Compressed sensing-based energy storage supporting wind power grid-connected power line single-phase grounding fault positioning method and application thereof
By applying compressed sensing algorithm and Kalman filtering in the collector lines of wind farms, the sparse zero-sequence injection current is calculated, solving the problem of single-phase grounding fault location in wind farms. This achieves efficient and accurate fault location and improves the robustness and applicability of the system.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- KUNMING UNIV OF SCI & TECH
- Filing Date
- 2025-11-14
- Publication Date
- 2026-07-21
AI Technical Summary
In wind farm collector lines, single-phase grounding faults are not obvious and the zero-sequence signal transmission path is complex. Traditional fault location methods face problems such as large data volume, complex calculation, and poor fault location accuracy, especially in long-distance cables and complex environments.
A compressed sensing-based method is adopted to calculate the sparse zero-sequence injection current by collecting three-phase voltage data. The fault current is reconstructed by combining Kalman filtering and compressed sensing algorithms. The fault distance is calculated using zero-sequence voltage and current, which reduces the dependence on the number of voltage measurement points and improves the positioning accuracy.
It achieves efficient and accurate single-phase grounding fault location under limited measurement point samples, reduces the dependence on synchronous sampling across the entire network, and improves the robustness of fault identification and system applicability.
Smart Images
Figure CN121114665B_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of power system relay protection technology, and in particular to a method for locating single-phase grounding faults in wind power grid-connected collector lines based on compressed sensing and its application. Background Technology
[0002] Wind farm collection lines often use a hybrid cable-overhead line layout with a multi-branched tree-like topology, resulting in single-phase grounding faults accounting for up to 80%. Furthermore, since wind farms currently use cable or hybrid overhead line structures to build collection networks, the characteristics of single-phase grounding faults are usually not obvious, and the zero-sequence signal transmission path is complex, posing a great challenge to traditional fault location methods.
[0003] Traditional fault location methods, such as traveling wave method, impedance method and manual inspection method, often face problems such as large data volume, complex calculation and poor fault location accuracy. The limitations of traditional methods are more obvious, especially in long-distance cables and complex environments.
[0004] In the process of conceiving and implementing this application, the inventors discovered that compressed sensing theory has significant advantages in undersampled data reconstruction. Wind farms also have undersampled characteristics such as sparse internal measurement points and complex signal transmission, resulting in a limited number of sampling points and incomplete observability of the system. This is similar to the scenario to which compressed sensing theory is applicable.
[0005] Therefore, this application proposes a single-phase grounding fault location method for energy storage-supported wind power grid-connected collector lines based on compressed sensing, aiming to overcome the difficulty of fault location in scenarios where the number of measurement points is limited. Summary of the Invention
[0006] The main purpose of this application is to provide a method for locating single-phase grounding faults in grid-connected wind power collection lines based on compressed sensing, aiming to solve the problem of fault location in scenarios where the number of measurement points is limited.
[0007] To achieve the above objectives, this application provides a method for locating single-phase grounding faults in wind power grid-connected collection lines based on compressed sensing, the method comprising:
[0008] Collect three-phase voltage data in the grid-connected collection line of wind power supported by energy storage, and calculate sparse zero-sequence injection current based on the three-phase voltage data. The sparse zero-sequence injection current is obtained by solving the underdetermined zero-sequence voltage equation set composed of the three-phase voltage data using a compressed sensing algorithm.
[0009] Identify the target nodes associated with the sparse zero-sequence injected current in the collection line area of each wind farm, and determine the area with the most target nodes as the fault area.
[0010] Obtain the zero-sequence voltage and zero-sequence current at the beginning and end of the fault region, and calculate the fault distance based on the zero-sequence voltage and zero-sequence current.
[0011] Optionally, the calculation steps for the sparse zero-sequence injection current include:
[0012] Kalman filtering is applied to the three-phase voltage data to extract the zero-sequence component from the filtered three-phase voltage data, resulting in the zero-sequence voltage equation set:
[0013]
[0014] Based on the aforementioned zero-sequence voltage equations, a sparsity-underdetermined zero-sequence voltage equation set is constructed:
[0015]
[0016] In the formula, M is the voltage measuring device installed on node N. The zero-sequence voltage components are obtained from the voltages of M nodes containing measuring devices using the symmetrical component method. This is the zero-order node impedance matrix constructed based on the network topology. The actual fault current is equivalently transformed into virtual zero-sequence fault currents at nodes m and n.
[0017] The sparse, underdetermined zero-sequence voltage equations are solved using a compressed sensing algorithm to obtain sparse solutions. , which serves as the sparse zero-sequence injection current.
[0018] Optionally, the sparse solution is obtained by using a compressed sensing algorithm to solve the sparse underdetermined zero-sequence voltage equations. The steps specifically include:
[0019] Initialize residual index set Support set , , Sparsity;
[0020] Calculate the correlation coefficient using the inner product matching criterion:
[0021] ;
[0022] Select the 2k maximum values from u to form a set. Construct its corresponding column index ;
[0023] Form a set based on the maximum value. The column indexes of and Update support set and index set ;
[0024] Solving using the conjugate gradient method Optimal sparsity coefficients :
[0025] ;
[0026] Select Largest absolute value A set of elements ,Will The support set sequence containing each element is labeled as And record the corresponding serial number. ;
[0027] Based on the support set sequence and serial number Update the index set and residuals ;
[0028] Determine if it satisfies or If the condition is met, stop the iteration and obtain the reconstructed signal. :
[0029]
[0030] Otherwise, let Then return to continue iterating. This formula represents the reconstruction of the signal using the CG–CoSaMP algorithm. Estimation is performed using the measurement matrix. With node voltage observation vector And combined with sparsity The reconstructed sparse vector values of the fault current are obtained.
[0031] Optionally, the steps for constructing the zero-sequence node impedance matrix include:
[0032] Based on the topology and zero-sequence parameters of the energy storage-supported wind power grid-connected collection line, a zero-sequence equivalent network is drawn.
[0033] Construct the zero-sequence node impedance matrix, and then form the corresponding observation matrix based on the specific distribution of the measurement points. ;
[0034]
[0035] In the formula, M represents the number of nodes containing the measuring device among the N nodes. This is the zero-sequence node impedance matrix formed based on the distribution of measurement points.
[0036] Optionally, the step of calculating the fault distance based on the zero-sequence voltage and the zero-sequence current includes:
[0037] Substituting the zero-sequence voltage and zero-sequence current at both ends into the transmission line equation, two real solutions d1 and d2 are obtained. The transmission line equation includes:
[0038]
[0039]
[0040]
[0041]
[0042]
[0043]
[0044]
[0045]
[0046]
[0047]
[0048]
[0049]
[0050] In the formula, , These are the real and imaginary parts of the phasor, respectively. The total ground capacitance impedance of the faulty collector line; The impedance of the faulty collector line; The zero-sequence voltage at the beginning of the faulty collector line; This refers to the zero-sequence current at the beginning of the faulty collector line; This is the zero-sequence voltage at the end of the faulty collector line.
[0051] The solution whose value is in the interval [0, 1] is taken as the unique solution among the two real solutions d1 and d2;
[0052] The fault distance is obtained by substituting the unique solution into the actual line length calculation formula.
[0053] Optionally, the zero-sequence voltage across the fault region satisfies the following expression:
[0054]
[0055] In the formula, This represents the total capacitance impedance to ground in the fault area. The impedance of the fault region; This is the fault distance ratio. ; , These are the zero-sequence voltage and zero-sequence current at the beginning of the fault region, respectively. This is the zero-sequence voltage at the end of the fault region.
[0056] Optionally, the wind farm collection line area is divided by the energy storage-supported wind power grid-connected collection line according to the node topology. The step of determining the target nodes associated with the sparse zero-sequence injection current appearing in each wind farm collection line area, and determining the area with the most target nodes as the fault area, includes:
[0057] Within a preset time window, the number of target nodes that satisfy the sparse zero-sequence injection current in the wind farm collector line area is counted.
[0058] The area of the wind farm's collection line where the target node appears within the preset time window is designated as the fault area.
[0059] In addition, to achieve the above objectives, this application also provides an application of the compressed sensing-based energy storage-supported wind power grid-connected collector line single-phase grounding fault location method as described in any of the preceding claims in single-phase grounding fault location.
[0060] In addition, to achieve the above objectives, this application also provides a computer system, the computer system comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the computer program is executed by the processor, it implements the steps of the method for locating single-phase grounding faults in grid-connected wind power collection lines based on compressed sensing as described in any of the preceding claims.
[0061] In addition, to achieve the above objectives, this application also provides a computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the method for locating single-phase grounding faults in grid-connected wind power collection lines based on compressed sensing as described in any of the preceding claims.
[0062] This application has at least the following beneficial effects:
[0063] 1. By using compressed sensing algorithms to reconstruct the zero-sequence injection current of faults, regional statistical analysis is performed on the reconstruction results within the time window to identify fault areas, reducing the dependence on the number of voltage measurement points and synchronous sampling across the entire network;
[0064] 2. By combining the voltage and current data of the measuring points at both ends of the fault area with the line parameters, the ranging equation is solved to realize the location of single-phase grounding faults in the energy storage-supported wind power grid-connected collection line;
[0065] 3. Introducing Kalman filtering into voltage data processing effectively suppresses noise and interference in the acquired data, improving the robustness of fault identification and the applicability of the system. Attached Figure Description
[0066] Figure 1 This is a flowchart illustrating the first embodiment of the method for locating single-phase grounding faults in grid-connected wind power collection lines based on compressed sensing in this application.
[0067] Figure 2 This is a schematic diagram of the energy storage-supported wind power grid-connected collection line model architecture involved in the embodiments of this application;
[0068] Figure 3 This is a schematic diagram of the architecture of a zero-sequence network for a single-phase ground fault involved in an embodiment of this application;
[0069] Figure 4 This is a schematic diagram of the architecture of the wind farm's power collection line area according to an embodiment of this application;
[0070] Figure 5 This is a schematic diagram of the current reconstruction result of the collector line node involved in the embodiments of this application;
[0071] Figure 6 This is a schematic diagram showing the statistical results of the occurrence of reconstructed nodes in each region involved in the embodiments of this application;
[0072] Figure 7 This is a schematic diagram of the hardware operating environment of the computer system involved in the embodiments of this application.
[0073] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation
[0074] To better understand the above technical solutions, exemplary embodiments of this disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of this disclosure to those skilled in the art.
[0075] First Embodiment
[0076] Reference Figure 1 This embodiment provides a method for locating single-phase grounding faults in grid-connected wind power collection lines based on compressed sensing. The method includes the following steps:
[0077] Step S10: Collect three-phase voltage data in the energy storage-supported wind power grid-connected collection line, and calculate the sparse zero-sequence injection current based on the three-phase voltage data. The sparse zero-sequence injection current is obtained by solving the underdetermined zero-sequence voltage equation set composed of the three-phase voltage data using a compressed sensing algorithm.
[0078] In this embodiment, the energy storage-supported wind power grid-connected collection line refers to a composite power transmission system in the wind farm's collection network that coordinates the operation of a wind power energy storage system (BESS) and an intelligent relay protection device. It is a "wind-storage synergy" stable grid-connected architecture that achieves the triple functions of wind power fluctuation mitigation, fault ride-through, and active grid support. The characteristics of this energy storage-supported wind power grid-connected collection line are its complex lines and limited sampling points.
[0079] The method described in this embodiment is applied to a three-phase circuit. It collects the voltage data of each phase in the three-phase circuit to obtain the three-phase voltage data, and calculates the sparse zero-sequence injection current based on the three-phase voltage data.
[0080] Considering the characteristics of energy storage supporting wind power grid-connected collection lines, the sampling points in the collected three-phase voltage data are limited. Therefore, for the calculation of sparse zero-sequence injection current, this embodiment creatively introduces a compressed sensing algorithm for calculation.
[0081] Specifically, the calculation steps for sparse zero-sequence injection current include:
[0082] Step S11: Perform Kalman filtering on the three-phase voltage data, extract the zero-sequence component from the filtered three-phase voltage data, and obtain the zero-sequence voltage equation set:
[0083]
[0084] It should be noted that the purpose of step S11 is to suppress measurement noise, especially high-frequency harmonic interference from wind farms, and improve the signal-to-noise ratio. For example, the Kalman filter model can be:
[0085]
[0086] In the formula, Indicates the system at time 10:00 The state vector includes zero-sequence voltage and zero-sequence current; Indicates the system at time 10:00 The state vector; This represents the state transition matrix, used to describe the evolution relationship between state variables at adjacent time points; This represents system process noise, reflecting model errors and external disturbances. For the system at time The observation information includes the actual sampled voltage and current; The observation matrix represents the mapping relationship between state variables and observations. To measure noise, reflecting sampling errors and external interference;
[0087] Step S12: Based on the zero-sequence voltage equation set, construct a sparsity underdetermined zero-sequence voltage equation set:
[0088]
[0089] In the formula, M is the voltage measuring device installed on node N. The zero-sequence voltage components are obtained from the voltages of M nodes containing measuring devices using the symmetrical component method. This is the zero-order node impedance matrix constructed based on the network topology. The virtual zero-sequence fault current is equivalently transformed from the actual fault current to the fault current at nodes m and n.
[0090] It is worth noting that the zero-sequence node impedance matrix is constructed based on the topology and zero-sequence impedance parameters of the energy storage-supported wind power grid-connected collector line.
[0091] It should be noted here that the underdetermined zero-sequence voltage equations obtained in S12 have an infinite number of solutions, while the negative-sequence fault current vector reconstructed by the compressed sensing algorithm only requires the target signal. Sufficiently sparse, compressed sensing technology can accurately reconstruct a unique solution vector, assuming... Given a sparse vector, it is reconstructed into a minimum using compressed sensing theory. The norm problem is addressed by employing a Compressive Sampling Matching Pursuit (CoSaMP) algorithm, an improvement upon the Conjugate Gradient Method (CG), to iteratively solve the system of equations and obtain sparse solutions. As a sparse zero-sequence injection current, that is:
[0092] Step S13: Solve the sparse, underdetermined zero-sequence voltage equations using the compressed sensing algorithm to obtain the sparse solution. As the sparse zero-sequence injection current:
[0093] Further and optionally, step S13 specifically includes the following steps:
[0094] Step S131, Initialize residuals index set Support set , , Sparsity;
[0095] Step S132: Calculate the correlation coefficient using the inner product matching criterion.
[0096] ;
[0097] Step S133: Select the 2k maximum values from u to form a set. Construct its corresponding column index ;
[0098] Step S134: Construct a set based on the maximum value. The column indexes of and Update support set and index set ;
[0099] Step S135: Solve using the conjugate gradient method. Optimal sparsity coefficients :
[0100] ;
[0101] Step S136, select Largest absolute value A set of elements ,Will The support set sequence containing each element is labeled as And record the corresponding serial number. ;
[0102] Step S137, based on the support set sequence and serial number Update the index set and residuals ;
[0103] Step S138, determine whether the condition is met. or If the condition is met, stop the iteration and obtain the reconstructed signal. ;
[0104] Step S139, otherwise, let Return to continue iterating.
[0105] Step S20: Determine the target nodes associated with the sparse zero-sequence injection current in the collection line area of each wind farm, and determine the area with the most target nodes as the fault area.
[0106] In step S20, the sparse zero-sequence injection current calculated in step S10 is used as a reference criterion to determine whether a current with a current value matching the sparse zero-sequence injection current appears in each node in the wind farm collector line area, and the node where the current appears is taken as the target node.
[0107] The region where the target node appears most frequently in each region is identified as the fault region.
[0108] It is worth noting that the energy storage-supported wind power grid-connected collection line includes multiple wind farm collection line areas, which are divided according to the node topology of the energy storage-supported wind power grid-connected collection line.
[0109] Furthermore, and optionally, the fault area is divided by time windows, the specific steps of which include:
[0110] Step S21: Within a preset time window, count the number of target nodes in the wind farm collector line region that satisfy the sparse zero-sequence injection current.
[0111] Step S22: The area of the wind farm collection line where the target node appears within the preset time window is designated as the fault area.
[0112] In some alternative implementations, the two regions with the most and second most target nodes can be counted as fault regions, and fault location can be performed on a unit of two fault regions.
[0113] Step S30: Obtain the zero-sequence voltage and zero-sequence current at the beginning and end of the fault area, and calculate the fault distance based on the zero-sequence voltage and zero-sequence current.
[0114] In step S30, taking the fault area determined in step S20 as a unit, the zero-sequence voltage and zero-sequence current at its first and last ends are obtained, and the fault distance is calculated based on these four quantities.
[0115] In some alternative implementations, the fault region is the faulty collector line. Measuring the electrical quantities at the beginning and end of the faulty collector line yields the zero-sequence voltage and zero-sequence current at its beginning and end. The zero-sequence voltage at both ends of the fault region satisfies the following expression:
[0116]
[0117] In the formula, This represents the total capacitance impedance to ground in the fault area. The impedance of the fault region; This is the fault distance ratio. ; , These are the zero-sequence voltage and zero-sequence current at the beginning of the fault region, respectively. This is the zero-sequence voltage at the end of the fault region.
[0118] Further, and optionally, the calculation of the fault distance includes the following steps:
[0119] Step S31: Substitute the zero-sequence voltage and zero-sequence current at both ends into the transmission line equation to obtain two real solutions d1 and d2. The transmission line equation includes:
[0120]
[0121]
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[0127]
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[0131]
[0132] In the formula, , These are the real and imaginary parts of the phasor, respectively. The total ground capacitance impedance of the faulty collector line; The impedance of the faulty collector line; The zero-sequence voltage at the beginning of the faulty collector line; This refers to the zero-sequence current at the beginning of the faulty collector line; This is the zero-sequence voltage at the end of the faulty collector line.
[0133] Solving the above equation yields two real solutions, d1 and d2.
[0134] Step S32: Among the two real solutions d1 and d2, the solution whose value is in the interval [0, 1] is taken as the unique solution;
[0135] Step S33: Substitute the unique solution into the actual line length calculation formula for conversion to obtain the fault distance.
[0136] In the technical solution provided in this embodiment, the zero-sequence injection current of the fault is reconstructed by the compressed sensing algorithm, and the fault area is identified by regional statistical analysis of the reconstruction results within the time window. The ranging equation is solved by combining the voltage and current data of the measuring points at both ends of the fault area with the line parameters, thereby reducing the dependence on the number of voltage measuring points and synchronous sampling of the entire network, and realizing the location of single-phase grounding faults in the grid-connected collection line of energy storage supporting wind power.
[0137] Second Embodiment
[0138] This embodiment provides a simulation model based on the single-phase grounding fault location method for energy storage-supported wind power grid-connected collector lines based on compressed sensing in the first embodiment.
[0139] Specifically, in PSCAD / EMTDC software, build such as Figure 2 The energy storage-supported wind power grid-connected collection line model shown requires a measurement point at each upstream and downstream terminal of each area to ensure the accuracy of fault location results. Nodes 1, 8, 16, 23, 31, 38, 46, 53, 61, and 68 are the measurement point locations for acquiring voltage and current data after a fault. To match actual field application requirements, a sampling rate of 2kHz is used. A single-phase ground fault is set between nodes 21 and 22, with a line length of 2km and the fault point 0.8km from node 21. The reconstruction time window is set to 10ms after the fault.
[0140] Furthermore, based on the topology of the wind farm's collector lines and the zero-sequence impedance parameters, a zero-sequence node impedance matrix is constructed. Combined with the distribution of measurement points, a corresponding observation matrix is formed, thus constructing a system as follows: Figure 3 The diagram shows the architecture of a zero-sequence network for a single-phase ground fault considering capacitance to ground.
[0141] Furthermore, based on the wind farm's collector lines and the regional division according to the node topology, interconnected nodes are grouped into one region, resulting in nine regions for the collector line model, as shown below. Figure 4 The diagram shows the architecture of the wind farm's collector line area. Each area requires a measuring point at its upstream and downstream terminals to acquire voltage and current data after a fault.
[0142] Furthermore, the CoSaMP (Compressive Sampling Matching Pursuit via Conjugate Gradient Method, CG-CoSaMP) algorithm, improved by the conjugate gradient method, is used to reconstruct the fault zero-sequence current. A schematic diagram of the collector line node current reconstruction results is provided below. Figure 5 If the number of reconstructed nodes is between 20 and 25, then region 3 can be identified as a faulty region.
[0143] Furthermore, the region with the highest frequency of reconfigured current nodes within the statistical time window was identified as the fault region. The statistical results of the number of reconfigured nodes in each region are shown below. Figure 6 Area 3 is the fault area.
[0144] Furthermore, in region 3, each collector line segment is 2km long, with a total length of 16km. A single-phase ground fault occurs 8.8km from node 1. The zero-sequence voltages of nodes 1 and 16 and the zero-sequence current of region 2 are utilized: , , Combined with the parameters of the faulty collector line, , .
[0145] Based on the voltage and current at both ends of the fault region, substitute them into the transmission line equation, and to eliminate the influence of phasor asynchrony on accuracy, take the modulus of both sides and square them:
[0146]
[0147] Furthermore, substituting these equations into the transmission line equations, we obtain the following quadratic equation:
[0148]
[0149] Solving this quadratic equation yields two solutions: 0.5510 and -1.8142. We select 0.5510, which lies in the interval [0, 1], as the desired solution.
[0150] This process is repeated until all 20 results are calculated and the average is taken, resulting in a fault distance of 55.1%. The fault location is 8.816 km from node 1, with an absolute error of 0.016 km and a relative error of 0.182%, which is extremely small.
[0151] Furthermore, as an implementation scheme, the present application also relates to the application of the compressed sensing-based energy storage-supported wind power grid-connected collector line single-phase grounding fault location method described in any of the preceding claims in single-phase grounding fault location.
[0152] Furthermore, as an implementation scheme, Figure 7 This is a schematic diagram of the hardware operating environment of the computer system involved in the embodiments of this application.
[0153] like Figure 7 As shown, the computer system may include: a processor 1001, such as a CPU; a memory 1005; a user interface 1003; a network interface 1004; and a communication bus 1002. The communication bus 1002 is used to enable communication between these components. The user interface 1003 may include a display screen or an input unit such as a keyboard; optionally, the user interface 1003 may also include a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface). The memory 1005 may be high-speed RAM or non-volatile memory, such as a disk drive. Optionally, the memory 1005 may also be a storage device independent of the aforementioned processor 1001.
[0154] Those skilled in the art will understand that Figure 7 The computer system architecture shown does not constitute a limitation on the computer system and may include more or fewer components than shown, or combine certain components, or have different component arrangements.
[0155] like Figure 7 As shown, the memory 1005, as a storage medium, may include an operating system, a network communication module, a user interface module, and computer programs. The operating system is a program that manages and controls the hardware and software resources of the computer system, as well as the operation of the computer programs and other software or programs.
[0156] exist Figure 7 In the computer system shown, the user interface 1003 is mainly used to connect to the terminal and communicate with the terminal; the network interface 1004 is mainly used to communicate with the backend server; and the processor 1001 can be used to call the computer program stored in the memory 1005.
[0157] In this embodiment, the computer system includes: a memory 1005, a processor 1001, and a computer program stored in the memory and executable on the processor, wherein:
[0158] When processor 1001 calls a computer program stored in memory 1005, it performs the following operations:
[0159] Collect three-phase voltage data in the grid-connected collection line of wind power supported by energy storage, and calculate sparse zero-sequence injection current based on the three-phase voltage data. The sparse zero-sequence injection current is obtained by solving the underdetermined zero-sequence voltage equation set composed of the three-phase voltage data using a compressed sensing algorithm.
[0160] Identify the target nodes associated with the sparse zero-sequence injected current in the collection line area of each wind farm, and determine the area with the most target nodes as the fault area.
[0161] Obtain the zero-sequence voltage and zero-sequence current at the beginning and end of the fault region, and calculate the fault distance based on the zero-sequence voltage and zero-sequence current.
[0162] When processor 1001 calls a computer program stored in memory 1005, it performs the following operations:
[0163] Kalman filtering is applied to the three-phase voltage data to extract the zero-sequence component from the filtered three-phase voltage data, resulting in the zero-sequence voltage equation set:
[0164]
[0165] Based on the aforementioned zero-sequence voltage equations, a sparsity-underdetermined zero-sequence voltage equation set is constructed:
[0166]
[0167] In the formula, M is the voltage measuring device installed on node N. The zero-sequence voltage components are obtained from the voltages of M nodes containing measuring devices using the symmetrical component method. This is the zero-order node impedance matrix constructed based on the network topology. The virtual zero-sequence fault current is equivalently transformed from the actual fault current to the fault current at nodes m and n.
[0168] The sparse, underdetermined zero-sequence voltage equations are solved using a compressed sensing algorithm to obtain sparse solutions. , which serves as the sparse zero-sequence injection current.
[0169] When processor 1001 calls a computer program stored in memory 1005, it performs the following operations:
[0170] Initialize residual index set Support set , , Sparsity;
[0171] Calculate the correlation coefficient using the inner product matching criterion:
[0172] ;
[0173] Select the 2k maximum values from u to form a set. Construct its corresponding column index ;
[0174] Form a set based on the maximum value. The column indexes of and Update support set and index set ;
[0175] Solving using the conjugate gradient method Optimal sparsity coefficients :
[0176] ;
[0177] Select Largest absolute value A set of elements ,Will The support set sequence containing each element is labeled as And record the corresponding serial number. ;
[0178] Based on the support set sequence and serial number Update the index set and residuals ;
[0179] Determine if it satisfies or If the condition is met, stop the iteration and obtain the reconstructed signal. ;
[0180] Otherwise, let Return to continue iterating.
[0181] The sparse, underdetermined zero-sequence voltage equations are solved using a compressed sensing algorithm to obtain sparse solutions. , which serves as the sparse zero-sequence injection current.
[0182] When processor 1001 calls a computer program stored in memory 1005, it performs the following operations:
[0183] Based on the topology and zero-sequence parameters of the energy storage-supported wind power grid-connected collection line, a zero-sequence equivalent network is drawn.
[0184] Construct the zero-sequence node impedance matrix, and then form the corresponding observation matrix based on the specific distribution of the measurement points.
[0185]
[0186] In the formula, M represents the number of nodes containing the measuring device among the N nodes. This is the zero-sequence node impedance matrix formed based on the distribution of measurement points.
[0187] When processor 1001 calls a computer program stored in memory 1005, it performs the following operations:
[0188] Substituting the zero-sequence voltage and zero-sequence current at both ends into the transmission line equation, two real solutions d1 and d2 are obtained. The transmission line equation includes:
[0189]
[0190]
[0191]
[0192]
[0193]
[0194]
[0195]
[0196]
[0197]
[0198]
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[0200]
[0201] In the formula, , These are the real and imaginary parts of the phasor, respectively. The total ground capacitance impedance of the faulty collector line; The impedance of the faulty collector line; The zero-sequence voltage at the beginning of the faulty collector line; This refers to the zero-sequence current at the beginning of the faulty collector line; This is the zero-sequence voltage at the end of the faulty collector line.
[0202] The solution whose value is in the interval [0, 1] is taken as the unique solution among the two real solutions d1 and d2;
[0203] The fault distance is obtained by substituting the unique solution into the actual line length calculation formula.
[0204] When processor 1001 calls a computer program stored in memory 1005, it performs the following operations:
[0205] The zero-sequence voltage across the fault region satisfies the following expression:
[0206]
[0207] In the formula, This represents the total capacitance impedance to ground in the fault area. The impedance of the fault region; The fault distance ratio, ; , These are the zero-sequence voltage and zero-sequence current at the beginning of the fault region, respectively. This is the zero-sequence voltage at the end of the fault region.
[0208] Furthermore, those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program includes program instructions and can be stored in a storage medium, which is a computer-readable storage medium. The program instructions are executed by at least one processor in a computer system to implement the process steps of the embodiments of the above methods.
[0209] Therefore, this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the various steps of the method for locating single-phase grounding faults in wind power grid-connected collector lines based on compressed sensing, as described in the above embodiments.
[0210] The computer-readable storage medium can be any computer-readable storage medium capable of storing program code, such as a USB flash drive, portable hard drive, read-only memory (ROM), magnetic disk, or optical disk.
[0211] It should be noted that, since the storage medium provided in the embodiments of this application is the storage medium used to implement the methods of the embodiments of this application, those skilled in the art can understand the specific structure and variations of the storage medium based on the methods described in the embodiments of this application, and therefore will not be repeated here. All storage media used in the methods of the embodiments of this application fall within the scope of protection of this application.
[0212] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.
[0213] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.
[0214] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.
[0215] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.
[0216] It should be noted that any reference signs placed between parentheses in the claims should not be construed as limiting the claims. The word "comprising" does not exclude the presence of components or steps not listed in the claims. The word "a" or "an" preceding a component does not exclude the presence of a plurality of such components. This application can be implemented by means of hardware comprising several different components and by means of a suitably programmed computer. In a unit claim enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names.
[0217] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.
[0218] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.
Claims
1. A method for locating single-phase grounding faults in grid-connected wind power collection lines based on compressed sensing, characterized in that, The method includes the following steps: Collect three-phase voltage data in the grid-connected collection line of wind power supported by energy storage, and calculate sparse zero-sequence injection current based on the three-phase voltage data. The sparse zero-sequence injection current is obtained by solving the underdetermined zero-sequence voltage equation set composed of the three-phase voltage data using a compressed sensing algorithm. Identify the target nodes associated with the sparse zero-sequence injected current in the collection line area of each wind farm, and determine the area with the most target nodes as the fault area. Obtain the zero-sequence voltage and zero-sequence current at the beginning and end of the fault region, and calculate the fault distance based on the zero-sequence voltage and zero-sequence current; The step of calculating the fault distance based on the zero-sequence voltage and the zero-sequence current includes: Substituting the zero-sequence voltage and zero-sequence current at both ends into the transmission line equation, two real solutions d1 and d2 are obtained. The transmission line equation includes: ； ； ； ； ； ； ； ； ； ； ； ； In the formula, , These are the real and imaginary parts of the phasor, respectively. The total ground capacitance impedance of the faulty collector line; The impedance of the faulty collector line; The zero-sequence voltage at the beginning of the faulty collector line; This refers to the zero-sequence current at the beginning of the faulty collector line; The zero-sequence voltage at the end of the faulty collector line; The solution whose value is in the interval [0, 1] is taken as the unique solution among the two real solutions d1 and d2; Substitute the unique solution into the actual line length calculation formula for conversion to obtain the fault distance; The zero-sequence voltage across the fault region satisfies the following expression: ； In the formula, This represents the total capacitance impedance to ground in the fault area. The impedance of the fault region; This is the fault distance ratio. ; , These are the zero-sequence voltage and zero-sequence current at the beginning of the fault region, respectively. The zero-sequence voltage at the end of the fault region; The wind farm collection line area is divided according to the node topology of the energy storage-supported wind power grid-connected collection line. The step of determining the target nodes associated with the sparse zero-sequence injection current in each wind farm collection line area, and identifying the area with the most target nodes as the fault area, includes: Within a preset time window, the number of target nodes that satisfy the sparse zero-sequence injection current in the wind farm collector line area is counted. The area of the wind farm's collection line where the target node appears within the preset time window is designated as the fault area.
2. The method as described in claim 1, characterized in that, The calculation steps for the sparse zero-sequence injection current include: Kalman filtering is applied to the three-phase voltage data to extract the zero-sequence component from the filtered three-phase voltage data, resulting in the zero-sequence voltage equation set: ； Based on the aforementioned zero-sequence voltage equations, a sparsity-underdetermined zero-sequence voltage equation set is constructed: ； In the formula, M is the voltage measuring device installed on node N. The zero-sequence voltage components are obtained from the voltages of M nodes containing measuring devices using the symmetrical component method. This is the zero-order node impedance matrix constructed based on the network topology. The virtual zero-sequence fault current is equivalently transformed from the actual fault current to the fault current at nodes m and n. The sparse, underdetermined zero-sequence voltage equations are solved using a compressed sensing algorithm to obtain sparse solutions. , which serves as the sparse zero-sequence injection current.
3. The method as described in claim 2, characterized in that, The sparse solution is obtained by solving the sparse underdetermined zero-sequence voltage equations using the compressed sensing algorithm. The steps specifically include: Initialize residual index set Support set , , Sparsity; Calculate the correlation coefficient using the inner product matching criterion: ； Select the 2k maximum values from u to form a set. Construct its corresponding column index ; Form a set based on the maximum value. The column indexes of and Update support set and index set ; Solving using the conjugate gradient method Optimal sparsity coefficients : ； Select Largest absolute value A set of elements ,Will The support set sequence containing each element is labeled as And record the corresponding serial number. ; Based on the support set sequence and serial number Update the index set and residuals ; Determine if it satisfies or If the condition is met, stop the iteration and obtain the reconstructed signal. Otherwise, let Return to continue iterating.
4. The method as described in claim 2, characterized in that, The steps for constructing the zero-sequence node impedance matrix include: Based on the topology and zero-sequence parameters of the energy storage-supported wind power grid-connected collection line, a zero-sequence equivalent network is drawn. Construct the zero-sequence node impedance matrix, and then form the corresponding observation matrix based on the specific distribution of the measurement points. ; ； In the formula, M represents the number of nodes containing the measuring device among the N nodes. This is the zero-sequence node impedance matrix formed based on the distribution of measurement points.
5. The application of the single-phase grounding fault location method based on compressed sensing for energy storage supporting wind power grid-connected collector lines as described in any one of claims 1 to 4 in single-phase grounding fault location.
6. A computer system, characterized in that, The computer system includes: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, it implements the steps of the method for locating single-phase grounding faults in the grid-connected wind power collection line based on compressed sensing, as described in any one of claims 1 to 4.
7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the method for locating single-phase grounding faults in grid-connected wind power collection lines based on compressed sensing, as described in any one of claims 1 to 4.