Optimal configuration method and device for neutral point fault current limiter of transformer
The optimization of fault current limiter configuration using a particle swarm algorithm addresses the challenges of high short-circuit currents and costs, ensuring transformer safety and grid stability.
Patent Information
- Application Number
- CN202410433328.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-04-11
- Publication Date
- 2025-07-15
AI Technical Summary
In the prior art, the configuration of the transformer neutral point fault current limiter is blind, resulting in insufficient current limit depth or excessive cost, affecting the safety of the transformer and the stability of the power grid.
By establishing a fitness function, combining the particle swarm algorithm to optimize the number and impedance value of the transformer neutral point fault current limiter to achieve optimal configuration, avoid the blindness of manual experience, and reduce the current limit cost.
It realizes the minimization of transformer damage in the event of short circuit failure, ensures the safe and stable operation of the power system, and reduces the cost of the power grid.
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Abstract
Description
Technical Field
[0001] This application belongs to the technical field of power grid optimization, and particularly relates to a method and device for optimizing the configuration of a neutral point fault current limiter for a transformer. Background Art
[0002] The short-circuit current withstand capacity of a transformer that has been in operation for a certain number of years is insufficiently designed in advance. Once a short-circuit fault occurs, the excessive short-circuit current will not only cause the rapid heating and temperature rise of the transformer winding, leading to a fire, but also generate huge stress inside the transformer, resulting in deformation or even damage of the transformer winding. To ensure the safety, stability, and reliability of the power grid and reduce the operating burden of power equipment, limiting the short-circuit current on the neutral point grounding wire of the transformer has become an urgent problem to be solved in power grid construction.
[0003] One current-limiting measure that can be considered is to connect a fault current limiter in series on the neutral point grounding wire of the transformer to limit the asymmetric short-circuit current, so that the short-circuit withstand capacity of the transformer and the breaking capacity of the circuit breaker can adapt to the system short-circuit level.
[0004] However, the reasonable configuration of the neutral point fault current limiter is restricted by various factors. If the current-limiting impedance value is too high, it will cause too high a neutral point overvoltage, break down the neutral point insulation, cause transformer faults, and it requires a large space position, high cost, and affects the operation of relay protection; if the current-limiting impedance value is too low, it will result in insufficient current-limiting depth, and the short-circuit current flowing through the transformer is still too high, and the problem of excessive short-circuit current is not solved. Similarly, if too many fault current limiters are configured at the neutral points of each transformer in the power grid, it will cause too high a cost and seriously affect the normal operation of relay protection; if not enough fault current limiters are configured at the neutral points of each transformer in the power grid, it will be difficult to ensure the safe operation of each transformer. Summary of the Invention
[0005] The embodiments of this application provide a method and device for optimizing the configuration of a neutral point fault current limiter for a transformer to solve the problem that the short-circuit current level of current power grid transformers is getting higher and the short-circuit current withstand capacity design of transformers is insufficient.
[0006] This application is implemented through the following technical solutions:
[0007] In a first aspect, the embodiments of this application provide a method for optimizing the configuration of a neutral point fault current limiter for a transformer, including:
[0008] Obtain the short-circuit current value of the over-standard node before transformer current limiting, the short-circuit current value of the over-standard node after transformer current limiting, the number of over-standard nodes on each side of the transformer, the number of neutral point grounding wires where the transformer can install a fault current limiter, the impedance value of each current limiter, and obtain the constraint conditions of the transformer.
[0009] Establish a fitness function based on the short-circuit current value of the over-standard nodes before transformer current limiting, the short-circuit current value of the over-standard nodes after transformer current limiting, the number of over-standard nodes on each side of the transformer, the number of neutral grounding wires of the transformer where fault current limiters can be installed, and the impedance values of each current limiter.
[0010] Based on the constraint conditions of the transformer, determine the upper limit of the number of installed fault current limiters and the value range of the impedance values of the current limiters.
[0011] Based on the upper limit of the number of installed fault current limiters and the value range of the impedance values of the current limiters, with the goal of minimizing the fitness function, solve for the number of installed fault current limiters, the installation locations of the fault current limiters, and the values of the impedance values of the current limiters through the particle swarm algorithm to obtain an optimized configuration plan.
[0012] Combined with the first aspect, in some possible implementation manners, establish a fitness function based on the short-circuit current value of the over-standard nodes before transformer current limiting, the short-circuit current value of the over-standard nodes after transformer current limiting, the number of over-standard nodes on each side of the transformer, the number of neutral grounding wires of the transformer where fault current limiters can be installed, and the impedance values of each current limiter, including:
[0013] Based on the short-circuit current value of the over-standard nodes before transformer current limiting, the short-circuit current value of the over-standard nodes after transformer current limiting, and the number of over-standard nodes on each side of the transformer, combined with the first formula, establish a first function; wherein, the first function characterizes the current limiting effect of the optimized configuration plan.
[0014] Based on the number of neutral grounding wires of the transformer where fault current limiters can be installed and the impedance values of each current limiter, combined with the second formula, establish a second function; wherein, the second function characterizes the current limiting economic cost of the optimized configuration plan.
[0015] Based on the first function, the second function, and the short-circuit current value of the over-standard nodes before transformer current limiting, combined with the third formula, establish a fitness function.
[0016] Combined with the first aspect, in some possible implementation manners, the first formula is:
[0017]
[0018] Wherein, f1 represents the first function, δ k represents the current limiting effect of the over-standard node k, I m represents the preset target value, I k ’ represents the short-circuit current of the over-standard node k after current limiting, and N represents the number of over-standard nodes on each side of the transformer.
[0019] Combined with the first aspect, in some possible implementation manners, the second formula is:
[0020]
[0021] Among them, f2 represents the second function, NFCL represents the number of neutral point grounding wires of the transformer that can install fault current limiters, and Z FCL (i) represents the impedance value of the i-th fault current limiter, and F FCL [Z FCL (i)] represents the cost of the i-th fault current limiter with an impedance value of Z FCL (i).
[0022] Combined with the first aspect, in some possible implementation manners, the third formula is:
[0023]
[0024] Among them, I k represents the short-circuit current value of the over-standard node k before current limiting, both w1 and w2 represent weight coefficients, and Z limit represents the constraint of the fault current limiter impedance value, and I limit represents the constraint of the fault current limiter current limiting effect. If both the fault current limiter impedance value constraint and the fault current limiter current limiting effect constraint meet the constraint conditions, then M = 0; otherwise, M = 5000.
[0025] Combined with the first aspect, in some possible implementation manners, based on the constraint conditions of the transformer, determine the upper limit of the number of installed fault current limiters and the value range of the current limiter impedance value, including:
[0026] Based on the constraint conditions of the transformer, obtain the insulation level of the transformer neutral point and the size of the spatial position where the fault current limiting can be installed.
[0027] Based on the insulation level of the transformer neutral point and the size of the spatial position where the fault current limiting can be installed, determine the upper limit of the number of installed fault current limiters and the value range of the current limiter impedance value.
[0028] Combined with the first aspect, in some possible implementation manners, based on the upper limit of the number of installed fault current limiters and the value range of the current limiter impedance value, with the goal of minimizing the fitness function, solve the number of installed fault current limiters, the installation position of the fault current limiter, and the value of the current limiter impedance value through the particle swarm algorithm, and obtain the optimized configuration scheme, including:
[0029] Initialize the algorithm parameters of the particle swarm algorithm. The positions of the initial particles are randomly and uniformly distributed. The dimension of the initial particle swarm is 2. Number each initial particle, and set the number of installed fault current limiters to 1.
[0030] Combined with the fitness function, calculate the fitness of each particle.
[0031] Combined with the fourth formula, calculate the gravitational constant.
[0032] Combine with the fifth formula to calculate the inertial mass of each particle.
[0033] Based on the gravitational constant and the inertial mass of each particle, combine with the sixth formula to calculate the resultant force on each particle.
[0034] Based on the resultant force on each particle and the inertial mass of each particle, combine with the seventh formula to calculate the acceleration of each particle.
[0035] Combine with the eighth formula to calculate the inertia coefficient.
[0036] Based on the inertia coefficient, the acceleration of each particle, and the number of each particle, combine with the ninth formula to update the velocity of each particle.
[0037] Based on the velocity of each particle, update the position of each particle, calculate the fitness of each particle after the updated position, determine the optimal particle and the worst particle, and update the worst particle based on the number of each particle.
[0038] Judge whether the number of installed fault current limiters reaches the upper limit of the number of installed fault current limiters at this time.
[0039] If the upper limit of the number of installed fault current limiters is reached, obtain the optimized configuration scheme according to the position of the optimal particle.
[0040] If the upper limit of the number of installed fault current limiters is not reached, increment the number of installed fault current limiters by one, and return to the step of calculating the fitness of each particle in combination with the fitness function.
[0041] In combination with the first aspect, in some possible implementation manners, the process of updating the worst particle based on the number of each particle includes:
[0042] Randomly generate a position value of a particle. If the randomly generated position value of the particle is less than the preset value, replace the position value of the worst particle with the randomly generated position value of the particle.
[0043] If the randomly generated position value of the particle is greater than or equal to the preset value, obtain the number of the worst particle, and replace the position value of the worst particle with the average value of the position values of the particles before the number of the worst particle, thus completing the update of the worst particle.
[0044] In combination with the first aspect, in some possible implementation manners, the fourth formula is;
[0045]
[0046] Wherein, G(t) represents the gravitational constant at the t-th iteration, t represents the current iteration number, and S represents the maximum iteration number.
[0047] The fifth formula is:
[0048]
[0049] Among them, M i (t) represents the inertial mass of particle i at the t-th iteration, value i (t) represents the fitness value of particle i at the t-th iteration, best(t) represents the maximum value of the fitness value at the t-th iteration, and worst(t) represents the minimum value of the fitness value at the t-th iteration.
[0050] The sixth formula is:
[0051]
[0052] Among them, F i d (t) represents the resultant force on particle i, rand x represents the random number of the x-th particle in the set of particles containing the top member, rand x takes a random number within [0, 1], nbest represents the set of particles containing the top member, n represents the total number of particles in the set of particles containing the top member, represents the force between particle i and particle j at the t-th iteration in the d-th dimension, R ij (t) represents the Euclidean distance between particle i and particle j at the t-th iteration, ε represents a minimum value, represents the position of particle i at the t-th iteration in the d-th dimension, represents the position of particle j at the t-th iteration in the d-th dimension, M i (t) represents the inertial mass of particle i at the t-th iteration, M j (t) represents the inertial mass of particle j at the t-th iteration, np represents the number represented by the particle, and Cp is a fixed preset parameter value.
[0053] The seventh formula is:
[0054]
[0055] Among them, represents the acceleration of particle i at the t-th iteration in the d-th dimension;
[0056] The eighth formula is:
[0057]
[0058] Among them, ω represents the inertia coefficient, ω max represents the maximum value of the inertia factor, ω min represents the minimum value of the inertia factor.
[0059] The ninth formula is as follows:
[0060]
[0061] where V i d (t + 1) represents the velocity of particle i at the (t + 1)-th iteration in dimension d, and V i d (t) is the velocity of particle i at the t-th iteration in dimension d, the position of particle i at the t-th iteration in dimension d, H represents a random number within [0, 1], represents the position of the first particle alpha before particle i in dimension d, represents the position of the second particle beta before particle i in dimension d, represents the position of the third particle delta before particle i in dimension d.
[0062] The calculation formula for the preset value is as follows:
[0063]
[0064] where C set represents the preset value.
[0065] In a second aspect, an embodiment of the present application provides an optimized configuration device for a transformer neutral point fault current limiter, including:
[0066] A data acquisition module, configured to acquire the short-circuit current value of the over-standard node before transformer current limiting, the short-circuit current value of the over-standard node after transformer current limiting, the number of over-standard nodes on each side of the transformer, the number of neutral point grounding wires where the fault current limiter can be installed on the transformer, the impedance value of each current limiter, and acquire the constraint conditions of the transformer.
[0067] A function calculation module, configured to establish a fitness function based on the short-circuit current value of the over-standard node before transformer current limiting, the short-circuit current value of the over-standard node after transformer current limiting, the number of over-standard nodes on each side of the transformer, the number of neutral point grounding wires where the fault current limiter can be installed on the transformer, and the impedance value of each current limiter.
[0068] A condition restriction module, configured to determine the upper limit of the number of installed fault current limiters and the value range of the impedance value of the current limiter based on the constraint conditions of the transformer.
[0069] A result output module, configured to obtain an optimized configuration scheme by solving the number of installed fault current limiters, the installation position of the fault current limiter, and the value range of the impedance value of the current limiter based on the upper limit of the number of installed fault current limiters and the value range of the impedance value of the current limiter, with the minimum fitness function as the goal, through the particle swarm algorithm.
[0070] It can be understood that for the beneficial effects of the second aspect above, reference can be made to the relevant descriptions in the first aspect above, and details will not be elaborated here.
[0071] The beneficial effects of the embodiments of the present application compared with the prior art are as follows:
[0072] In the present application, a fitness function with the best current-limiting effect and the lowest current-limiting cost as the goal is established through the parameters of the transformer, and the optimal optimization configuration scheme is solved through the particle swarm algorithm, avoiding the blindness of configuring the neutral point fault current limiter of the transformer solely based on manual experience. While achieving a large current-limiting depth, the current-limiting cost is reduced as much as possible, realizing its optimal configuration. When a short-circuit fault occurs, the damage to the transformer can be minimized to the greatest extent, contributing to the safe and stable operation of the power system. At the same time, the grid operation cost is reduced, providing strong technical support for the safe and reliable operation of transformer equipment.
[0073] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit this specification. BRIEF DESCRIPTION OF THE DRAWINGS
[0074] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.
[0075] Figure 1 is a flowchart of an optimization configuration method for a neutral point fault current limiter of a transformer provided by an embodiment of the present application;
[0076] Figure 2 is a flowchart of an optimization configuration method for a fault current limiter provided by an embodiment of the present application;
[0077] Figure 3 is a particle coding diagram provided by an embodiment of the present application;
[0078] Figure 4 is a flowchart of solving an optimization configuration scheme provided by an embodiment of the present application;
[0079] Figure 5 is a structural diagram of an optimization configuration device for a neutral point fault current limiter of a transformer provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS
[0080] In the following description, specific details such as specific system architectures and technologies are presented for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, those skilled in the art should clearly understand that the present application can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid unnecessary details from interfering with the description of the present application.
[0081] It should be understood that when used in the specification and appended claims of the present application, the term "comprising" indicates the presence of the described features, wholes, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.
[0082] It should also be understood that the term "and / or" as used in the specification and appended claims of the present application refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.
[0083] As used in the specification and appended claims of the present application, the term "if" can be interpreted as "when", "once", "in response to determining", or "in response to detecting" depending on the context. Similarly, the phrase "if determined" or "if [the described condition or event] is detected" can be interpreted as meaning "once determined", "in response to determining", "once [the described condition or event] is detected", or "in response to detecting [the described condition or event]" depending on the context.
[0084] In addition, in the description of the specification and appended claims of the present application, the terms "first", "second", "third", etc. are only used for distinguishing descriptions and cannot be understood as indicating or implying relative importance.
[0085] The reference to "one embodiment" or "some embodiments" etc. described in the specification of the present application means that a specific feature, structure, or characteristic described in connection with that embodiment is included in one or more embodiments of the present application. Thus, statements such as "in one embodiment", "in some embodiments", "in other some embodiments", "in still other embodiments", etc. that appear in different places in this specification do not necessarily all refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in another way. The terms "including", "comprising", "having", and their variants all mean "including but not limited to", unless otherwise specifically emphasized in another way.
[0086] The reasonable configuration of the neutral point fault current limiter is restricted by various factors. If the current limiting impedance value is too high, it will lead to too high overvoltage at the neutral point, breakdown of the neutral point insulation, causing transformer faults, and it requires a large space position, high cost and affects the operation of relay protection; if the current limiting impedance value is too low, it will lead to insufficient current limiting depth, and the short-circuit current flowing through the transformer is still too high, and the problem of too high short-circuit current is not solved. Similarly, if too many fault current limiters are configured at the neutral points of each transformer in the power grid, it will lead to too high cost and seriously affect the normal operation of relay protection; if sufficient fault current limiters are not configured at the neutral points of each transformer in the power grid, it will be difficult to ensure the safe operation of each transformer.
[0087] Based on the above problems, the embodiment of the present application provides an optimal configuration method for the neutral point fault current limiter of the transformer. By means of algorithm optimization, the optimal optimization configuration scheme is solved, avoiding the blindness of configuring the neutral point fault current limiter of the transformer only based on manual experience. While achieving a large current limiting depth, the current limiting cost is reduced as much as possible, and its optimal configuration is realized.
[0088] Figure 1 It is a schematic flowchart of the optimal configuration method for the neutral point fault current limiter of the transformer provided by an embodiment of the present application. Referring to Figure 1 , the detailed description of the optimal configuration method for the neutral point fault current limiter of the transformer is as follows:
[0089] Step 101, obtain the short-circuit current value of the over-standard node before transformer current limiting, the short-circuit current value of the over-standard node after transformer current limiting, the number of over-standard nodes on each side of the transformer, the number of neutral point grounding wires where the transformer can install the fault current limiter, the impedance value of each current limiter, and obtain the constraint conditions of the transformer.
[0090] Specifically, each side of the transformer refers to the high-voltage side, medium-voltage side and low-voltage side of the transformer. The high-voltage side of the transformer usually refers to the side connected to the high-voltage line of the power system. High voltage usually refers to a higher voltage level, such as 110 kV, 220 kV, etc. The low-voltage side of the transformer is the side connected to the low-voltage line of the power system. Low voltage usually refers to a lower voltage level, such as 10 kV, 35 kV, etc. The voltage of the medium-voltage side of the transformer is between the high-voltage side and the low-voltage side. For example: a transformer with a voltage level of 500 kV: generally consists of three sets of winding voltage levels of 500 kV high-voltage side, 220 kV medium-voltage side, and 35 kV low-voltage side. The neutral point of the transformer is located on the medium-voltage side.
[0091] Step 102, based on the short-circuit current value of the over-standard node before transformer current limiting, the short-circuit current value of the over-standard node after transformer current limiting, the number of over-standard nodes on each side of the transformer, the number of neutral point grounding wires where the transformer can install the fault current limiter, and the impedance value of each current limiter, establish a fitness function.
[0092] Exemplarily, step 102 may include:
[0093] Based on the short-circuit current value of the over-standard node before transformer current limiting, the short-circuit current value of the over-standard node after transformer current limiting, and the number of over-standard nodes on each side of the transformer, a first function is established in combination with the first formula; wherein, the first function represents the current limiting effect of the optimized configuration scheme.
[0094] Based on the number of neutral point grounding wires of the transformer where the fault current limiter can be installed and the impedance values of each current limiter, a second function is established in combination with the second formula; wherein, the second function represents the current limiting economic cost of the optimized configuration scheme.
[0095] Based on the first function, the second function, and the short-circuit current value of the over-standard node before transformer current limiting, a fitness function is established in combination with the third formula.
[0096] Specifically, the first function represents the current limiting effect of the optimized configuration scheme, that is, during asymmetric short circuit, after the fault current limiter is connected, the short-circuit current levels of the over-standard nodes on each side of the transformer should be lower than the preset target value.
[0097] Specifically, the second function represents the current limiting economic cost of the optimized configuration scheme, and the relevant variables include the number of fault current limiters, the impedance values of the fault current limiters, and the total load loss. Since the working time of the fault current limiter is usually less than 4 s and the load loss approaches zero, the influence of the load loss is ignored, and only the number of fault current limiters and the impedance values of the fault current limiters are considered.
[0098] Exemplarily, the first formula may be:
[0099]
[0100] wherein, f1 represents the first function, δ k represents the current limiting effect of the over-standard node k, I m represents the preset target value, I k ’ represents the short-circuit current of the over-standard node k after current limiting, and N represents the number of over-standard nodes on each side of the transformer.
[0101] Exemplarily, the second formula may be:
[0102]
[0103] wherein, f2 represents the second function, NFCL represents the number of neutral point grounding wires of the transformer where the fault current limiter can be installed, Z FCL (i) represents the impedance value of the i-th fault current limiter, F FCL [Z FCL (i)] represents the cost of the i-th fault current limiter with the impedance value of Z FCL (i).
[0104] Exemplarily, the third formula may be:
[0105]
[0106] Wherein, I k represents the short - circuit current value of the over - standard node k before current limiting, w1 and w2 both represent weight coefficients, Z limit represents the impedance value constraint of the fault current limiter, I limit represents the current - limiting effect constraint of the fault current limiter. If both the impedance value constraint of the fault current limiter and the current - limiting effect constraint of the fault current limiter meet the constraint conditions, then M = 0; otherwise, M = 5000.
[0107] Step 103: Based on the constraint conditions of the transformer, determine the upper limit of the number of installed fault current limiters and the value range of the impedance value of the current limiter.
[0108] Exemplarily, step 103 may include:
[0109] Based on the constraint conditions of the transformer, obtain the insulation level of the transformer neutral point and the size of the spatial position where the fault current limiting can be installed.
[0110] Based on the insulation level of the transformer neutral point and the size of the spatial position where the fault current limiting can be installed, determine the upper limit of the number of installed fault current limiters and the value range of the impedance value of the current limiter.
[0111] Specifically, if the maximum value of the impedance value of the current limiter is too large, it may cause the over - voltage of the neutral point to exceed its insulation level and the equipment volume to be too large. Therefore, it is necessary to limit the maximum value of the impedance value of the current limiter according to the insulation level of the transformer neutral point and the size of the spatial position where the fault current limiting can be installed. At the same time, due to the limited number of grounding wires at the transformer center point (related to the size of the spatial position where the fault current limiting can be installed), there is also an upper limit to the number of installed fault current limiters.
[0112] Step 104: Based on the upper limit of the number of installed fault current limiters and the value range of the impedance value of the current limiter, with the goal of minimizing the fitness function, solve the number of installed fault current limiters, the installation position of the fault current limiter, and the value of the impedance value of the current limiter through the particle swarm algorithm to obtain the optimal configuration scheme.
[0113] Exemplarily, step 104 may include:
[0114] Initialize the algorithm parameters of the particle swarm algorithm. The positions of the initial particles are randomly and uniformly distributed. The dimension of the initial particle swarm is 2. Number each initial particle and set the number of installed fault current limiters to 1.
[0115] Combine with the fitness function to calculate the fitness of each particle.
[0116] Combine with the fourth formula to calculate the gravitational constant.
[0117] Combine with the fifth formula to calculate the inertial mass of each particle.
[0118] Based on the gravitational constant and the inertial mass of each particle, combine with the sixth formula to calculate the resultant force on each particle.
[0119] Based on the resultant force on each particle and the inertial mass of each particle, combine with the seventh formula to calculate the acceleration of each particle.
[0120] Combine with the eighth formula to calculate the inertia coefficient.
[0121] Based on the inertia coefficient, the acceleration of each particle, and the number of each particle, combine with the ninth formula to update the velocity of each particle.
[0122] Based on the velocity of each particle, update the position of each particle, calculate the fitness of each particle after updating the position, determine the optimal particle and the worst particle, and update the worst particle based on the number of each particle.
[0123] Judge whether the number of installed fault current limiters reaches the upper limit of the number of installed fault current limiters at this time.
[0124] If the upper limit of the number of installed fault current limiters is reached, obtain the optimized configuration scheme according to the position of the optimal particle.
[0125] If the upper limit of the number of installed fault current limiters is not reached, increase the number of installed fault current limiters by one, and return to the step of calculating the fitness of each particle by combining with the fitness function.
[0126] Exemplarily, the process of updating the worst particle based on the number of each particle includes:
[0127] Randomly generate a position value of a particle. If the randomly generated position value of the particle is less than the preset value, replace the position value of the worst particle with the randomly generated position value of the particle.
[0128] If the randomly generated position value of the particle is greater than or equal to the preset value, obtain the number of the worst particle, and use the mean value of the position values of the particles before the number of the worst particle to replace the position value of the worst particle to complete the update of the worst particle.
[0129] Specifically, in the particle swarm algorithm, each particle in the constructed D-dimensional search space represents a possible solution to the optimization problem. The initial particles are randomly generated by a uniform distribution. At the t-th iteration in the d dimension, the motion state of particle i is represented by the position and the velocity V i d (t).
[0130]
[0131]
[0132] According to the particle swarm optimization algorithm, at the t-th iteration, the position of the particle can be calculated according to the following equation
[0133]
[0134] In order to improve the algorithm efficiency, the basic PSO algorithm is improved.
[0135] According to the gravitational search algorithm, the particle velocity can be calculated from the velocity and acceleration obtained in the previous iteration of the particle.
[0136]
[0137] where V i d (t) is the velocity of particle i in dimension d at iteration t; is the acceleration of particle i in dimension d at iteration t.
[0138] After introducing the particle swarm optimization algorithm to improve the gravitational search algorithm, the velocity calculation formula is as follows:
[0139]
[0140] In order to improve the local search ability of the algorithm of this scheme, therefore, the positions of the previous three particles of particle i and are used to replace the global optimal position The obtained velocity update formula is as follows:
[0141]
[0142] where V i d (t + 1) represents the velocity of particle i at the (t + 1)-th iteration in dimension d, V i d (t) is the velocity of particle i at the t-th iteration in dimension d, ω represents the inertia coefficient, represents the acceleration of particle i at the t-th iteration in dimension d, and H represents a random number within [0, 1].
[0143] Exemplarily, the fourth formula can be;
[0144]
[0145] Among them, G(t) represents the gravitational constant at the t-th iteration, t represents the current iteration number, and S represents the maximum number of iterations.
[0146] The fifth formula can be:
[0147]
[0148] Among them, M i (t) represents the inertial mass of particle i at the t-th iteration, value i (t) represents the fitness value of particle i at the t-th iteration, best(t) represents the maximum value of the fitness value at the t-th iteration, and worst(t) represents the minimum value of the fitness value at the t-th iteration.
[0149] The sixth formula can be:
[0150]
[0151] Among them, F i d (t) represents the resultant force on particle i, rand x represents the random number of the x-th particle in the set of particles containing the top members, rand x takes a random number within [0, 1], nbest represents the set of particles containing the top members, n represents the total number of particles in the set of particles containing the top members, represents the force between particle i and particle j at the t-th iteration in the d dimension, R ij (t) represents the Euclidean distance between particle i and particle j at the t-th iteration, ε represents a minimum value, approaching 0, and for the convenience of calculation, the value of ε here is 0, represents the position of particle i at the t-th iteration in the d dimension, represents the position of particle j at the t-th iteration in the d dimension, M i (t) represents the inertial mass of particle i at the t-th iteration, M j (t) represents the inertial mass of particle j at the t-th iteration, np represents the number represented by the particle, and Cp is a fixed preset parameter value.
[0152] The seventh formula can be:
[0153]
[0154] Among them, represents the acceleration of particle i at the t-th iteration in the d dimension;
[0155] The eighth formula can be:
[0156]
[0157] Among them, ω represents the inertia coefficient, ω max represents the maximum value of the inertia factor, ω min represents the minimum value of the inertia factor.
[0158] The ninth formula can be:
[0159]
[0160] Among them, V i d (t + 1) represents the velocity of particle i at the (t + 1)-th iteration in dimension d, V i d (t) is the velocity of particle i at the t-th iteration in dimension d, the position of particle i at the t-th iteration in dimension d, H represents a random number within [0, 1], represents the position of the first particle alpha before particle i in dimension d, represents the position of the second particle beta before particle i in dimension d, represents the position of the third particle delta before particle i in dimension d.
[0161] Specifically, the formula for calculating the velocity of the updated particle incorporates the gravitational search algorithm. When a fault occurs at the neutral point of the transformer, its strong global search ability can find the optimal solution in the entire search space, and it is crucial to quickly find the optimal fault current limiter configuration to reduce damage. In addition, the global optimal position of the particle is updated using the previous three particles of the particle, incorporating the idea of the grey wolf optimization algorithm, which improves the local search ability, can deeply explore the solution space, realizes the organic combination of global and local searches, and thus finds the optimal solution.
[0162] The calculation formula for the preset value can be:
[0163]
[0164] Among them, C set represents the preset value.
[0165] Specifically, the particle swarm algorithm, the gravitational search algorithm, and the grey wolf optimization algorithm all possess high flexibility and adaptability, and can be flexibly adjusted according to the problem characteristics and parameter settings. When optimizing the configuration of the neutral point fault current limiter of the transformer, this characteristic helps to better adapt to different fault conditions and operating conditions. At the same time, the combination of multiple algorithms makes the method highly adaptable and robust, and can meet the requirements under different environments. This characteristic makes the method more reliable and can give a more reasonable optimization configuration plan.
[0166] The above-mentioned optimization configuration method for the neutral point fault current limiter of the transformer establishes a fitness function with the best current limiting effect and the minimum current limiting cost through the parameters of the transformer, and solves the optimal optimization configuration scheme through the particle swarm algorithm, avoiding the blindness of configuring the neutral point fault current limiter of the transformer solely based on manual experience. While achieving a large current limiting depth, it minimizes the current limiting cost as much as possible and realizes its optimal configuration. When a short-circuit fault occurs, it can minimize the damage to the transformer to the greatest extent, contribute to the safe and stable operation of the power system, reduce the grid operation cost at the same time, and provide strong technical support for the safe and reliable operation of the transformer equipment.
[0167] For the convenience of understanding, the present application provides another specific embodiment, and the process of obtaining the optimal configuration is as Figure 2 shown and is described in detail as follows:
[0168] Step 1: Construct a mathematical model for the optimal configuration of the FCL, analyze the characteristics of the solutions in the established mathematical model for the optimal configuration, and encode the particles accordingly according to the on-site installation requirements, so that the solutions to the problem are mapped into a unified mathematical space. There is no strict limit on the encoding of the particles for the optimal configuration of the fault current limiter, and its solutions include whether to install a fault current limiter at the neutral point of each side of each transformer and the impedance value of the current limiting reactor; mathematically, it can be expressed by 0, 1, and real number encoding to ensure that no illegal solutions are generated during the update and iteration process of the particles.
[0169] The particle encoding process is as Figure 3 shown. N is the number of neutral points of the transformer where the fault current limiter can be installed. The first part is M, the neutral points of the transformer candidates for installing the fault current limiter, and each element represents whether to install the fault current limiter; the second part is the current limiting impedance value, and its spatial size is the same as that of the first part.
[0170] Step 2: Define the system constraints. Statistically analyze factors such as the over-standard nodes and current limiting requirements in the system, the insulation level of the transformer neutral point, and the spatial position size where the fault current limiter can be installed, and determine the upper limit of the number of installed fault current limiters and the reasonable value range of the impedance value of the fault current limiter.
[0171] Step 3: Use the method of this solution to solve the optimization configuration scheme of the neutral point fault current limiter of the transformer.
[0172] Further, in step 3, as Figure 4 shown, it specifically includes:
[0173] 1. Initialize the algorithm parameters, such as: ω max 、ω min 、S, the number of FCL installation platforms (the number of installed fault current limiters) m, m = 1, etc., and the initial particles are randomly and uniformly distributed.
[0174] 2. Calculate and update the fitness of each particle at the current iteration number.
[0175] 3. Calculate the gravitational constant G(t) at iteration number t, and simultaneously determine the best fitness best(t) and the worst fitness worst(t) at this time.
[0176] 4. Calculate and update all the forces F i d (t) acting on each particle at iteration number t.
[0177] 5. Calculate the inertial mass M i (t) of each particle at iteration number t.
[0178] 6. Calculate and update the acceleration of each particle at iteration number t
[0179] 7. Calculate and update the inertial coefficient ω at iteration number t.
[0180] 8. Calculate and update the velocity V i d (t) and position
[0181] 9. Determine the worst particle in this iteration, and replace the worst particle with a better particle.
[0182] 10. If the maximum number of fault current limiter installation platforms N (m = N) is reached, end the calculation and output the optimal configuration plan; otherwise, m = m + 1, and return to step 2.
[0183] Further, in step 9, after evaluating the particles and determining the worst particle, it is necessary to replace it with a new or improved particle. After determining the worst particle, a random value is generated, called the gamma particle. If the generated random value is less than the preset value then replace the gamma particle value with the new value. Otherwise, it is replaced by the average value of the previous 3 particles and of particle i.
[0184] Figure 5 Fig. shows the structural schematic diagram of the transformer neutral point fault current limiter optimal configuration device provided by the embodiment of the present invention. For the sake of convenience of description, only the parts related to the embodiment of the present invention are shown and are described in detail as follows:
[0185] As Figure 5 shown, the transformer neutral point fault current limiter optimal configuration device includes:
[0186] The data acquisition module 201 is used to acquire the short-circuit current value of the over-standard nodes before the transformer current limiting, the short-circuit current value of the over-standard nodes after the transformer current limiting, the number of over-standard nodes on each side of the transformer, the number of neutral point grounding wires where the fault current limiter can be installed on the transformer, the impedance value of each current limiter, and acquire the constraint conditions of the transformer.
[0187] The function calculation module 202 is used to establish a fitness function based on the short-circuit current value of the over-standard nodes before the transformer current limiting, the short-circuit current value of the over-standard nodes after the transformer current limiting, the number of over-standard nodes on each side of the transformer, the number of neutral point grounding wires where the fault current limiter can be installed on the transformer, and the impedance value of each current limiter.
[0188] The condition limiting module 203 is used to determine the upper limit of the number of installed fault current limiters and the value range of the impedance value of the current limiter based on the constraint conditions of the transformer.
[0189] The result output module 204 is used to obtain the optimized configuration scheme by solving the number of installed fault current limiters, the installation position of the fault current limiter, and the value of the impedance value of the current limiter through the particle swarm algorithm with the goal of minimizing the fitness function based on the upper limit of the number of installed fault current limiters and the value range of the impedance value of the current limiter.
[0190] Exemplarily, the function calculation module 202 can be used for:
[0191] Based on the short-circuit current value of the over-standard nodes before the transformer current limiting, the short-circuit current value of the over-standard nodes after the transformer current limiting, and the number of over-standard nodes on each side of the transformer, combined with the first formula, establish the first function; wherein, the first function represents the current limiting effect of the optimized configuration scheme.
[0192] Based on the number of neutral point grounding wires where the fault current limiter can be installed on the transformer and the impedance value of each current limiter, combined with the second formula, establish the second function; wherein, the second function represents the current limiting economic cost of the optimized configuration scheme.
[0193] Based on the first function, the second function, and the short-circuit current value of the over-standard nodes before the transformer current limiting, combined with the third formula, establish the fitness function.
[0194] Exemplarily, the first formula can be:
[0195]
[0196] Wherein, f1 represents the first function, δ k represents the current limiting effect of the over-standard node k, I m represents the preset target value, I k ’ represents the short-circuit current of the over-standard node k after current limiting, and N represents the number of over-standard nodes on each side of the transformer.
[0197] Exemplarily, the second formula can be:
[0198]
[0199] where f2 represents the second function, NFCL represents the number of neutral point ground wires of the transformer where the fault current limiter can be installed, Z FCL (i) represents the impedance value of the i-th fault current limiter, and F FCL [Z FCL (i)] represents the cost of the i-th fault current limiter with the impedance value Z FCL (i).
[0200] Exemplarily, the third formula can be:
[0201]
[0202] where I k represents the short-circuit current value of the over-standard node k before current limiting, both w1 and w2 represent weight coefficients, Z limit represents the constraint of the fault current limiter impedance value, and I limit represents the constraint of the fault current limiter current limiting effect. If both the fault current limiter impedance value constraint and the fault current limiter current limiting effect constraint satisfy the constraint conditions, then M = 0; otherwise, M = 5000.
[0203] Exemplarily, the condition restriction module 203 can be used to:
[0204] Based on the constraint conditions of the transformer, obtain the insulation level of the transformer neutral point and the size of the spatial position where the fault current limiter can be installed.
[0205] Based on the insulation level of the transformer neutral point and the size of the spatial position where the fault current limiter can be installed, determine the upper limit of the number of installed fault current limiters and the value range of the limiter impedance value.
[0206] Exemplarily, the result output module 204 can be used to:
[0207] Initialize the algorithm parameters of the particle swarm algorithm. The positions of the initial particles are randomly and uniformly distributed. The dimension of the initial particle swarm is 2. Number each initial particle and set the number of installed fault current limiters to 1.
[0208] Combine with the fitness function to calculate the fitness of each particle.
[0209] Combine with the fourth formula to calculate the gravitational constant.
[0210] Combine with the fifth formula to calculate the inertial mass of each particle.
[0211] Based on the gravitational constant and the inertial mass of each particle, combine with the sixth formula to calculate the resultant force received by each particle.
[0212] Based on the resultant force received by each particle and the inertial mass of each particle, combined with the seventh formula, calculate the acceleration of each particle.
[0213] Combined with the eighth formula, calculate the inertia coefficient.
[0214] Based on the inertia coefficient, the acceleration of each particle, and the number of each particle, combined with the ninth formula, update the velocity of each particle.
[0215] Based on the velocity of each particle, update the position of each particle, calculate the fitness of each particle after the position update, determine the optimal particle and the worst particle, and update the worst particle based on the number of each particle.
[0216] Judge whether the number of installed fault current limiters reaches the upper limit of the number of installed fault current limiters at this time.
[0217] If the upper limit of the number of installed fault current limiters is reached, obtain the optimized configuration scheme according to the position of the optimal particle.
[0218] If the upper limit of the number of installed fault current limiters is not reached, increase the number of installed fault current limiters by one, and return to the step of calculating the fitness of each particle in combination with the fitness function.
[0219] Exemplarily, the result output module 204 can also be used for:
[0220] Randomly generate a position value of a particle. If the randomly generated position value of the particle is less than the preset value, replace the position value of the worst particle with the randomly generated position value of the particle.
[0221] If the randomly generated position value of the particle is greater than or equal to the preset value, obtain the number of the worst particle, and replace the position value of the worst particle with the average value of the position values of the particles before the number of the worst particle to complete the update of the worst particle.
[0222] Exemplarily, the fourth formula can be;
[0223]
[0224] Among them, G(t) represents the gravitational constant at the t-th iteration, t represents the current iteration number, and S represents the maximum iteration number.
[0225] The fifth formula can be:
[0226]
[0227] Among them, M i (t) represents the inertial mass of particle i at the t-th iteration, value i(t) represents the fitness value of particle i at the t-th iteration, best(t) represents the maximum fitness value at the t-th iteration, and worst(t) represents the minimum fitness value at the t-th iteration.
[0228] The sixth formula can be:
[0229]
[0230] Among them, F i d (t) represents the resultant force on particle i, rand x represents the random number of the x-th particle in the particle set containing the top members, and rand x takes a random number within [0, 1], nbest represents the particle set containing the top members, n represents the total number of particles in the particle set containing the top members, represents the force between particle i and particle j at the t-th iteration in dimension d, R ij (t) represents the Euclidean distance between particle i and particle j at the t-th iteration, ε represents a minimum value, represents the position of particle i at the t-th iteration in dimension d, represents the position of particle j at the t-th iteration in dimension d, M i (t) represents the inertial mass of particle i at the t-th iteration, M j (t) represents the inertial mass of particle j at the t-th iteration, np represents the number represented by the particle, and Cp is a fixed preset parameter value.
[0231] The seventh formula can be:
[0232]
[0233] Among them, represents the acceleration of particle i at the t-th iteration in dimension d;
[0234] The eighth formula can be:
[0235]
[0236] Among them, ω represents the inertia coefficient, ω max represents the maximum value of the inertia factor, ω min represents the minimum value of the inertia factor.
[0237] The ninth formula can be:
[0238]
[0239] Among them, V i d(t + 1) represents the velocity of particle i at the (t + 1)-th iteration in dimension d, V i d (t) is the velocity of particle i at the t-th iteration in dimension d, the position of particle i at the t-th iteration in dimension d, H represents a random number within [0, 1], represents the position of the first particle alpha before particle i in dimension d, represents the position of the second particle beta before particle i in dimension d, represents the position of the third particle delta before particle i in dimension d.
[0240] The calculation formula for the preset value can be:
[0241]
[0242] where C set represents the preset value.
[0243] In the above embodiments, the descriptions of the respective embodiments have their own emphases. For parts not detailed or recorded in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.
[0244] Those of ordinary skill in the art can realize that, in combination with the templates, units, and algorithm steps of the examples described in the embodiments disclosed herein, they can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods for each specific application to implement the described functions, but such implementation should not be considered to exceed the scope of the present invention.
[0245] If the said module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, to implement all or part of the processes in the methods of the above embodiments of the present invention, it can also be completed by a computer program instructing the relevant hardware. The said computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, it can implement the steps of the above embodiments of the optimization configuration method for the neutral point fault current limiter of each transformer. Among them, the said computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form, etc. The said computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, read-only memory, random access memory, electrical carrier signal, telecommunication signal, and software distribution medium, etc.
[0246] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.
Claims
1. An optimization configuration method for a neutral point fault current limiter of a transformer, characterized in that, Including: Obtaining the short-circuit current value of the over-standard node before the transformer current limiting, the short-circuit current value of the over-standard node after the transformer current limiting, the number of over-standard nodes on each side of the transformer, the number of neutral-point grounding wires of the transformer where fault current limiters can be installed, the impedance value of each current limiter, and obtaining the constraint conditions of the transformer; Based on the short-circuit current value of the over-standard node before the transformer current limiting, the short-circuit current value of the over-standard node after the transformer current limiting, the number of over-standard nodes on each side of the transformer, the number of neutral-point grounding wires of the transformer where fault current limiters can be installed, and the impedance value of each current limiter, establishing a fitness function; Based on the constraint conditions of the transformer, determining the upper limit of the number of installed fault current limiters and the value range of the impedance value of the current limiter; Based on the upper limit of the number of installed fault current limiters and the value range of the impedance value of the current limiter, with the goal of minimizing the fitness function, solving the number of installed fault current limiters, the installation location of the fault current limiter, and the value of the impedance value of the current limiter through the particle swarm algorithm to obtain an optimized configuration plan.
2. The method for optimizing the configuration of the neutral point fault current limiter of a transformer according to claim 1, wherein The establishing a fitness function based on the short-circuit current value of the over-standard node before the transformer current limiting, the short-circuit current value of the over-standard node after the transformer current limiting, the number of over-standard nodes on each side of the transformer, the number of neutral-point grounding wires of the transformer where fault current limiters can be installed, and the impedance value of each current limiter includes: Based on the short-circuit current value of the over-standard node before the transformer current limiting, the short-circuit current value of the over-standard node after the transformer current limiting, and the number of over-standard nodes on each side of the transformer, combining with the first formula to establish a first function; where the first function represents the current limiting effect of the optimized configuration plan; Based on the number of neutral-point grounding wires of the transformer where fault current limiters can be installed and the impedance value of each current limiter, combining with the second formula to establish a second function; where the second function represents the current limiting economic cost of the optimized configuration plan; Based on the first function, the second function, and the short-circuit current value of the over-standard node before the transformer current limiting, combining with the third formula to establish the fitness function.
3. The method for optimizing the configuration of the transformer neutral point fault current limiter according to claim 2, wherein, The first formula is: Among them, f1 represents the first function, and δ k represents the current limiting effect of the over-standard node k, and I m represents the preset target value, and I k ' represents the short-circuit current of the over-standard node k after current limiting, and N represents the number of over-standard nodes on each side of the transformer.
4. The method for optimizing the configuration of the neutral point fault current limiter of a transformer according to claim 3, wherein, The second formula is: Among them, f2 represents the second function, NFCL represents the number of neutral grounding wires of the transformer where a fault current limiter can be installed, Z FCL (i) represents the impedance value of the i-th fault current limiter, F FCL [Z FCL (i)] represents the cost of the i-th fault current limiter with an impedance value of Z FCL (i).
5. The method for optimizing the configuration of the transformer neutral point fault current limiter according to claim 4, wherein The third formula is: Among them, I k represents the short-circuit current value of the over-standard node k before current limiting. Both w1 and w2 represent weight coefficients. Z limit represents the impedance value constraint of the fault current limiter. I limit represents the current-limiting effect constraint of the fault current limiter. If both the impedance value constraint of the fault current limiter and the current-limiting effect constraint of the fault current limiter satisfy the constraint conditions, then M = 0; otherwise, M = 5000.
6. The method for optimizing the configuration of the transformer neutral point fault current limiter according to claim 1, characterized in that, The determining the upper limit of the number of installed fault current limiters and the value range of the impedance value of the current limiter based on the constraint conditions of the transformer includes: Based on the constraint conditions of the transformer, obtaining the insulation level of the transformer neutral point and the size of the spatial position where fault current limiting can be installed; Based on the insulation level of the transformer neutral point and the size of the spatial position where fault current limiting can be installed, determining the upper limit of the number of installed fault current limiters and the value range of the impedance value of the current limiter.
7. The method for optimizing the configuration of the neutral point fault current limiter of a transformer according to claim 1, characterized in that, The solving the number of installed fault current limiters, the installation location of the fault current limiter, and the value of the impedance value of the current limiter through the particle swarm algorithm based on the upper limit of the number of installed fault current limiters and the value range of the impedance value of the current limiter, with the goal of minimizing the fitness function, to obtain an optimized configuration plan includes: Initializing the algorithm parameters of the particle swarm algorithm, the positions of the initial particles are randomly and uniformly distributed, the dimension of the initial particle swarm is 2, numbering each initial particle, and setting the number of installed fault current limiters to 1; Calculate the fitness of each particle in combination with the fitness function; Calculate the gravitational constant in combination with the fourth formula; Calculate the inertial mass of each particle in combination with the fifth formula; Based on the gravitational constant and the inertial mass of each particle, calculate the resultant force received by each particle in combination with the sixth formula; Based on the resultant force received by each particle and the inertial mass of each particle, calculate the acceleration of each particle in combination with the seventh formula; Calculate the inertia coefficient in combination with the eighth formula; Based on the inertia coefficient, the acceleration of each particle, and the number of each particle, update the velocity of each particle in combination with the ninth formula; Based on the velocity of each particle, update the position of each particle, calculate the fitness of each particle after updating the position, determine the optimal particle and the worst particle, and update the worst particle based on the number of each particle; Judge whether the number of installed fault current limiters reaches the upper limit of the number of installed fault current limiters at this time; If the upper limit of the number of installed fault current limiters is reached, obtain the optimized configuration plan according to the position of the optimal particle; If the upper limit of the number of installed fault current limiters is not reached, increase the number of installed fault current limiters by one, and return to the step of calculating the fitness of each particle in combination with the fitness function.
8. The method for optimizing the configuration of the transformer neutral point fault current limiter according to claim 7, wherein The process of updating the worst particle based on the number of each particle includes: Randomly generate a position value of a particle. If the randomly generated position value of the particle is less than the preset value, replace the position value of the worst particle with the randomly generated position value of the particle; If the randomly generated position value of the particle is greater than or equal to the preset value, obtain the number of the worst particle, and replace the position value of the worst particle with the average value of the position values of the particles before the number of the worst particle to complete the update of the worst particle.
9. The method for optimizing the configuration of the transformer neutral point fault current limiter according to claim 8, wherein, The fourth formula is; Among them, G(t) represents the gravitational constant at the t-th iteration, t represents the current iteration number, and S represents the maximum iteration number; The fifth formula is: Among them, M i (t) represents the inertial mass of particle i at the t-th iteration, value i (t) represents the fitness value of particle i at the t-th iteration, best(t) represents the maximum value of the fitness value at the t-th iteration, and worst(t) represents the minimum value of the fitness value at the t-th iteration; The sixth formula is: Among them, F i d (t) represents the resultant force acting on particle i, and rand x represents the random number of the x-th particle in the particle set containing the top member, and the value of rand x is a random number within [0, 1]. nbest represents the particle set containing the top member, and n represents the total number of particles in the particle set containing the top member. represents the force between particle i and particle j at the t-th iteration in dimension d, and R ij (t) represents the Euclidean distance between particle i and particle j at the t-th iteration, and ε represents the minimum value. represents the position of particle i at the t-th iteration in dimension d. represents the position of particle j at the t-th iteration in dimension d, and M i (t) represents the inertial mass of particle i at the t-th iteration, and M j (t) represents the inertial mass of particle j at the t-th iteration. np represents the number represented by the particle, and Cp is a fixed preset parameter value. The seventh formula is: Among them, represents the acceleration of particle i at the t-th iteration in the d dimension; The eighth formula is: where ω represents the inertial coefficient, ω max represents the maximum value of the inertia factor, ω min represents the minimum value of the inertia factor; The ninth formula is: Among them, V i d (t + 1) represents the velocity of particle i at the (t + 1)-th iteration in dimension d, and V i d (t) is the velocity of particle i at the t-th iteration in dimension d, the position of particle i at the t-th iteration in dimension d, H represents a random number within [0, 1], represents the position of the first particle alpha before particle i in dimension d, represents the position of the second particle beta before particle i in dimension d, represents the position of the third particle delta before particle i in dimension d; The calculation formula of the preset value is: Among them, C set represents the preset value.
10. An optimized configuration device for a transformer neutral point fault current limiter, characterized in that, Include: A data acquisition module for acquiring the short-circuit current value of the over-standard nodes before the transformer limits the current, the short-circuit current value of the over-standard nodes after the transformer limits the current, the number of over-standard nodes on each side of the transformer, the number of neutral point grounding wires of the transformer that can install fault current limiters, the impedance value of each current limiter, and acquiring the constraint conditions of the transformer; A function calculation module for establishing a fitness function based on the short-circuit current value of the over-standard nodes before the transformer limits the current, the short-circuit current value of the over-standard nodes after the transformer limits the current, the number of over-standard nodes on each side of the transformer, the number of neutral point grounding wires of the transformer that can install fault current limiters, and the impedance value of each current limiter; A condition restriction module for determining the upper limit of the number of installed fault current limiters and the value range of the impedance value of the current limiter based on the constraint conditions of the transformer; A result output module, which is used to solve the number of installed fault current limiters, the installation positions of the fault current limiters, and the value range of the impedance values of the current limiters based on the upper limit of the number of installed fault current limiters and the value range of the impedance values of the current limiters, with the goal of minimizing the fitness function through the particle swarm algorithm, so as to obtain an optimized configuration plan.