and adopt the load transfer path to perform real-time load transfer in the case of complete failure of the power distribution network substation when the preset constraint condition is met.

[0120] The embodiment also provides a computer device suitable for the case of power distribution network substation complete failure real-time load transfer, which comprises a memory and a processor; the memory is configured to store computer executable instructions, and the processor is configured to execute the computer executable instructions to realize the power distribution network substation complete failure real-time load transfer method proposed in the above embodiment.

[0121] The embodiment also provides a storage medium having a computer program stored thereon, and the program is executed by a processor to realize the power distribution network substation complete failure real-time load transfer method proposed in the above embodiment.

[0122] The storage medium proposed in the embodiment belongs to the same inventive concept as the method for realizing real-time transfer of load in the event of full stop of a power distribution network substation fault proposed in the above embodiment, and the technical details not described in the embodiment can be seen from the above embodiment, and the embodiment has the same beneficial effects as the above embodiment.

[0123] Through the above description of the embodiments, those skilled in the art can clearly understand that the present application can be realized by means of software and necessary universal hardware, and of course can also be realized by hardware. Based on such understanding, the technical solutions of the present application or the part that contributes to the prior art can be embodied in the form of a software product, which can be stored in a computer readable storage medium, such as a floppy disk, a read-only memory (ROM), a random access memory (RAM), a FLASH, a hard disk, or an optical disc, etc., and includes a number of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute the methods of various embodiments of the present application.

[0124] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present application and not to limit the present application, and although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or replaced by equivalents without departing from the spirit and scope of the present application, and they should be covered in the scope of the claims of the present application.

Claims

1. A method for real-time transfer of load in case of total failure of a power distribution network substation, characterized in that, The method comprises the following steps: According to the topology structure of the power distribution network substation, the load of each node of the power distribution network substation is obtained; Based on the total load of the power distribution network substation obtained, a target function is constructed and a constraint condition is set; The scheme fitness value of the target function is calculated by using the improved particle swarm algorithm, and the optimal load transfer path is selected based on the fitness value; The selected optimal load transfer path is evaluated, and when the preset constraint condition is met, the load transfer path is used for real-time load transfer under the condition of total stop of the power distribution network substation fault.

2. A method for real-time transfer of load in case of total failure of a substation of a power distribution network as claimed in claim 1 wherein, Based on the total load of the power distribution network substation obtained, a target function is constructed, which comprises: The target function is the transfer cost of the node load of the power distribution network substation; The transfer cost is calculated by the transfer time of the node load of the power distribution network substation, the capacity of the node load of the power distribution network substation, the average price during the total stop period of the power distribution network substation fault, and the transfer cost coefficient of the node load of the power distribution network substation.

3. A method for real-time transfer of load in case of total failure of a substation of a power distribution network as claimed in claim 2 wherein, The constraint condition comprises: the threshold range of the voltage of the node of the power distribution network substation, the threshold range of the capacity of the node load of the power distribution network substation, and the threshold range of the power angle change of the node of the power distribution network substation.

4. A method for real-time transfer of load in case of total failure of a substation of a power distribution network as claimed in claim 3 wherein, The scheme fitness value of the target function is calculated by using the improved particle swarm algorithm, and the optimal load transfer path is selected based on the fitness value, which comprises: Initialize the candidate load transfer path scheme and the scheme adjustment step; According to the target function and the constraint condition, the fitness value of each transfer path scheme is calculated; The load transfer path scheme and the scheme adjustment step are updated; Determine whether the scheme falls into a local optimal solution; When falling into a local optimal solution, randomly select a load transfer path again, and update the scheme position again by using an adaptive factor; then return to the judgment to start again; When not falling into a local optimal solution, determine whether the iteration number reaches the maximum iteration number, and return to step (a) to start again when the maximum iteration number is not reached, until the maximum iteration number is reached to stop iteration; Select the scheme with the lowest fitness value and output the selected load transfer path as the optimal load transfer path based on the scheme.

5. A method for real-time transfer of load in case of total failure of a substation of a power distribution network as claimed in claim 4 wherein, The determination of whether the scheme falls into a local optimal solution comprises: The scheme fitness value at the Mth moment is obtained and recorded as a first scheme fitness value FIT1, the scheme fitness value at the M+1th moment is obtained and recorded as a second scheme fitness value FIT2, and the like is sequentially continued until the scheme fitness value at the M+TH moment is obtained and recorded as a TH+1th scheme fitness value FIT TH+1 The scheme fitness value change rate is calculated: Wherein, ΔFIT represents the scheme fitness value change rate, and TH represents the iteration threshold; When the scheme fitness value change rate ΔFIT is less than the scheme fitness value reference change rate ΔFIT ref then it is judged that the scheme falls into a local optimal solution.

6. A method for real-time transfer of load in case of total failure of a substation of an electrical distribution network according to claim 5, characterized in that, The iteration threshold TH is positively correlated with the total number N of load nodes of the power distribution network substation node and the total capacity of the load of the power distribution network substation nodes.

7. A method for real-time transfer of load in the event of a grid substation fault blackout as claimed in claim 6, wherein, The selected optimal load transfer path is evaluated, which comprises: When the optimal load transfer path meets the main transformer constraint, the node power flow constraint, and the capacity constraint condition at the same time, it is considered that the load transfer requirement is met.

8. A power distribution network substation fault black-out real-time load transfer system applying the method according to any one of claims 1-7, characterized in that, The method comprises the following steps: An acquisition module is configured to obtain the load of each node of the power distribution network substation according to the topology structure of the power distribution network substation; A construction module is configured to construct a target function and set a constraint condition based on the total load of the power distribution network substation obtained; An optimization selection module is configured to select an optimal load transfer path by using the improved particle swarm algorithm on the target function; An evaluation module is configured to evaluate the selected optimal load transfer path, and when the preset constraint condition is met, the load transfer path is used for real-time load transfer under the condition of total stop of the power distribution network substation fault.

9. A computer device, comprising: The method comprises the following steps: A memory and a processor are provided. The memory is configured to store computer executable instructions, and the processor is configured to execute the computer executable instructions, and the computer executable instructions, when executed by the processor, implement the steps of the power distribution network substation fault total stop real-time transferred load method in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The memory is configured to store computer executable instructions, and the processor is configured to execute the computer executable instructions, and the computer executable instructions, when executed by the processor, implement the steps of the power distribution network substation fault total stop real-time transferred load method in any one of claims 1 to 7.

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