A method, system, device, and medium for detecting a reactor turn-to-turn short circuit fault

Abstract

The application discloses a kind of reactor turn-to-turn short circuit fault detection method, system, equipment and medium, it is related to the technical field of reactor.The detection method is carried out model construction using structure data and operating data, generates the adjustable circuit model corresponding to reactor;Based on the simulation current corresponding to adjustable circuit model and the measured current in operating data, coil parameter identification is generated, and target coil parameter is generated;Based on target coil parameter and the normal coil impedance matrix corresponding to reactor, turn-to-turn short circuit fault detection is generated, and turn-to-turn short circuit detection data is generated.The application takes the normal coil impedance matrix corresponding to target coil parameter and reactor as observation object, can effectively perceive the operating state of each layer coil of reactor, improve detection result accuracy.

Description

Technical Field

[0001] This invention relates to the field of reactor technology, and in particular to methods, systems, equipment and media for detecting inter-turn short-circuit faults in reactors. Background Technology

[0002] To maintain the stability of power grid operation, reactors are increasingly used in power systems, and dry-type air-core reactors are widely used for reactive power compensation, filtering, and current limiting due to their structural characteristics. Dry-type air-core reactors mainly consist of several tightly arranged coils, and changes in their coil parameters reflect the condition of the equipment itself. Inter-turn short-circuit faults are one of the common fault types in dry-type air-core reactors.

[0003] Currently, traditional inter-turn short-circuit fault detection technologies mainly include the detection coil method, temperature monitoring method, smoke detection method, and equivalent impedance monitoring method. The detection coil method is easily affected by the spatial magnetic field, leading to misjudgment of the condition; the temperature detection method relies on the temperature change of the dry-type air-core reactor for detection, but its sensitivity is not high in the early stage of the fault; the smoke detection method is affected by the gas in the environment and can only provide early warning in the case of severe faults, resulting in poor reliability; the equivalent impedance monitoring method uses the equivalent impedance transformation characteristics of the reactor to monitor inter-turn short-circuit faults, but the impedance change is small in the early stage of the fault, resulting in low monitoring sensitivity. Summary of the Invention

[0004] This invention provides a method, system, device, and medium for detecting inter-turn short-circuit faults in reactors, which solves the technical problems of existing inter-turn short-circuit fault detection technologies being easily affected by environmental factors, having low sensitivity and poor reliability in the early stages of fault detection, and resulting in low accuracy of detection results.

[0005] This invention provides a method for detecting inter-turn short-circuit faults in reactors, comprising:

[0006] Obtain the structural data and operational data of the reactor, and use the structural data and operational data to construct a model to generate an adjustable circuit model corresponding to the reactor.

[0007] Based on the simulated current corresponding to the adjustable circuit model and the measured current in the operating data, coil parameters are identified to generate target coil parameters.

[0008] Based on the target coil parameters and the normal coil impedance matrix corresponding to the reactor, inter-turn short-circuit fault detection is performed to generate inter-turn short-circuit detection data corresponding to the reactor.

[0009] Optionally, the operating data includes port voltage and total reactor current; the step of using the structural data and the operating data to construct a model and generate an adjustable circuit model corresponding to the reactor includes:

[0010] The port voltage is used as the model input data, the total current of the reactor is used as the model output data, and the model is constructed by combining the structural data to generate the reactor inter-turn circuit model corresponding to the reactor.

[0011] The inter-turn circuit model of the reactor is updated using preset parameters to generate an adjustable circuit model corresponding to the reactor.

[0012] The fitness function of the adjustable circuit model is:

[0013]

[0014] Where Y represents fitness; This represents the total current of the reactor. Calculate the total current for the adjustable circuit model.

[0015] Optionally, the step of identifying coil parameters and generating target coil parameters based on the simulated current corresponding to the adjustable circuit model and the measured current in the operating data includes:

[0016] The simulated current corresponding to the adjustable circuit model is compared with the measured current in the running data to generate a comparison result;

[0017] When the comparison results are the same, the initial coil parameters in the structural data are used as the target coil parameters.

[0018] When the comparison results are different, the position of the wolf is initialized using a preset coefficient formula to generate multiple initial candidate schemes;

[0019] The fitness values ​​of the initial candidate solutions are calculated using the adjustable circuit model to generate multiple fitness values.

[0020] Select the initial candidate solutions corresponding to the fitness values ​​that meet the preset selection rules, and generate the first initial candidate solution, the second initial candidate solution, and the third initial candidate solution;

[0021] The first initial candidate scheme, the second initial candidate scheme, and the third initial candidate scheme are updated using a preset update formula and the preset coefficient formula to generate a first intermediate candidate scheme, a second intermediate candidate scheme, and a third intermediate candidate scheme.

[0022] The candidate solution with the maximum fitness value among the first intermediate candidate solution, the second intermediate candidate solution, and the third intermediate candidate solution is taken as the target candidate solution and the number of iterations is counted.

[0023] Determine whether the number of iterations is greater than the preset maximum number of iterations;

[0024] If so, the electrical parameters corresponding to the target candidate scheme shall be used as the target coil parameters corresponding to the reactor;

[0025] If not, the target candidate solution is taken as the new initial solution, and the process jumps to the step of calculating the fitness value of the initial candidate solution through the adjustable circuit model to generate multiple fitness values.

[0026] Optionally, the step of performing inter-turn short-circuit fault detection based on the target coil parameters and the normal coil impedance matrix corresponding to the reactor, and generating inter-turn short-circuit detection data corresponding to the reactor, includes:

[0027] The impedance matrix of the faulty coil is generated by constructing an impedance matrix using the target coil parameters.

[0028] The difference matrix is ​​generated by calculating the difference between the normal coil impedance matrix and the fault coil impedance matrix corresponding to the reactor.

[0029] Based on the impedance data and mutual inductance data of each coil in the difference matrix, the rate of change of the index is calculated to generate the rate of change of impedance and the rate of change of mutual inductance of the coil.

[0030] Inter-turn short-circuit fault detection is performed based on the impedance change rate and the mutual inductance change rate, and inter-turn short-circuit detection data corresponding to the reactor is generated.

[0031] Optionally, the step of calculating the rate of change of the index based on the impedance data and mutual inductance data corresponding to each coil in the difference matrix, and generating the rate of change of impedance and mutual inductance corresponding to the coil, includes:

[0032] Substitute the impedance data corresponding to the coil in the difference matrix into the preset impedance change rate calculation formula to calculate the impedance change rate and generate the impedance change rate corresponding to the coil.

[0033] The formula for calculating the preset impedance change rate is:

[0034]

[0035] Among them, Z li Z represents the impedance change rate of the i-th layer coil; ni Z represents the healthy impedance of the i-th layer coil; xi Let be the fault impedance of the i-th layer coil;

[0036] Substitute the mutual inductance data corresponding to the coil into the preset mutual inductance data calculation formula to calculate the mutual inductance data and generate the mutual inductance change rate corresponding to the coil.

[0037] The preset mutual inductance data calculation formula is as follows:

[0038]

[0039] Among them, M li,lj M represents the rate of change of mutual inductance between the i-th and j-th layer coils; ni,nj For healthy mutual inductance between the i-th and j-th layer coils; M xi,xj The mutual inductance is for the fault of the i-th and j-th layer coils.

[0040] Optionally, the step of detecting inter-turn short-circuit faults based on the impedance change rate and the mutual inductance change rate, and generating inter-turn short-circuit detection data corresponding to the reactor, includes:

[0041] Determine whether the rate of change of impedance and the rate of change of mutual inductance corresponding to the coil are both less than a first preset value;

[0042] If so, it is determined that the coils corresponding to the impedance change rate and the mutual inductance change rate have not experienced inter-turn short circuit faults, and the coil normal data is generated and the number of detections is counted.

[0043] If not, the degree of fault corresponding to the coil is determined based on the first preset interval, the second preset interval, and the second preset value, and coil detection data corresponding to the coil is generated and the number of detections is counted.

[0044] When the number of detections equals the total number of coils corresponding to the reactor, the inter-turn short-circuit detection data corresponding to the reactor is constructed using all the coil detection data and all the coil normal data at the current moment.

[0045] Optionally, the step of determining the fault degree corresponding to the coil based on the first preset interval, the second preset interval, and the second preset value, generating coil detection data corresponding to the coil, and counting the number of detections includes:

[0046] Determine whether either the rate of change of impedance or the rate of change of mutual inductance is within a first preset range;

[0047] If so, it is determined that the coil corresponding to the impedance change rate and the mutual inductance change rate has a minor fault, and the first coil detection data is generated and the number of detections is counted.

[0048] If not, determine whether either the rate of change of impedance or the rate of change of mutual inductance is within the second preset range;

[0049] If so, it is determined that the coil corresponding to the impedance change rate and the mutual inductance change rate has a moderate fault, and second coil detection data is generated and the number of detections is counted.

[0050] If not, then determine whether the rate of change of impedance and the rate of change of mutual inductance are both greater than the second preset value;

[0051] If so, it is determined that the coil corresponding to the impedance change rate and the mutual inductance change rate has a serious fault, and third coil detection data is generated and the number of detections is counted.

[0052] If not, then the coil corresponding to the impedance change rate and the mutual inductance change rate is determined to have a moderate fault, and the fourth coil detection data is generated and the number of detections is counted.

[0053] The present invention also provides a reactor inter-turn short-circuit fault detection system, comprising:

[0054] An adjustable circuit model generation module is used to acquire the structural data and operating data of the reactor, and to construct a model using the structural data and operating data to generate an adjustable circuit model corresponding to the reactor.

[0055] The target coil parameter generation module is used to identify coil parameters and generate target coil parameters based on the simulated current corresponding to the adjustable circuit model and the measured current in the running data.

[0056] The inter-turn short-circuit detection data generation module is used to perform inter-turn short-circuit fault detection based on the target coil parameters and the normal coil impedance matrix corresponding to the reactor, and generate inter-turn short-circuit detection data corresponding to the reactor.

[0057] The present invention also provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of implementing any of the above-described reactor inter-turn short-circuit fault detection methods.

[0058] The present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed, implements any of the above-described reactor inter-turn short-circuit fault detection methods.

[0059] As can be seen from the above technical solutions, the present invention has the following advantages:

[0060] This invention acquires the structural and operational data of a reactor, uses this data to construct a model, and generates an adjustable circuit model corresponding to the reactor. Based on the simulated current corresponding to the adjustable circuit model and the measured current in the operational data, coil parameters are identified to generate target coil parameters. Based on the target coil parameters and the impedance matrix of the reactor's normal coils, inter-turn short-circuit fault detection is performed, generating inter-turn short-circuit detection data for the reactor. By using the target coil parameters and the impedance matrix of the reactor's normal coils as the observation objects, the operating status of each layer of the reactor's coils can be effectively perceived, improving the accuracy of the detection results. This invention solves the technical problems of existing reactor inter-turn short-circuit fault detection technologies, which are easily affected by environmental factors, have low sensitivity and poor reliability in the early stages of fault detection, resulting in low accuracy of the detection results. Attached Figure Description

[0061] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0062] Figure 1 This is a flowchart of the steps of a reactor inter-turn short-circuit fault detection method provided in Embodiment 1 of the present invention;

[0063] Figure 2 This is a flowchart of the steps of a reactor inter-turn short-circuit fault detection method provided in Embodiment 2 of the present invention;

[0064] Figure 3 This is a flowchart of the Canglang algorithm provided in Embodiment 2 of the present invention;

[0065] Figure 4 This is a flowchart of a reactor inter-turn short-circuit fault detection method provided in Embodiment 2 of the present invention;

[0066] Figure 5 This is a structural block diagram of a reactor inter-turn short-circuit fault detection system provided in Embodiment 3 of the present invention;

[0067] Figure 6 This is a structural block diagram of a dry-type air-core reactor fault detection system based on the Canglang algorithm provided in Embodiment 3 of the present invention;

[0068] Figure 7 This is a structural block diagram of an electronic device provided in Embodiment 4 of the present invention. Detailed Implementation

[0069] Existing reactor inter-turn short-circuit fault detection technologies are largely affected by environmental factors, resulting in low sensitivity and poor reliability in the early stages of fault detection. Furthermore, few methods detect faults from the perspective of changes in reactor electrical parameters; typical methods, such as equivalent impedance monitoring, only focus on changes in the reactor's total equivalent resistance and equivalent inductance, failing to capture detailed changes in the electrical parameters of each coil layer. Therefore, this invention provides a reactor inter-turn short-circuit fault detection method, system, device, and medium to address the shortcomings of existing reactor inter-turn short-circuit fault detection technologies, which are easily affected by environmental factors, exhibiting low sensitivity and poor reliability in the early stages of fault detection, leading to low accuracy of detection results.

[0070] To make the objectives, features, and advantages of this invention more apparent and understandable, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0071] Example 1

[0072] Please see Figure 1 , Figure 1 This is a flowchart illustrating the steps of a reactor inter-turn short-circuit fault detection method provided in Embodiment 1 of the present invention.

[0073] Example 1 of this invention provides a method for detecting inter-turn short-circuit faults in a reactor, comprising:

[0074] Step 101: Obtain the structural and operational data of the reactor, and use the structural and operational data to build a model and generate an adjustable circuit model corresponding to the reactor.

[0075] In this embodiment of the invention, the reactor refers to a dry-type air-core reactor. Using an actual dry-type air-core reactor as the data collection object, its structural data and operational data are acquired. The operational data includes port voltage and total reactor current. The port voltage of the dry-type air-core reactor under operating conditions is collected using a current transformer. As a system input parameter, the total current Using the actual output parameters of the system and combined with structural data, a model is constructed to generate the reactor's inter-turn circuit model. The inter-turn circuit model is then updated using preset parameters to generate the corresponding adjustable circuit model for the reactor.

[0076] Step 102: Identify coil parameters based on the simulated current corresponding to the adjustable circuit model and the measured current in the running data, and generate target coil parameters.

[0077] In this embodiment of the invention, the simulated current corresponding to the adjustable circuit model and the measured current in the operating data are compared to obtain the comparison result. The comparison result determines whether the collected data is affected by environmental factors. When the comparison result is the same, it means that the collected data is not affected by environmental factors. At this time, the initial coil parameters in the collected structural data can be directly used as the target coil parameters. The initial coil parameters include the coil parameters of each layer of the dry-type air-core reactor, and the coil parameters include self-inductance, mutual inductance, and resistance.

[0078] When the comparison results are different, it indicates that the collected data is affected by environmental factors. Therefore, it is necessary to optimize the model parameters to obtain accurate target coil parameters. The Canglang algorithm is used to optimize the model parameters of the adjustable circuit model to determine the target coil parameters corresponding to the reactor. Specifically, the Canglang position is initialized using a preset coefficient formula, generating multiple initial candidate schemes. The fitness values ​​of the initial candidate schemes are calculated using the adjustable circuit model, generating multiple fitness values. The initial candidate schemes corresponding to the fitness values ​​that satisfy the preset selection rules are selected, generating the first, second, and third initial candidate schemes. The first, second, and third initial candidate schemes are updated using preset update formulas and preset coefficient formulas, generating the first, second, and third intermediate candidate schemes. The candidate scheme with the maximum fitness value among the first, second, and third intermediate candidate schemes is selected as the target candidate scheme, and the number of iterations is counted. If the number of iterations exceeds the preset maximum number of iterations, the electrical parameters corresponding to the target candidate scheme are used as the target coil parameters for the reactor. If not, the target candidate scheme is used as the new initial scheme, and the process jumps to the step of calculating the fitness values ​​of the initial candidate schemes using the adjustable circuit model to generate multiple fitness values.

[0079] Step 103: Based on the target coil parameters and the normal coil impedance matrix corresponding to the reactor, perform inter-turn short-circuit fault detection and generate inter-turn short-circuit detection data corresponding to the reactor.

[0080] In this embodiment of the invention, an impedance matrix is ​​constructed using the target coil parameters to generate the fault coil impedance matrix. A difference matrix is ​​generated by calculating the difference between the impedance matrix of the normal coil corresponding to the reactor and the impedance matrix of the fault coil. Based on the impedance and mutual inductance data of each coil in the difference matrix, the rate of change of indicators is calculated to generate the impedance change rate and mutual inductance change rate for each coil. Inter-turn short-circuit fault detection is performed based on the impedance change rate and mutual inductance change rate, generating inter-turn short-circuit detection data for the reactor.

[0081] In this embodiment of the invention, structural and operational data of the reactor are acquired, and a model is constructed using these data to generate an adjustable circuit model corresponding to the reactor. Based on the simulated current corresponding to the adjustable circuit model and the measured current in the operational data, coil parameters are identified to generate target coil parameters. Based on the target coil parameters and the normal coil impedance matrix corresponding to the reactor, inter-turn short-circuit fault detection is performed, generating inter-turn short-circuit detection data for the reactor. The Canglang algorithm is a highly innovative metaheuristic optimization algorithm. This technology simulates the unique hierarchical leadership and hunting process of a canglang wolf to achieve precise perception of the coil parameters (inductance, resistance, mutual inductance) of a dry-type air-core reactor, and detects inter-turn short-circuit faults by observing the impedance and mutual inductance change rates. Simultaneously, the parameter calculation process has superior optimization capabilities and fast convergence speed, improving the sensitivity and real-time performance of inter-turn short-circuit fault monitoring of the reactor. Meanwhile, this scheme proposes using the rate of change of the self-inductance, mutual inductance, and resistance of each layer of the reactor coils—that is, the target coil parameters—as the observation object. This effectively senses the operating status of each layer of the reactor coils and improves the accuracy of the detection results. It solves the technical problem that existing reactor inter-turn short-circuit fault detection technologies are easily affected by environmental factors, resulting in low sensitivity and poor reliability in the early stages of fault detection, leading to low accuracy of the detection results.

[0082] Example 2

[0083] Please see Figure 2 , Figure 2 This is a flowchart illustrating the steps of a reactor inter-turn short-circuit fault detection method provided in Embodiment 2 of the present invention.

[0084] Another method for detecting inter-turn short-circuit faults in reactors provided in Example 2 of this invention includes:

[0085] Step 201: Obtain the structural and operational data of the reactor, and use the structural and operational data to build a model and generate an adjustable circuit model corresponding to the reactor.

[0086] Furthermore, the operating data includes port voltage and total reactor current, and step 201 may include the following sub-steps S11-S12:

[0087] S11. Use the port voltage as the model input data and the total reactor current as the model output data, and combine it with the structural data to build the model and generate the reactor inter-turn circuit model corresponding to the reactor.

[0088] S12. Update the reactor inter-turn circuit model using preset parameters to generate the corresponding adjustable circuit model of the reactor.

[0089] In this embodiment of the invention, an actual dry-type air-core reactor is used as the data collection object, and the port voltage of the dry-type air-core reactor under operating conditions is collected using a current transformer. As a system input parameter, the total current As the actual output parameters of the system, a circuit model is established using an actual dry-type air-core reactor, and the system input parameters are used. Substituting into the adjustable circuit model, the total current is calculated using the adjustable circuit model. The accuracy of the adjustable circuit model parameters is evaluated using the fitness function.

[0090] This example uses a 35kV reactor as the experimental object, with a rated capacity S. n =2000kV·A, system voltage U=35kV, 20 layers of coil, equally divided into 5 enclosures. The port voltage of the dry-type air-core reactor under operating conditions is obtained using a current transformer. and total current These serve as the system input data and the actual model output data, respectively.

[0091] Using an actual dry-type air-core reactor as a reference, an adjustable circuit model is established. In this example, the adjustable circuit model has 20 layers of coils, and its expression is as follows:

[0092]

[0093] Among them, R i L i These represent the resistance and self-inductance parameters of the i-th layer coil, respectively; M i,k This represents the mutual inductance parameter between coils i and k; This represents the port voltage of the i-th layer coil; This represents the branch current of coil i; i = 1, 2, ..., 20.

[0094] The formula for calculating the total current of the model is:

[0095]

[0096] in, This indicates the calculation of the total current using an adjustable circuit model. This represents the branch current in the adjustable circuit model.

[0097] Updating the reactor inter-turn circuit model using preset parameters means adding random numbers to R, L, and M as initial values ​​for the impedance matrix, thereby updating the reactor inter-turn circuit model and obtaining the corresponding adjustable circuit model of the reactor.

[0098] Using the system input data, i.e., the port voltage, as the input condition for the adjustable circuit model, and combining the adjustable circuit model expression and the total current calculation formula, the output data of the adjustable circuit model, i.e., the total current of the adjustable circuit model, is calculated. The fitness function is constructed using the actual output and the adjustable output to evaluate the parameter optimization results. The fitness function expression is as follows:

[0099]

[0100] Where Y represents fitness; This represents the total current of the reactor. Calculate the total current for the adjustable circuit model.

[0101] Step 202: Identify coil parameters based on the simulated current corresponding to the adjustable circuit model and the measured current in the running data, and generate target coil parameters.

[0102] Further, step 202 may include the following sub-steps S21-S210:

[0103] S21. Compare the simulated current corresponding to the adjustable circuit model with the measured current in the running data to generate a comparison result.

[0104] S22. When the comparison results are the same, the initial coil parameters in the structural data shall be used as the target coil parameters.

[0105] S23. When the comparison results are different, the position of the wolf is initialized using a preset coefficient formula to generate multiple initial candidate schemes.

[0106] S24. Calculate the fitness values ​​of the initial candidate schemes using the adjustable circuit model to generate multiple fitness values.

[0107] S25. Select the initial candidate schemes corresponding to the fitness values ​​that satisfy the preset selection rules, and generate the first initial candidate scheme, the second initial candidate scheme and the third initial candidate scheme.

[0108] S26. Update the first initial candidate scheme, the second initial candidate scheme, and the third initial candidate scheme using the preset update formula and the preset coefficient formula, and generate the first intermediate candidate scheme, the second intermediate candidate scheme, and the third intermediate candidate scheme.

[0109] S27. Select the candidate scheme with the maximum fitness value among the first intermediate candidate scheme, the second intermediate candidate scheme and the third intermediate candidate scheme as the target candidate scheme and count the number of iterations.

[0110] S28. Determine whether the number of iterations is greater than the preset maximum number of iterations. If yes, proceed to step S29; otherwise, proceed to step S210.

[0111] S29. Use the electrical parameters corresponding to the target candidate scheme as the target coil parameters corresponding to the reactor.

[0112] S210. Take the target candidate solution as the new initial solution, and jump to execute the step of calculating the fitness value of the initial candidate solution through the adjustable circuit model to generate multiple fitness values.

[0113] The preset selection rule refers to selecting the three fitness values ​​with the highest fitness values.

[0114] In this embodiment of the invention, the simulated current corresponding to the adjustable circuit model is compared with the measured current in the operating data to generate a comparison result. When the comparison result is the same, the initial coil parameters in the structural data are used as the target coil parameters. When the comparison result is different, the adjustable circuit model is optimized to determine the target coil parameters corresponding to the reactor. Specifically, the Canglang algorithm is used to optimize the adjustable circuit model parameters until the model parameters minimize the fitness function, thus completing the calculation of the electrical parameters of each layer of the dry-type air-core reactor, including self-inductance, mutual inductance, and resistance, and obtaining the target coil parameters.

[0115] By simulating the social hierarchy of wolves, the wolf algorithm designates the best solution as the α wolf; the second and third best solutions as the β wolf and δ wolf, respectively; and the other candidate solutions as the ω wolf. The ω wolf follows the other wolves, and the search for the optimal solution is guided by the α, β, and δ wolves. The wolf's hunting process mainly consists of three steps: finding prey, surrounding prey, and attacking prey. Surrounding prey is represented by the following formula:

[0116]

[0117] Where t represents the current algebra; and Represents the first coefficient vector and the second coefficient vector; X p X indicates the location of the prey, and X indicates the location of the wolf. and The calculation formula, i.e., the formula for the preset coefficients, is as follows:

[0118]

[0119] Where Iteration is the maximum number of iterations, which is 200 in this example, and r1 and r2 are any vectors in the interval [0,1]. Let t be the first parameter vector; t represents the current algebra. and Let represent the first coefficient vector and the second coefficient vector.

[0120] The grey wolf can identify the location of its prey and surround them. Hunting is generally guided by the α wolf, with β and δ wolves sometimes also participating. However, in the abstract search space, we do not know the location of the optimal value (prey). To mimic the grey wolf's hunting behavior, we assume that the α, β, and δ wolves know the potential locations of the prey, store the three currently obtained optimal solutions, and force other solutions (ω wolves) to update their positions based on these three optimal solutions. The preset update formula is:

[0121]

[0122] in, The distance between the prey and the wolf in the first initial candidate scenario; The distance between the prey and the wolf in the second initial candidate scheme; X represents the distance between the prey and the wolf in the third initial candidate scenario; p Let p represent the prey's position, where p = α, β, δ; X represents the wolf's position; X1 is the position of a single wolf updated based on wolf α, and X2 and X3 are the positions of a single wolf updated based on wolves β and γ, respectively; X(t+1) is the target candidate solution.

[0123] The wolf primarily searches for prey based on the positions of α, β, and δ wolves, moving away from each other to search and clustering together to attack. The parameter 'a' decreases linearly with the number of iterations to highlight the wolf algorithm's global exploration and local search capabilities. Within the interval [-2a, 2a], A decreases as a decreases. Within the interval [-1, 1], the next candidate position will be between the current position and the prey's location, simulating the wolf's attack behavior and highlighting its local search capabilities. When |A| > 1, the simulated candidate will explore away from the prey, demonstrating the wolf algorithm's global exploration capabilities. C takes any value in the interval [0, 2]. For the prey, C provides a free weight; when C > 1, the prey's position has little impact on the distance between the wolf and the prey; when C < 1, the impact is significant, showcasing the strong randomness and global exploration capabilities of the wolf algorithm during optimization, avoiding getting trapped in local optima.

[0124] Figure 3 The flowchart for the optimization process of the Canglang algorithm is shown below. In this example, the optimization steps of the Canglang algorithm are as follows:

[0125] 1. Initialize the position X of the Azure Wolf i (i = 1, 2, ..., n), initialized according to the preset coefficient formula.

[0126] 2. Calculate the fitness value of each candidate solution using the fitness function, select the three best solutions and name them as follows: That is, select the three initial candidate solutions corresponding to the three largest fitness values ​​to generate the first initial candidate solution, the second initial candidate solution, and the third initial candidate solution;

[0127] 3. Update the candidate solutions using the preset update formula, and update... The values ​​are updated using preset update formulas and preset coefficient formulas to update the first initial candidate scheme, the second initial candidate scheme, and the third initial candidate scheme, generating the first intermediate candidate scheme, the second intermediate candidate scheme, and the third intermediate candidate scheme.

[0128] 4. Calculate the fitness value for each candidate solution based on the fitness function, select the best solution, and rename it. Increment the iteration count by 1, that is, take the candidate solution with the maximum fitness value among the first intermediate candidate solution, the second intermediate candidate solution and the third intermediate candidate solution as the target candidate solution and count the iteration count;

[0129] 5. Determine if the number of iterations is greater than the preset maximum number of iterations. If so, end the process and use the electrical parameters corresponding to the target candidate scheme as the target coil parameters corresponding to the reactor. Here, the electrical parameters refer to the resistance, self-inductance, and mutual inductance corresponding to the adjustable circuit model. Otherwise, use the target candidate scheme as the new initial scheme and return to "Step 3".

[0130] Step 203: Construct the impedance matrix using the target coil parameters to generate the fault coil impedance matrix.

[0131] In this embodiment of the invention, the target coil parameters are combined with the structural data of the reactor to construct the coil impedance matrix of the reactor fault state, thereby obtaining the fault coil impedance matrix.

[0132] Step 204: Calculate the difference between the normal coil impedance matrix and the fault coil impedance matrix corresponding to the reactor to generate a difference matrix.

[0133] In this embodiment of the invention, the coil impedance matrix of the reactor in its healthy state and the coil impedance matrix in its fault state are subjected to parameter processing analysis. That is, the difference between the normal coil impedance matrix and the fault coil impedance matrix in the reactor's healthy state is calculated to obtain the difference matrix. The specific expression is as follows:

[0134]

[0135] Among them, Z n and Z x In this example, Z represents the impedance matrix under healthy and faulty conditions, i.e., the normal coil impedance matrix and the faulty coil impedance matrix, respectively. ni and Z xiM represents the impedance of the i-th layer coil in the normal coil impedance matrix and the faulty coil impedance matrix, respectively. ni,nj and M xi,xj These represent the mutual inductance of the i-th and j-th layers of coils in the normal coil impedance matrix and the faulty coil impedance matrix, respectively.

[0136] Step 205: Calculate the rate of change of the index based on the impedance data and mutual inductance data of each coil in the difference matrix, and generate the rate of change of impedance and mutual inductance of the coil.

[0137] Further, step 205 may include the following sub-steps S31-S32:

[0138] S31. Substitute the impedance data corresponding to the coil in the difference matrix into the preset impedance change rate calculation formula to calculate the impedance change rate and generate the impedance change rate corresponding to the coil.

[0139] The formula for calculating the preset impedance change rate is:

[0140]

[0141] Among them, Z li Z represents the impedance change rate of the i-th layer coil; ni Z represents the healthy impedance of the i-th layer coil; xi Let be the fault impedance of the i-th layer coil.

[0142] S32. Substitute the mutual inductance data corresponding to the coil into the preset mutual inductance data calculation formula to calculate the mutual inductance data and generate the mutual inductance change rate corresponding to the coil.

[0143] The default formula for calculating mutual inductance data is:

[0144]

[0145] Among them, M li,lj M represents the rate of change of mutual inductance between the i-th and j-th layer coils; ni,nj For healthy mutual inductance between the i-th and j-th layer coils; M xi,xj The mutual inductance is for the fault of the i-th and j-th layer coils.

[0146] In this embodiment of the invention, the rate of change of parameter indicators of each layer of coils is obtained by using the difference matrix, that is, the impedance change rate and mutual inductance change rate corresponding to each coil are calculated by using the preset impedance change rate calculation formula and the preset mutual inductance data calculation formula respectively.

[0147] Step 206: Perform inter-turn short-circuit fault detection based on impedance change rate and mutual inductance change rate, and generate inter-turn short-circuit detection data corresponding to the reactor.

[0148] Further, step 206 may include the following sub-steps S41-S44:

[0149] S41. Determine whether the rate of change of impedance and the rate of change of mutual inductance corresponding to the coil are both less than the first preset value. If yes, proceed to step S42; otherwise, proceed to step S43.

[0150] S42. Determine that the coils corresponding to the impedance change rate and mutual inductance change rate have not experienced inter-turn short circuit faults, generate normal coil data, and count the number of tests.

[0151] S43. Based on the first preset interval, the second preset interval, and the second preset value, determine the fault level of the coil, generate coil detection data corresponding to the coil, and count the number of detections.

[0152] S44. When the number of tests equals the total number of coils corresponding to the reactor, use all coil test data and all coil normal data at the current moment to construct the inter-turn short circuit test data corresponding to the reactor.

[0153] Furthermore, step S43 may include the following sub-steps S431-S437:

[0154] S431. Determine whether either the rate of change of impedance or the rate of change of mutual inductance is within the first preset range. If yes, proceed to step S432; otherwise, proceed to step S433.

[0155] S432. Determine that the coil corresponding to the impedance change rate and mutual inductance change rate has a minor fault, generate the first coil detection data and count the number of detections.

[0156] S433. Determine whether either the rate of change of impedance or the rate of change of mutual inductance is within the second preset range. If yes, proceed to step S434; otherwise, proceed to step S435.

[0157] S434. Determine that the coil corresponding to the impedance change rate and mutual inductance change rate has a moderate fault, generate the second coil detection data and count the number of detections.

[0158] S435. Determine whether the rate of change of impedance and the rate of change of mutual inductance are both greater than the second preset value. If yes, proceed to step S436; otherwise, proceed to step S437.

[0159] S436. Determine that the coil corresponding to the impedance change rate and mutual inductance change rate has a serious fault, generate third coil detection data and count the number of detections.

[0160] S437. Determine that the coil corresponding to the impedance change rate and mutual inductance change rate has a moderate fault, generate the fourth coil detection data and count the number of detections.

[0161] The first preset value is 3%. The second preset value is 15%. The first preset range is greater than 3% and less than 7%. The second preset range is greater than 7% and less than 15%.

[0162] In this embodiment of the invention, inter-turn short-circuit faults in a dry-type air-core reactor are detected by observing the impedance and mutual inductance change rate of each layer of coils. Specifically, this example sets four threshold values ​​to determine the severity of the inter-turn short-circuit fault, as follows:

[0163] (1) When both the impedance and mutual inductance change rates are no greater than 3%, that is, when the impedance and mutual inductance change rates corresponding to the coil are both less than the first preset value, it is determined that the coil corresponding to the impedance and mutual inductance change rates has not experienced an inter-turn short circuit fault, and normal coil data is obtained and the number of tests is counted. Otherwise, it is determined whether the impedance and mutual inductance change rates are within the first preset range. When all impedance and mutual inductance change rates are less than the first preset value, it is determined that the reactor has not experienced an inter-turn short circuit fault.

[0164] (2) When either the impedance or the mutual inductance change rate is greater than 3% but not greater than 7%, that is, if either the impedance change rate or the mutual inductance change rate of the coil is within the first preset range, it is determined that a minor fault has occurred in the coil, the first coil detection data is obtained, and the number of detections is counted. Otherwise, it is determined whether the impedance change rate and the mutual inductance change rate are both within the second preset range.

[0165] (3) When either the impedance or mutual inductance change rate is greater than 7% but not greater than 15%, that is, when either the impedance change rate or the mutual inductance change rate of the coil is within the second preset range, the coil corresponding to the impedance change rate and the mutual inductance change rate is determined to have a moderate fault, the second coil detection data is obtained, and the number of detections is counted. Otherwise, it is determined whether both the impedance change rate and the mutual inductance change rate are greater than the second preset value.

[0166] (4) When both the impedance and mutual inductance change rates are greater than 15%, that is, when both the impedance and mutual inductance change rates are greater than the second preset value, the coil corresponding to the impedance and mutual inductance change rates is determined to have a serious fault, the third coil detection data is obtained, and the number of detections is counted. Otherwise, the coil corresponding to the impedance and mutual inductance change rates is determined to have a moderate fault, the fourth coil detection data is obtained, and the number of detections is counted.

[0167] When the number of judgments equals the total number of coils corresponding to the reactor, all coil test data and all normal coil data are used to construct the inter-turn short-circuit detection data for the reactor. Otherwise, fault judgment continues for other coils. Since each reactor consists of multiple layers of coils, each layer has its own coil parameters. When a fault occurs in one or more layers of coils, the coil parameters of the corresponding layer will change significantly, while the other layers will not change or will experience negligible changes. Therefore, the fault location can be determined by observing the changes in the impedance, i.e., the coil parameters, of each layer of coils. The degree of fault is determined based on the percentage change in parameters, and the fault is located based on the specific number of coil layers with impedance changes, thereby achieving the diagnosis of the fault location and degree of the dry-type air-core reactor.

[0168] In embodiments of the present invention, such as Figure 4 As shown, the voltage signal of the actual reactor is input into the reactor model, i.e., the adjustable circuit model, and the simulated current is output. Then, the simulated current and the measured current in the operating data are numerically compared to generate a comparison result. When the comparison result is different, the parameters are optimized using the Canglang algorithm, i.e., the Canglang algorithm is used to optimize the model parameters of the adjustable circuit model, and the optimization result is output to obtain the target coil parameters. The impedance and mutual inductance change rate are calculated using the target coil parameters. Based on the first preset value, the first preset interval, the second preset interval, and the second preset value, the fault degree corresponding to the coil is judged, the fault degree corresponding to the coil is determined, and the detection structure is output. The parameter calculation scheme used in this embodiment is a novel metaheuristic algorithm. It takes the strict hierarchy of the Canglang as a reference, simulates the special hierarchical leadership and hunting process of the Canglang, and combines the fitness function change to establish the parameter changes of each layer of coil, including inductance, resistance, and mutual inductance, under the operating state of the dry-type air-core reactor. This completes the monitoring of the state of the dry-type air-core reactor coil, timely feedback of the working state of the dry-type air-core reactor coil, realizes the monitoring of power equipment, and improves the power system's control over important power equipment. This method has a fast convergence speed, can better coordinate exploration and development capabilities, has stronger randomness and considerable exploration capabilities, and can accurately determine the working status of each layer of coils in the reactor, thus realizing real-time fault monitoring.

[0169] Example 3

[0170] Please see Figure 5 , Figure 5 This is a structural block diagram of a reactor inter-turn short-circuit fault detection system provided in Embodiment 3 of the present invention.

[0171] Example 3 of this invention provides a reactor inter-turn short-circuit fault detection system, comprising:

[0172] The adjustable circuit model generation module 501 is used to acquire the structural data and operating data of the reactor, and to build a model using the structural data and operating data to generate an adjustable circuit model corresponding to the reactor.

[0173] The target coil parameter generation module 502 is used to identify coil parameters and generate target coil parameters based on the simulated current corresponding to the adjustable circuit model and the measured current in the running data.

[0174] The inter-turn short circuit detection data generation module 503 is used to perform inter-turn short circuit fault detection based on the target coil parameters and the normal coil impedance matrix corresponding to the reactor, and generate inter-turn short circuit detection data corresponding to the reactor.

[0175] Optionally, the operating data includes port voltage and total reactor current, and the adjustable circuit model generation module 501 can perform the following steps:

[0176] The port voltage is used as the model input data, the total reactor current is used as the model output data, and the model is constructed by combining the structural data to generate the reactor inter-turn circuit model corresponding to the reactor.

[0177] The reactor inter-turn circuit model is updated using preset parameters to generate an adjustable circuit model corresponding to the reactor.

[0178] The fitness function of the adjustable circuit model is:

[0179]

[0180] Where Y represents fitness; This represents the total current of the reactor. Calculate the total current for the adjustable circuit model.

[0181] Optionally, the target coil parameter generation module 502 may perform the following steps:

[0182] The simulated current corresponding to the adjustable circuit model is compared with the measured current in the running data to generate a comparison result.

[0183] When the comparison results are the same, the initial coil parameters in the structural data will be used as the target coil parameters.

[0184] When the comparison results are different, the position of the wolf is initialized using a preset coefficient formula to generate multiple initial candidate schemes;

[0185] The fitness values ​​of the initial candidate solutions are calculated using an adjustable circuit model, generating multiple fitness values.

[0186] Select the initial candidate solutions corresponding to the fitness values ​​that meet the preset selection rules, and generate the first initial candidate solution, the second initial candidate solution, and the third initial candidate solution;

[0187] The first initial candidate scheme, the second initial candidate scheme, and the third initial candidate scheme are updated using preset update formulas and preset coefficient formulas to generate the first intermediate candidate scheme, the second intermediate candidate scheme, and the third intermediate candidate scheme.

[0188] The candidate solution with the maximum fitness value among the first, second, and third intermediate candidate solutions is selected as the target candidate solution, and the number of iterations is counted.

[0189] Determine if the number of iterations is greater than the preset maximum number of iterations;

[0190] If so, the electrical parameters corresponding to the target candidate scheme will be used as the target coil parameters corresponding to the reactor;

[0191] If not, the target candidate solution is taken as the new initial solution, and the process jumps to the step of calculating the fitness value of the initial candidate solution through the adjustable circuit model to generate multiple fitness values.

[0192] Optionally, the inter-turn short-circuit detection data generation module 503 includes:

[0193] The fault coil impedance matrix generation module is used to construct the impedance matrix using the target coil parameters, thereby generating the fault coil impedance matrix.

[0194] The difference matrix construction module is used to calculate the difference between the normal coil impedance matrix and the fault coil impedance matrix corresponding to the reactor, and generate the difference matrix.

[0195] The impedance change rate and mutual inductance change rate generation module is used to calculate the index change rate based on the impedance data and mutual inductance data corresponding to each coil in the difference matrix, and generate the impedance change rate and mutual inductance change rate corresponding to the coil.

[0196] The inter-turn short-circuit detection data generation submodule is used to detect inter-turn short-circuit faults based on impedance change rate and mutual inductance change rate, and generate inter-turn short-circuit detection data corresponding to the reactor.

[0197] Optionally, the impedance change rate and mutual inductance change rate generation module may perform the following steps:

[0198] Substitute the impedance data corresponding to the coil in the difference matrix into the preset impedance change rate calculation formula to calculate the impedance change rate and generate the impedance change rate corresponding to the coil.

[0199] The formula for calculating the preset impedance change rate is:

[0200]

[0201] Among them, Z liZ represents the impedance change rate of the i-th layer coil; ni Z represents the healthy impedance of the i-th layer coil; xi Let be the fault impedance of the i-th layer coil;

[0202] Substitute the mutual inductance data corresponding to the coil into the preset mutual inductance data calculation formula to calculate the mutual inductance data and generate the mutual inductance change rate corresponding to the coil.

[0203] The default formula for calculating mutual inductance data is:

[0204]

[0205] Among them, M li,lj M represents the rate of change of mutual inductance between the i-th and j-th layer coils; ni,nj For healthy mutual inductance between the i-th and j-th layer coils; M xi,xj The mutual inductance is for the fault of the i-th and j-th layer coils.

[0206] Optionally, the inter-turn short-circuit detection data generation submodule includes:

[0207] The rate of change judgment module is used to determine whether the rate of change of impedance and the rate of change of mutual inductance corresponding to the coil are both less than the first preset value.

[0208] The coil normal data generation module is used to determine that, if the impedance change rate and mutual inductance change rate are correct, the coil corresponding to the coil has not experienced an inter-turn short circuit fault, generate coil normal data, and count the number of tests.

[0209] The coil detection data generation module is used to determine the degree of fault of the coil based on the first preset interval, the second preset interval, and the second preset value if the fault is not found, generate the coil detection data corresponding to the coil, and count the number of detections.

[0210] The inter-turn short-circuit detection data construction module is used to construct the inter-turn short-circuit detection data corresponding to the reactor by using all coil detection data and all coil normal data at the current moment when the number of detections equals the total number of coils corresponding to the reactor.

[0211] Optionally, the coil detection data generation module may perform the following steps:

[0212] Determine whether either the rate of change of impedance or the rate of change of mutual inductance is within a first preset range;

[0213] If so, it is determined that the coil corresponding to the impedance change rate and mutual inductance change rate has a minor fault, the first coil detection data is generated and the number of detections is counted;

[0214] If not, determine whether either the rate of change of impedance or the rate of change of mutual inductance is within the second preset range;

[0215] If so, the coil corresponding to the impedance change rate and mutual inductance change rate is determined to have a moderate fault, and the second coil detection data is generated and the number of detections is counted.

[0216] If not, then determine whether the rate of change of impedance and the rate of change of mutual inductance are both greater than the second preset value;

[0217] If so, the coil corresponding to the impedance change rate and mutual inductance change rate is determined to have a serious fault, and the third coil detection data is generated and the number of detections is counted.

[0218] If not, the coil corresponding to the impedance change rate and mutual inductance change rate is determined to have a moderate fault, and the fourth coil detection data is generated and the number of detections is counted.

[0219] In embodiments of the present invention, such as Figure 6 As shown, the system can also provide a fault detection system for dry-type air-core reactors based on the Canglang algorithm, including a reactor model selection module, a database, a parameter setting module, and an output / export module. Reactor parameter settings include system voltage, rated voltage, number of enclosures, and number of coil layers. Optimization results include multiple resistances, inductances, and mutual inductances. Detection results include fault severity and fault location.

[0220] Example 4

[0221] Please see Figure 7 , Figure 7 This is a structural block diagram of an electronic device provided in Embodiment 4 of the present invention.

[0222] An electronic device according to an embodiment of the present invention includes: a memory 701 and a processor 702. The memory 701 stores a computer program. When the computer program is executed by the processor 702, the processor 702 performs the reactor inter-turn short circuit fault detection method as described in any of the above embodiments.

[0223] The memory 701 may be an electronic memory such as flash memory, EEPROM (Electrically Erasable Programmable Read-Only Memory), EPROM, hard disk, or ROM. The memory 701 has a storage space 703 for program code 713 for performing any of the method steps described above. For example, the storage space 703 for program code may include various program codes 713 for implementing the various steps in the methods described above. This program code can be read from or written to one or more computer program products. These computer program products include program code carriers such as hard disks, compact discs (CDs), memory cards, or floppy disks. The program code may be compressed, for example, in a suitable form. When run by a computing processing device, this code causes the computing processing device to perform the various steps in the reactor inter-turn short-circuit fault detection method described above.

[0224] This invention also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the reactor inter-turn short-circuit fault detection method as described in any of the above embodiments.

[0225] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0226] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, or indirect coupling or communication connection between apparatuses or units, and may be electrical, mechanical, or other forms.

[0227] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0228] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0229] If the integrated unit is implemented as 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, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0230] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for detecting inter-turn short-circuit faults in a reactor, characterized in that, include: Obtain the structural data and operational data of the reactor, and use the structural data and operational data to construct a model to generate an adjustable circuit model corresponding to the reactor. Based on the simulated current corresponding to the adjustable circuit model and the measured current in the operating data, coil parameters are identified to generate target coil parameters. Based on the target coil parameters and the normal coil impedance matrix corresponding to the reactor, inter-turn short-circuit fault detection is performed to generate inter-turn short-circuit detection data corresponding to the reactor. The operating data includes port voltage and total reactor current; The step of using the structural data and the operational data to construct a model and generate an adjustable circuit model corresponding to the reactor includes: The port voltage is used as the model input data, the total current of the reactor is used as the model output data, and the model is constructed by combining the structural data to generate the reactor inter-turn circuit model corresponding to the reactor. The inter-turn circuit model of the reactor is updated using preset parameters to generate an adjustable circuit model corresponding to the reactor. The fitness function of the adjustable circuit model is: ； in, For fitness; This represents the total current of the reactor. Calculate the total current for the adjustable circuit model; The step of identifying coil parameters and generating target coil parameters based on the simulated current corresponding to the adjustable circuit model and the measured current in the operating data includes: The simulated current corresponding to the adjustable circuit model is compared with the measured current in the running data to generate a comparison result; When the comparison results are the same, the initial coil parameters in the structural data are used as the target coil parameters. When the comparison results are different, the position of the wolf is initialized using a preset coefficient formula to generate multiple initial candidate schemes; The fitness values ​​of the initial candidate solutions are calculated using the adjustable circuit model to generate multiple fitness values. Select the initial candidate solutions corresponding to the fitness values ​​that meet the preset selection rules, and generate the first initial candidate solution, the second initial candidate solution, and the third initial candidate solution; The first initial candidate scheme, the second initial candidate scheme, and the third initial candidate scheme are updated using a preset update formula and the preset coefficient formula to generate a first intermediate candidate scheme, a second intermediate candidate scheme, and a third intermediate candidate scheme. The candidate solution with the maximum fitness value among the first intermediate candidate solution, the second intermediate candidate solution, and the third intermediate candidate solution is taken as the target candidate solution and the number of iterations is counted. Determine whether the number of iterations is greater than the preset maximum number of iterations; If so, the electrical parameters corresponding to the target candidate scheme shall be used as the target coil parameters corresponding to the reactor; If not, the target candidate solution is taken as the new initial solution, and the process jumps to the step of calculating the fitness value of the initial candidate solution through the adjustable circuit model to generate multiple fitness values. The step of performing inter-turn short-circuit fault detection based on the target coil parameters and the normal coil impedance matrix corresponding to the reactor, and generating inter-turn short-circuit detection data corresponding to the reactor, includes: The impedance matrix of the faulty coil is generated by constructing an impedance matrix using the target coil parameters. The difference matrix is ​​generated by calculating the difference between the normal coil impedance matrix and the fault coil impedance matrix corresponding to the reactor. Based on the impedance data and mutual inductance data of each coil in the difference matrix, the rate of change of the index is calculated to generate the rate of change of impedance and the rate of change of mutual inductance of the coil. Inter-turn short-circuit fault detection is performed based on the impedance change rate and the mutual inductance change rate, and inter-turn short-circuit detection data corresponding to the reactor is generated.

2. The method for detecting inter-turn short-circuit faults in a reactor according to claim 1, characterized in that, The step of calculating the rate of change of indicators based on the impedance data and mutual inductance data corresponding to each coil in the difference matrix, and generating the impedance change rate and mutual inductance change rate corresponding to the coil, includes: Substitute the impedance data corresponding to the coil in the difference matrix into the preset impedance change rate calculation formula to calculate the impedance change rate and generate the impedance change rate corresponding to the coil. The formula for calculating the preset impedance change rate is: ； in, Let be the rate of change of impedance of the i-th layer coil; The healthy impedance of the i-th layer coil; Let be the fault impedance of the i-th layer coil; Substitute the mutual inductance data corresponding to the coil into the preset mutual inductance data calculation formula to calculate the mutual inductance data and generate the mutual inductance change rate corresponding to the coil. The preset mutual inductance data calculation formula is as follows: ； in, Let be the rate of change of mutual inductance between the i-th and j-th layer coils; For healthy mutual inductance between the i-th and j-th layer coils; The mutual inductance is for the fault of the i-th and j-th layer coils.

3. The method for detecting inter-turn short-circuit faults in a reactor according to claim 1, characterized in that, The step of detecting inter-turn short-circuit faults based on the impedance change rate and the mutual inductance change rate, and generating inter-turn short-circuit detection data corresponding to the reactor, includes: Determine whether the rate of change of impedance and the rate of change of mutual inductance corresponding to the coil are both less than a first preset value; If so, it is determined that the coils corresponding to the impedance change rate and the mutual inductance change rate have not experienced inter-turn short circuit faults, and the coil normal data is generated and the number of detections is counted. If not, the degree of fault corresponding to the coil is determined based on the first preset interval, the second preset interval, and the second preset value, and coil detection data corresponding to the coil is generated and the number of detections is counted. When the number of detections equals the total number of coils corresponding to the reactor, the inter-turn short-circuit detection data corresponding to the reactor is constructed using all the coil detection data and all the coil normal data at the current moment.

4. The method for detecting inter-turn short-circuit faults in a reactor according to claim 3, characterized in that, The step of determining the fault degree of the coil based on a first preset interval, a second preset interval, and a second preset value, generating coil detection data for the coil, and counting the number of detections includes: Determine whether either the rate of change of impedance or the rate of change of mutual inductance is within a first preset range; If so, it is determined that the coil corresponding to the impedance change rate and the mutual inductance change rate has a minor fault, and the first coil detection data is generated and the number of detections is counted. If not, determine whether either the rate of change of impedance or the rate of change of mutual inductance is within the second preset range; If so, it is determined that the coil corresponding to the impedance change rate and the mutual inductance change rate has a moderate fault, and second coil detection data is generated and the number of detections is counted. If not, then determine whether the rate of change of impedance and the rate of change of mutual inductance are both greater than the second preset value; If so, it is determined that the coil corresponding to the impedance change rate and the mutual inductance change rate has a serious fault, and third coil detection data is generated and the number of detections is counted. If not, then the coil corresponding to the impedance change rate and the mutual inductance change rate is determined to have a moderate fault, and the fourth coil detection data is generated and the number of detections is counted.

5. A reactor inter-turn short-circuit fault detection system, characterized in that, include: An adjustable circuit model generation module is used to acquire the structural data and operating data of the reactor, and to construct a model using the structural data and operating data to generate an adjustable circuit model corresponding to the reactor. The target coil parameter generation module is used to identify coil parameters and generate target coil parameters based on the simulated current corresponding to the adjustable circuit model and the measured current in the running data. The inter-turn short circuit detection data generation module is used to perform inter-turn short circuit fault detection based on the target coil parameters and the normal coil impedance matrix corresponding to the reactor, and generate inter-turn short circuit detection data corresponding to the reactor. The operating data includes port voltage and total reactor current; the adjustable circuit model generation module is used to take the port voltage as model input data, the total reactor current as model output data, and combine the structural data to build a model and generate the reactor inter-turn circuit model corresponding to the reactor. The inter-turn circuit model of the reactor is updated using preset parameters to generate an adjustable circuit model corresponding to the reactor. The fitness function of the adjustable circuit model is: ； in, For fitness; This represents the total current of the reactor. Calculate the total current for the adjustable circuit model; The target coil parameter generation module is used to compare the simulated current corresponding to the adjustable circuit model with the measured current in the running data and generate a comparison result. When the comparison results are the same, the initial coil parameters in the structural data are used as the target coil parameters. When the comparison results are different, the position of the wolf is initialized using a preset coefficient formula to generate multiple initial candidate schemes; The fitness values ​​of the initial candidate solutions are calculated using the adjustable circuit model to generate multiple fitness values. Select the initial candidate solutions corresponding to the fitness values ​​that meet the preset selection rules, and generate the first initial candidate solution, the second initial candidate solution, and the third initial candidate solution; The first initial candidate scheme, the second initial candidate scheme, and the third initial candidate scheme are updated using a preset update formula and the preset coefficient formula to generate a first intermediate candidate scheme, a second intermediate candidate scheme, and a third intermediate candidate scheme. The candidate solution with the maximum fitness value among the first intermediate candidate solution, the second intermediate candidate solution, and the third intermediate candidate solution is taken as the target candidate solution and the number of iterations is counted. Determine whether the number of iterations is greater than the preset maximum number of iterations; If so, the electrical parameters corresponding to the target candidate scheme shall be used as the target coil parameters corresponding to the reactor; If not, the target candidate solution is taken as the new initial solution, and the process jumps to the step of calculating the fitness value of the initial candidate solution through the adjustable circuit model to generate multiple fitness values. The inter-turn short-circuit detection data generation module includes: The fault coil impedance matrix generation module is used to construct an impedance matrix using the target coil parameters to generate the fault coil impedance matrix. The difference matrix construction module is used to calculate the difference between the normal coil impedance matrix and the fault coil impedance matrix corresponding to the reactor, and generate a difference matrix. The impedance change rate and mutual inductance change rate generation module is used to calculate the index change rate based on the impedance data and mutual inductance data corresponding to each coil in the difference matrix, and generate the impedance change rate and mutual inductance change rate corresponding to the coil. The inter-turn short-circuit detection data generation submodule is used to perform inter-turn short-circuit fault detection based on the impedance change rate and the mutual inductance change rate, and generate inter-turn short-circuit detection data corresponding to the reactor.

6. An electronic device, characterized in that, The device includes a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor causes the processor to perform the steps of the reactor inter-turn short-circuit fault detection method as described in any one of claims 1 to 4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed, it implements the reactor inter-turn short-circuit fault detection method as described in any one of claims 1 to 4.

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