Remote control based outdoor primary and secondary fused pole-mounted circuit breaker

Abstract

The application belongs to the technical field of circuit breaker control, and relates to an outdoor primary and secondary fusion pole-mounted circuit breaker based on remote control. A fingerprint calibration module applies pulse excitation to each calibration port under different states and environmental conditions, and a complex wavelet transform is used to establish a complex time-frequency transfer fingerprint. A cause and effect attribution module converts three-phase voltage and current into abnormal tensors, matches fingerprints to inversely estimate equivalent interference input, determines interference cause and effect strength by constructing facts and counterfactuals to predict responses, and decomposes abnormal tensors into electromagnetic interference, faults and residuals in combination with fault correlation strength. An on-site protection module independently opens the circuit when the protection criterion is met and locks the remote closing. A remote closing verification module performs safety verification based on the circuit breaker state, the protection state and the attribution result. The application solves the problem that the primary and secondary fusion circuit breaker is difficult to distinguish the electromagnetic interference component from the fault component in abnormal electrical responses, which leads to the on-site protection being prone to misoperation and the remote closing being poor in safety.

Description

Technical Field

[0001] This invention belongs to the field of circuit breaker control technology and relates to an outdoor primary and secondary integrated pole-mounted circuit breaker based on remote control. Background Technology

[0002] Outdoor primary and secondary integrated pole-mounted circuit breakers typically integrate voltage sensors, current sensors, protection controllers, communication units, and opening and closing operating mechanisms. During circuit breaker operation, electromagnetic fields on the primary side, conducted interference in the secondary terminal area, and transient electromagnetic disturbances generated by the operation of the operating mechanism may enter the voltage and current sampling circuits through different coupling paths, causing abrupt amplitude changes, phase shifts, or high-frequency transient components in the acquired signals.

[0003] Existing protection devices typically determine line faults based on whether voltage, current amplitude, sequence components, or duration meet set conditions, making it difficult to distinguish between abnormal responses caused by electromagnetic interference and responses to actual faults. Misjudging electromagnetic interference as a fault may lead to unnecessary circuit breaker tripping; conversely, attributing a real fault to electromagnetic interference may increase the risk of missed fault detection and unsafe remote circuit breaker closing.

[0004] Therefore, there is a need for an outdoor primary and secondary integrated pole-mounted circuit breaker that can distinguish between electromagnetic interference and fault components in abnormal electrical responses without delaying local protection actions, and use the distinction results to constrain remote-controlled closing. Summary of the Invention

[0005] In view of this, an outdoor primary and secondary integrated pole-mounted circuit breaker based on remote control is proposed to solve the problem that primary and secondary integrated circuit breakers have difficulty distinguishing between electromagnetic interference components and fault components in abnormal electrical responses, which leads to easy false tripping of local protection and poor safety of remote closing.

[0006] The first aspect of the present invention proposes an outdoor primary and secondary integrated pole-mounted circuit breaker based on remote control, including a fingerprint calibration module, a cause-effect attribution module, a local protection module, and a remote control closing verification module.

[0007] The fingerprint calibration module is used to determine the complex time-frequency transmission relationship from each calibration port of the circuit breaker to each electrical channel through pulse excitation, and to form an electromagnetic interference fingerprint indexed according to the circuit breaker status and environmental conditions. The causal attribution module is used to acquire abnormal electrical responses, estimate the equivalent interference input of each calibrated port based on the electromagnetic interference fingerprint, form interference prediction based on the complex time-frequency transfer relationship, and determine the attribution result of abnormal electrical responses based on the interference prediction and the preset fault mechanism. The local protection module is used to output a tripping command when the local protection criteria are met, and to set a remote control closing lockout state; the local protection module has a higher execution priority than the causal attribution module. The remote control closing verification module is used to perform a safety verification based on the circuit breaker status, local protection criteria, and the attribution results of the causal attribution module after receiving a remote control closing request, and to generate a remote control closing permission.

[0008] Furthermore, the method for constructing the electromagnetic interference fingerprint includes: setting multiple environmental conditions under different circuit breaker states, and applying pulse excitation to the primary electromagnetic field calibration port, the secondary terminal area calibration port, and the operating mechanism calibration port under each combination of conditions; collecting the pulse excitation timing data and electrical response timing data of each calibration port, and processing them using the same complex wavelet transform parameters; determining the complex time-frequency transfer coefficient based on the corresponding complex wavelet coefficients of each calibration port and each electrical response channel, and associating the complex time-frequency transfer coefficient with the corresponding circuit breaker state and environmental parameters to construct the electromagnetic interference fingerprint.

[0009] Furthermore, the causal attribution module includes: estimating the equivalent interference input tensor based on the electromagnetic interference fingerprint and the acquired abnormal electrical response tensor, and forming a port source contribution tensor and an interference prediction tensor based on the equivalent interference input tensor; dividing the interference units according to the port source contribution tensor, and generating a factual prediction response and a counterfactual prediction response after removing the target interference unit; determining the causal effect strength of each interference unit based on the residual energy of the factual prediction response and the counterfactual prediction response relative to the abnormal electrical response tensor; constructing a fault-fidelity causal hypergraph based on the causal effect strength and a preset fault mechanism, and decomposing the abnormal electrical response tensor into electromagnetic interference components, fault components, and residual components through the fault-fidelity causal hypergraph.

[0010] Further, the formation of the port source contribution tensor and the interference prediction tensor includes: matching complex time-frequency transfer coefficients from the electromagnetic interference fingerprint based on the current circuit breaker state and environmental parameters; aligning the complex time-frequency transfer coefficients according to the time position and wavelet scale of the abnormal electrical response tensor; applying sparsity constraints to determine the equivalent interference input tensor with the objective of minimizing the difference between the superimposed response of the input complex wavelet coefficients of each calibrated port after mapping by the complex time-frequency transfer coefficients and the abnormal electrical response tensor; multiplying the equivalent interference input tensor by the complex time-frequency transfer coefficients of the corresponding electrical response channels to obtain the port source contribution tensor; and superimposing the port source contribution tensor along the port dimension to obtain the interference prediction tensor.

[0011] Furthermore, the preset fault mechanisms include single-phase grounding faults, phase-to-phase short-circuit faults, three-phase short-circuit faults, phase loss faults, and overload faults, as well as fault feature templates corresponding to each preset fault mechanism.

[0012] Furthermore, the fault-fidelity causal hypergraph includes time-frequency nodes, electromagnetic interference causal hyperedges, and fault hyperedges in the abnormal electrical response tensor; wherein, the time-frequency node corresponds to the complex wavelet coefficients of an electrical response channel at a time position and a wavelet scale; the electromagnetic interference causal hyperedge connects an interference unit and multiple time-frequency nodes located within the interference unit; the fault hyperedge connects a preset fault mechanism and multiple time-frequency nodes that conform to the corresponding fault feature template.

[0013] Furthermore, the step of decomposing the abnormal electrical response tensor into electromagnetic interference components, fault components, and residual components through a fault-fidelity causal hypergraph includes: obtaining the causal action strength of each electromagnetic interference causal hyperedge connected to each time-frequency node and the fault association strength of each fault hyperedge; allocating corresponding causal action strength and fault association strength according to the port source contribution ratio of each electromagnetic interference causal hyperedge at the time-frequency node and the fault feature template reconstruction contribution ratio of each fault hyperedge at the time-frequency node to obtain the node interpretation strength of each hyperedge; determining the decomposition weight of each hyperedge according to the node interpretation strength, and performing weighted reconstruction on the corresponding time-frequency node according to the decomposition weight of each hyperedge to obtain the electromagnetic interference components, fault components, and residual components.

[0014] Further, determining the decomposition weight of each hyperedge based on the node interpretation strength includes: when the sum of the node interpretation strengths of each hyperedge is not greater than one, determining each node interpretation strength as the decomposition weight of the corresponding candidate hyperedge, and determining the difference between one and the sum of the decomposition weights as the residual weight; when the sum of the node interpretation strengths of each hyperedge is greater than one, normalizing each node interpretation strength to obtain the decomposition weight of the corresponding hyperedge, and determining the residual weight as zero.

[0015] Furthermore, the method for obtaining the fault association strength includes: reconstructing the target time-frequency node set in the abnormal electrical response tensor based on the fault feature template corresponding to the target fault mechanism, and calculating the reduction in the reconstruction residual energy before and after introducing the fault feature template; determining the fault association strength of the corresponding fault superedge by using the proportion of the reduction in residual energy to the abnormal electrical response energy corresponding to the target time-frequency node set.

[0016] Furthermore, the causal attribution module also includes: performing threshold determination on the proportions of fault component energy, electromagnetic interference component energy, and residual component energy to the abnormal electrical response tensor energy to determine whether an electromagnetic interference alarm is triggered; the local protection module also includes: after the local protection criterion is released, performing threshold determination on the proportions of fault component energy and residual component energy to determine whether the remote control closing interlocking state is released.

[0017] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) The present invention determines the complex time-frequency transmission relationship of different electromagnetic interference sources entering the voltage and current sampling circuit through port pulse calibration, and estimates the equivalent interference input during operation through abnormal electrical response, so that the interference prediction result corresponds to the current abnormal event.

[0018] (2) The present invention constructs interference units by retaining the port source contribution tensor of the calibrated port source and forms counterfactual prediction response by removing the target interference unit, thereby determining the actual explanatory power of each interference unit for the abnormal response.

[0019] (3) The present invention separates electromagnetic interference contribution, fault contribution and unexplained residuals by fault feature template and fault fidelity causal hypergraph, which can reduce the risk of misclassifying real faults as electromagnetic interference.

[0020] (4) The present invention makes the local protection action and the causal attribution processing independent of each other, and uses the attribution results to constrain the remote control closing permission, thereby taking into account both the real-time nature of the protection action and the security of remote control. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the module structure of the outdoor primary and secondary integrated pole-mounted circuit breaker based on remote control according to the present invention. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] The specific solution of the remote-controlled outdoor primary and secondary integrated pole-mounted circuit breaker provided by the present invention will be described in detail below with reference to the accompanying drawings.

[0024] Example 1 See Figure 1 As shown, Figure 1 A schematic diagram of the modular structure of the outdoor primary and secondary integrated pole-mounted circuit breaker based on remote control in this embodiment is provided.

[0025] The outdoor primary and secondary integrated pole-mounted circuit breaker of this embodiment includes a primary breaking unit, a three-phase voltage sensor, a three-phase current sensor, an operating mechanism, a synchronous sampling circuit, a controller, a communication unit, a local protection output circuit, a remote control closing output circuit, and a calibration interface assembly.

[0026] The calibration interface assembly includes a primary electromagnetic field calibration port, a secondary terminal area calibration port, and an operating mechanism calibration port.

[0027] The primary electromagnetic field calibration port applies pulse excitation through a field coupling component that is electrically isolated from the primary conductive circuit to simulate interference from the primary electromagnetic field coupled to the sampling circuit.

[0028] The calibration port of the secondary terminal area is connected to or located adjacent to the secondary sampling terminal area through an isolation coupling component, and is used to simulate conducted interference or common-mode interference in the secondary terminal area.

[0029] The calibration port of the operating mechanism is connected to or located near the opening and closing coils and their control circuits through an isolation coupling component, in order to simulate transient interference generated by the operation of the operating mechanism.

[0030] The amplitude of the calibration pulse is limited to a value that does not trigger the local protection criterion, does not saturate the synchronous sampling circuit, and can be identified within the target analysis frequency band.

[0031] The three-phase voltage sensor and the three-phase current sensor are connected to a synchronous sampling circuit. The synchronous sampling circuit sends six channels of timing data of the three-phase voltage and three-phase current to the controller.

[0032] The local protection module, fingerprint calibration module, cause-effect attribution module, and remote control closing verification module are executed by the controller.

[0033] The local protection module has a higher execution priority than the causal attribution module, the communication unit, and the remote closing verification module.

[0034] S1, Construction of electromagnetic interference fingerprint.

[0035] Multiple environmental conditions are set for both the open and closed states of the circuit breaker. Environmental parameters may include temperature, humidity, control power supply voltage, and detection parameters that reflect the external electromagnetic environment.

[0036] Under each circuit breaker condition and environmental operating condition combination, pulse excitation is sequentially applied to each calibration port. Only one calibration port is applied at a time, and the next pulse excitation is applied after the electrical response of the previous pulse excitation has decayed to the steady-state noise range.

[0037] When the energy of each electrical response channel corresponding to the previous pulse excitation does not exceed the corresponding steady-state noise baseline for multiple consecutive detection windows, it is determined that the electrical response corresponding to the previous pulse has decayed to the steady-state noise range.

[0038] The pulse excitation timing data and electrical response timing data of each calibration port are collected synchronously. The electrical response timing data includes three-phase voltage and three-phase current timing data.

[0039] The pulse excitation timing data of each calibration port are arranged according to the calibration port dimension to form an interference input timing matrix: .

[0040] In the formula, To calibrate the number of ports, this embodiment... ; This represents the number of sampling points.

[0041] The three-phase voltage and three-phase current time-series data are arranged according to the electrical response channel dimension to form an electrical response time-series matrix: .

[0042] In the formula, In this embodiment, the number of electrical response channels is... These correspond to the three-phase voltage channel and the three-phase current channel, respectively. This represents the number of sampling points.

[0043] The same complex wavelet transform parameters are used to process the interference input timing matrix and the electrical response timing matrix respectively.

[0044] The sampling frequency should be no less than twice the highest frequency of the target analysis, and the complex wavelet type, scale set, window length, and boundary extension method should be kept consistent during the fingerprint calibration and operation phases.

[0045] For the calibration port and electrical response path, the complex time-frequency transfer coefficient is determined according to the following formula: .

[0046] In the formula, For calibrating the port To electrical response channel The complex time-frequency transfer coefficient; For calibrating the port Electrical response path under individual excitation The complex wavelet coefficients; For calibrating the port Complex wavelet coefficients; for The complex conjugate; To prevent positive numbers with a denominator of zero; For time location; It is a wavelet scale.

[0047] When multiple pulse excitations are applied repeatedly under the same operating condition, the final complex time-frequency transfer coefficient is determined by averaging the multiple obtained complex time-frequency transfer coefficients or by using the complex least squares method.

[0048] The amplitude gain is the magnitude of the complex time-frequency transfer coefficient, and the phase relationship is the argument of the complex time-frequency transfer coefficient.

[0049] The complex time-frequency transfer coefficients are associated with and stored with the corresponding circuit breaker status and environmental parameters to form an electromagnetic interference fingerprint.

[0050] S2, Generation of the anomalous electrical response tensor.

[0051] During operation, three-phase voltage and three-phase current are collected synchronously, the time-frequency energy of each electrical response channel within the sliding time window is calculated, and when the increment of the time-frequency energy relative to the corresponding steady-state energy baseline exceeds the abnormal trigger threshold, the corresponding sliding time window is determined as the abnormal response time window.

[0052] Electrical timing data within the abnormal response time window is extracted and processed using the same complex wavelet transform parameters as in the electromagnetic interference fingerprinting stage to obtain the abnormal electrical response tensor.

[0053] Time-frequency energy is represented as: .

[0054] In the formula, Electrical response channel At the wavelet scale Sliding time window Time-frequency energy within; For the first A sliding time window; Electrical response channel Complex wavelet coefficients; For time location; It is a wavelet scale.

[0055] Based on steady-state historical data under the same circuit breaker condition and similar environmental conditions, the steady-state energy baseline corresponding to each electrical response channel and each wavelet scale is determined.

[0056] When the time-frequency energy of at least one electrical response channel at at least one wavelet scale exceeds the sum of the corresponding steady-state energy baseline and the abnormal trigger threshold, and continues to reach the preset detection window number, the corresponding time range is determined as the abnormal response time window.

[0057] The abnormal triggering threshold is determined based on the statistical distribution of steady-state time-frequency energy under the same circuit breaker state and similar environmental conditions.

[0058] Extract the three-phase voltage and three-phase current time-series data within the abnormal response time window, and process them using the same complex wavelet transform parameters as in the fingerprint calibration stage to obtain the abnormal electrical response tensor: .

[0059] In the formula, For anomalous electrical response tensor; Number of electrical response channels; This represents the number of time positions within the abnormal response time window. This represents the number of wavelet scales.

[0060] S3, Determination of equivalent disturbance input and disturbance prediction tensor.

[0061] Based on the current circuit breaker status and current environmental parameters, the corresponding complex time-frequency transfer coefficient is matched from the electromagnetic interference fingerprint.

[0062] When the current environmental parameters are located between adjacent calibrated environmental conditions, the complex time-frequency transfer coefficients corresponding to the adjacent environmental conditions are interpolated.

[0063] Specifically, when the current environmental parameters are located between adjacent calibrated environmental conditions, linear interpolation is performed on the real and imaginary parts of the corresponding complex time-frequency transfer coefficients to obtain the complex time-frequency transfer coefficients corresponding to the current environmental parameters. For multidimensional environmental parameters, multidimensional linear interpolation or radial basis function interpolation methods are used.

[0064] When the current environmental parameters exceed the range of the calibrated environmental conditions, the complex time-frequency transfer coefficient corresponding to the calibrated environmental condition closest to the current environmental parameters is adopted, and the reliability of the complex time-frequency transfer coefficient is reduced, without performing unconstrained extrapolation.

[0065] The time-frequency coordinates of the complex time-frequency transfer coefficients are aligned according to the time position and wavelet scale of the abnormal electrical response tensor.

[0066] The objective is to minimize the difference between the superimposed response after mapping the complex time-frequency transfer coefficients of each calibration port and the tensor of the abnormal electrical response, and to apply sparsity constraints to determine the equivalent disturbance input tensor.

[0067] The objective function to be optimized is: .

[0068] In the formula, For the equivalent disturbance input tensor; For anomalous electrical response tensor; For calibrating the port Complex time-frequency transfer coefficients to each electrical response channel; For calibrating the port The corresponding equivalent interference input; This represents the complex product at the corresponding time position and wavelet scale. It is the Frobenius norm; The sparse constraint coefficient; for Norm; To calibrate the number of ports.

[0069] The validity of the complex time-frequency transfer coefficient is determined based on the signal-to-noise ratio and the degree of dispersion of the repeated calibration results.

[0070] The sparse constraint coefficient is determined based on the fitting results of the calibrated interference samples and the non-interference samples, in order to balance the interference prediction error and the number of activated interference units.

[0071] Sparse constraints are used to limit the number of calibrated ports and continuous time-frequency regions activated within the same anomalous response time window, in order to conform to the characteristic that electromagnetic interference typically produces the main response in a limited number of ports and a limited number of time-frequency regions.

[0072] The equivalent disturbance input tensor is obtained by solving the optimization objective function using the alternating direction multiplier method.

[0073] Multiply the equivalent disturbance input tensor by the complex time-frequency transfer coefficients of the corresponding electrical response channels to obtain the port source contribution tensor with dimensions of calibration port, electrical response channel, time position and wavelet scale; The port source contribution tensor is represented as: .

[0074] In the formula, Contribute tensors to the port source; For calibrating the port After complex time-frequency transfer coefficient mapping in the electrical response path Time and location wavelet scale Port source contribution; For complex time-frequency transfer coefficients; For calibrating the port In time location wavelet scale The equivalent interference input complex wavelet coefficients at the location.

[0075] By superimposing the port source contribution tensor along the calibration port dimension, we obtain the interference prediction tensor with the dimensions of electrical response channel, time location, and wavelet scale.

[0076] Both the interference prediction tensor and the anomalous electrical response tensor have three dimensions: electrical response channel, time location, and wavelet scale.

[0077] S4, interference unit and causal effect strength.

[0078] Screen and retain the complex wavelet coefficients in the port source contribution tensor that are higher than the corresponding steady-state noise threshold.

[0079] For the filtered complex wavelet coefficients, the set of complex wavelet coefficients that are continuous in time position and continuous in wavelet scale are divided into the same interference unit. An interference unit can be distributed to one or more electrical response channels, but has a unique calibration port source.

[0080] The interference prediction tensor that retains all interference units is determined as the fact prediction response.

[0081] The counterfactual prediction response is obtained by removing the port source contribution corresponding to the target interference unit from the factual prediction response.

[0082] The increase in residual energy of the predicted response before and after removal relative to the tensor of the anomalous electrical response is calculated, and the causal effect strength of the corresponding electromagnetic interference causal superedge is determined by the proportion of the increase in residual energy to the anomalous electrical response energy within the effective range of the target interference unit.

[0083] The residual energy of the predicted response relative to the anomalous electrical response tensor is: .

[0084] The residual energy of the counterfactual predicted response relative to the anomalous electrical response tensor is: .

[0085] The causal interaction strength of the target interference element is: .

[0086] In the formula, For target jamming unit The residual energy of the factual predicted response relative to the tensor of the anomalous electrical response; Interference unit Scope of application; For time-frequency nodes; For the anomalous electrical response tensor at time-frequency nodes The value at; Predicting responses at time and frequency nodes based on facts The value at that location.

[0087] To remove the target jamming unit The residual energy of the counterfactual predicted response relative to the anomalous electrical response tensor; To predict counterfactual responses at time and frequency nodes The value at that location.

[0088] For target jamming unit The strength of causal effect; To prevent positive numbers with a denominator of zero.

[0089] The causal effect strength is limited to the range of 0 to 1. The greater the increase in residual energy after removing the target interference element, the stronger the explanatory power of the interference element for the abnormal electrical response.

[0090] S5, Fault Feature Template and Fault Association Strength.

[0091] The preset fault mechanisms include single-phase grounding fault, phase-to-phase short circuit fault, three-phase short circuit fault, phase loss fault, and overload fault.

[0092] Each fault mechanism corresponds to at least one fault feature template. Fault feature templates can be obtained from confirmed fault test data, simulation data verified by field data, or historical fault waveform data verified by manual verification.

[0093] The fault feature template includes a fault waveform morphology template and matching constraints.

[0094] The fault waveform template It means that among them For the number of electrical response channels, The number of time and location parameters for the fault template. The number of wavelet scales represents the number of wavelet scales. It contains the normalized complex wavelet coefficients of each electrical response channel at different time positions and wavelet scales, used to characterize the typical time-frequency waveform morphology of this fault mechanism; this template has been energy normalized and does not contain actual fault amplitude information.

[0095] The matching constraints include: channel activation mode: limiting which electrical response channels should have significant responses and which channels should approach zero; channel amplitude ratio: limiting the range of ratios of complex wavelet coefficient moduli between activated channels; channel phase relationship: limiting the range of differences in the arguments of complex wavelet coefficients between activated channels; characteristic wavelet scale range: limiting the wavelet scale range in which the main energy of the fault mechanism is concentrated.

[0096] During fault matching, only when the anomalous electrical response tensor is in the corresponding time-frequency node set... Only after all the above matching constraints are met simultaneously will the fault hyperedge be added to the fault-fidelity causal hypergraph. The time-frequency node set Limited to the time position and wavelet scale within the specified characteristic wavelet scale interval.

[0097] The fault feature templates are aligned with the time position and wavelet scale according to the abnormal response time window, and the corresponding template amplitude is determined by least squares fitting.

[0098] The fault correlation strength is: .

[0099] in, , .

[0100] In the formula, Fault mechanism The strength of the fault association; Before introducing the fault feature template, the squared residual Frobenius norm of the fault feature template reconstructed response and the anomalous electrical response tensor on the target time-frequency node set is... To introduce a fault feature template and determine the template amplitude using least-squares fitting, the squared Frobenius norm of the residual between the reconstructed response and the anomalous electrical response tensor on the target time-frequency node set is calculated. The template magnitude coefficients are determined by least squares fitting. Target Fault Mechanism The corresponding set of time-frequency nodes.

[0101] The fault association strength is limited to the range of 0 to 1.

[0102] A corresponding fault superedge is established only when the target time-frequency node set simultaneously satisfies the channel activation mode, amplitude ratio, phase relationship, and feature scale range defined by the corresponding fault feature template.

[0103] S6, Fault-Fidelity Causal Hypergraph and Tensor Decomposition.

[0104] Fault-fidelity causal hypergraphs include time-frequency nodes, electromagnetic interference causal hyperedges, and fault hyperedges.

[0105] Each time-frequency node corresponds to an electrical response channel with anomalous electrical response complex wavelet coefficients at a time location and wavelet scale; Each electromagnetic interference causal hyperedge connects an interference unit and multiple time-frequency nodes within the interference unit's range, and is used to characterize the causal effect of the interference unit on multiple time-frequency nodes. Each fault hyperedge connects a preset fault mechanism and multiple time-frequency nodes that conform to the corresponding fault feature template, which is used to characterize the correlation between multiple time-frequency nodes that jointly satisfy the corresponding fault mechanism.

[0106] Based on the port source contribution ratio of each electromagnetic interference causal hyperedge at the time-frequency node and the fault template reconstruction contribution ratio of each fault hyperedge at the time-frequency node, the corresponding causal action strength and fault association strength are allocated to the time-frequency node to obtain the node interpretation strength of each candidate hyperedge.

[0107] When the sum of the node interpretation strengths of each candidate hyperedge is not greater than 1, the node interpretation strength is determined as the decomposition weight of the corresponding candidate hyperedge, and the difference between 1 and the sum of the decomposition weights is determined as the residual weight.

[0108] When the sum of the node interpretation strengths of each candidate hyperedge is greater than 1, the node interpretation strengths are normalized to obtain the decomposition weights of the corresponding candidate hyperedges, and the residual weights are set to zero.

[0109] The electromagnetic interference components are obtained by weighting and reconstructing the corresponding time-frequency nodes based on the decomposition weights of each electromagnetic interference causal hyperedge.

[0110] Based on the decomposition weights of each fault hyperedge, the corresponding time-frequency nodes are weighted and reconstructed to obtain the fault components; The corresponding time-frequency nodes are reconstructed using the residual weights to obtain the residual components.

[0111] The nodal interpretation strength of the causal hyperedge of electromagnetic interference is: .

[0112] In the formula, For electromagnetic interference causal superedge At time-frequency nodes The strength of the node interpretation at that location; Interference unit The strength of causal effect; For target jamming unit At time-frequency nodes The corresponding port source contribution; For the anomalous electrical response tensor at time-frequency nodes The value at that location.

[0113] The node interpretation strength of a faulty hyperedge is: .

[0114] In the formula, For faulty overedge At time-frequency nodes The strength of the node interpretation at that location; Fault mechanism The strength of the fault association; For fault feature templates at time-frequency nodes The reconstruction contribution.

[0115] The reconstruction contribution refers to the reconstructed complex wavelet coefficients formed at each time-frequency node after the fault feature template is fitted with least squares to determine the optimal amplitude coefficients. .

[0116] when At that time, the decomposition weight of each candidate hyperedge is equal to the interpretation strength of the corresponding node, and the residual weight is: .

[0117] In the formula, For residual weights, The sum of the strengths is explained for candidate superedge nodes.

[0118] when At that time, the residual weight is zero.

[0119] The electromagnetic interference components are: .

[0120] The fault components are: .

[0121] The residual components are: .

[0122] In the formula, Time-frequency node Electromagnetic interference components at the location; For the anomalous electrical response tensor at time-frequency nodes The value at; For electromagnetic interference causal superedge At time-frequency nodes Decomposition weights at each location; Time-frequency node Fault components at the location; For faulty overedge At time-frequency nodes Decomposition weights at each location; Time-frequency node The residual components at the location.

[0123] When there are no reliable electromagnetic interference causal extrapolation edges or fault extrapolation edges, all abnormal electrical responses of the corresponding time-frequency nodes are attributed to the residual components.

[0124] S7, local protection and remote closing verification.

[0125] The causal attribution module further includes: determining the threshold values ​​of the proportions of fault component energy, electromagnetic interference component energy, and residual component energy to the abnormal electrical response tensor energy to determine whether an electromagnetic interference alarm is triggered. The local protection module further includes: after the local protection criterion is released, a threshold judgment is made on the energy ratio of the fault component and the energy ratio of the residual component to determine whether to release the remote control closing interlock state.

[0126] When the local protection module has already output a trip command, the attribution result output by the causal attribution module does not cancel the trip command.

[0127] An electromagnetic interference alarm is generated when the proportion of fault component energy to abnormal electrical response tensor energy is lower than the fault determination threshold, the proportion of electromagnetic interference component energy to abnormal electrical response tensor energy is higher than the interference determination threshold, and the proportion of residual component energy to abnormal electrical response tensor energy is lower than the residual confidence threshold.

[0128] After the local protection criterion is released, the remote control closing interlocking state is released only when the circuit breaker is in the open state, the operating mechanism is in normal state, the fault component energy ratio and the residual component energy ratio continuously meet the corresponding permissible threshold, and there is no new protection start signal or abnormal response.

[0129] When the remote control closing verification module successfully authenticates the remote control command and the circuit breaker status, protection status, and interlocking status all meet the closing conditions, it generates a remote control closing permission that is valid only for the current remote control closing request.

[0130] The local protection module independently receives three-phase voltage and three-phase current sampling data and executes instantaneous overcurrent protection, overcurrent protection, grounding protection, undervoltage protection or other protection criteria applicable to the target power distribution line.

[0131] When any local protection criterion with tripping authority is met, the local protection module directly outputs a tripping command and sets the remote control closing interlock status.

[0132] If the cause-effect attribution module has not yet started processing, is processing, or has already output electromagnetic interference attribution results, the already output tripping command will not be revoked.

[0133] The energy ratio of the electromagnetic interference components is: .

[0134] The energy ratio of the fault component is: .

[0135] The residual component energy ratio is: .

[0136] In the formula, The proportion of electromagnetic interference component energy; For electromagnetic interference component tensors; The proportion of fault component energy; For fault component tensors; The energy ratio of the residual components; For residual component tensors; For anomalous electrical response tensor; It is the Frobenius norm.

[0137] The fault determination threshold, interference determination threshold, and residual confidence threshold are determined based on pure electromagnetic interference samples, pure fault samples, and samples of electromagnetic interference and fault superposition.

[0138] After the protection criteria are released, the remote control closing lockout status is not directly released.

[0139] The remote control closing verification module shall verify at least the following conditions: The circuit breaker is in the open position; The operating mechanism and control power supply are in normal condition; The in-situ protection criterion has been overturned; The proportion of fault component energy is below the fault clearance threshold for multiple consecutive confirmation windows. The residual component energy ratio is below the residual allowable threshold for multiple consecutive confirmation windows; There are no new protection activation signals or abnormal responses; The source, authority, and validity of the remote closing command have been verified.

[0140] When all the above conditions are met, the remote control closing interlock is released, and a remote control closing permission is generated that is valid only for the current remote control closing request.

[0141] The remote control closing permission expires when the closing action is performed once, the permission validity period expires, or any security verification condition is no longer met.

[0142] In this embodiment, the values ​​of each threshold are as follows: fault determination threshold is 0.3, interference determination threshold is 0.6, residual confidence threshold is 0.1; fault tolerance threshold is 0.1, and residual tolerance threshold is 0.15. These thresholds can be adjusted according to specific application scenarios and line parameters.

[0143] It should be noted that the above parameters are stored separately according to the circuit breaker status and environmental conditions, and can be calibrated based on subsequently confirmed operating samples. However, parameter calibration must not affect the protection settings and independent operation logic of the local protection module.

[0144] This disclosure also provides a computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform a method according to an embodiment of this disclosure.

[0145] In general, the various exemplary embodiments of this disclosure can be implemented in hardware, dedicated circuitry, software, firmware, logic, or any combination thereof. Some aspects can be implemented in hardware, while others can be implemented in firmware or software that can be executed by a controller, microprocessor, or other computing device. When aspects of the embodiments of this disclosure are illustrated or described as block diagrams, flowcharts, or using some other graphical representation, it will be understood that the blocks, apparatuses, systems, techniques, or methods described herein can be implemented as non-limiting examples in hardware, software, firmware, dedicated circuitry or logic, general-purpose hardware or controllers or other computing devices, or some combination thereof.

[0146] It should be noted that the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0147] The exemplary embodiments of this disclosure described in detail above are merely illustrative and not restrictive. Those skilled in the art will understand that equivalent modifications and combinations of these embodiments or their features can be made without departing from the principles and spirit of this disclosure, and such modifications should fall within the scope of this disclosure.

Claims

1. An outdoor primary and secondary integrated pole-mounted circuit breaker based on remote control, characterized in that, include: The fingerprint calibration module is used to determine the complex time-frequency transmission relationship from each calibration port of the circuit breaker to each electrical channel through pulse excitation, and to form an electromagnetic interference fingerprint indexed according to the circuit breaker status and environmental conditions. The causal attribution module is used to acquire abnormal electrical responses, estimate the equivalent interference input of each calibrated port based on the electromagnetic interference fingerprint, form interference prediction based on the complex time-frequency transfer relationship, and determine the attribution result of abnormal electrical responses based on the interference prediction and the preset fault mechanism. The local protection module is used to output a tripping command when the local protection criteria are met, and to set the remote control closing interlock status. The local protection module has a higher execution priority than the causal attribution module; The remote control closing verification module is used to perform a safety verification based on the circuit breaker status, local protection criteria, and the attribution results of the causal attribution module after receiving a remote control closing request, and to generate a remote control closing permission.

2. The outdoor primary and secondary integrated pole-mounted circuit breaker based on remote control as described in claim 1, characterized in that, The method for constructing the electromagnetic interference fingerprint includes: Multiple environmental conditions are set under different circuit breaker states, and pulse excitation is applied to the primary side electromagnetic field calibration port, the secondary terminal area calibration port, and the operating mechanism calibration port under each combination of conditions. The pulse excitation timing data and electrical response timing data of each calibration port are collected and processed using the same complex wavelet transform parameters; The complex time-frequency transfer coefficients are determined based on the corresponding complex wavelet coefficients of each calibration port and each electrical response channel, and the complex time-frequency transfer coefficients are associated with the corresponding circuit breaker status and environmental parameters to construct an electromagnetic interference fingerprint.

3. The outdoor primary and secondary integrated pole-mounted circuit breaker based on remote control as described in claim 2, characterized in that, The causal attribution module includes: Based on the electromagnetic interference fingerprint, the equivalent interference input tensor is estimated based on the acquired abnormal electrical response tensor, and the port source contribution tensor and interference prediction tensor are formed based on the equivalent interference input tensor. The interference units are divided according to the port source contribution tensor, and the fact prediction response and the counterfactual prediction response after removing the target interference unit are generated respectively. The causal effect strength of each disturbance unit is determined based on the residual energy of the factual and counterfactual predicted responses relative to the tensor of the anomalous electrical response. Based on the causal action strength and the pre-defined fault mechanism, a fault-fidelity causal hypergraph is constructed, and the abnormal electrical response tensor is decomposed into electromagnetic interference components, fault components and residual components through the fault-fidelity causal hypergraph.

4. The outdoor primary and secondary integrated pole-mounted circuit breaker based on remote control as described in claim 3, characterized in that, The formation of the port source contribution tensor and the interference prediction tensor includes: Based on the current circuit breaker status and environmental parameters, the complex time-frequency transfer coefficient is matched from the electromagnetic interference fingerprint; The complex time-frequency transfer coefficients are aligned in time-frequency coordinates according to the time position and wavelet scale of the anomalous electrical response tensor. With the goal of minimizing the difference between the superposition response of the input complex wavelet coefficients of each calibration port after mapping through the complex time-frequency transfer coefficients and the tensor of the abnormal electrical response, sparse constraints are applied to determine the equivalent disturbance input tensor. The equivalent disturbance input tensor is multiplied by the complex time-frequency transfer coefficients of the corresponding electrical response channels to obtain the port source contribution tensor. The interference prediction tensor is obtained by superimposing the port source contribution tensor along the port dimension.

5. The outdoor primary and secondary integrated pole-mounted circuit breaker based on remote control as described in claim 3, characterized in that, The preset fault mechanisms include single-phase grounding fault, phase-to-phase short-circuit fault, three-phase short-circuit fault, phase loss fault, and overload fault, as well as fault feature templates corresponding to each preset fault mechanism.

6. The outdoor primary and secondary integrated pole-mounted circuit breaker based on remote control as described in claim 3, characterized in that, The fault-fidelity causal hypergraph includes time-frequency nodes, electromagnetic interference causal hyperedges, and fault hyperedges in the abnormal electrical response tensor; wherein, a time-frequency node corresponds to the complex wavelet coefficients of an electrical response channel at a time position and a wavelet scale; an electromagnetic interference causal hyperedge connects an interference unit and multiple time-frequency nodes located within the interference unit; and a fault hyperedge connects a preset fault mechanism and multiple time-frequency nodes that conform to the corresponding fault feature template.

7. The outdoor primary and secondary integrated pole-mounted circuit breaker based on remote control as described in claim 6, characterized in that, The decomposition of the anomalous electrical response tensor into electromagnetic interference components, fault components, and residual components using a fault-fidelity causal hypergraph includes: Obtain the causal effect strength of each electromagnetic interference causal hyperedge connected to each time-frequency node and the fault correlation strength of each fault hyperedge; Based on the proportion of port source contribution of each electromagnetic interference causal hyperedge at the time-frequency node and the proportion of fault feature template reconstruction contribution of each fault hyperedge at the time-frequency node, the corresponding causal action strength and fault association strength are assigned to obtain the node interpretation strength of each hyperedge. The decomposition weights of each hyperedge are determined based on the node interpretation strength, and the corresponding time-frequency nodes are reconstructed by weighting according to the decomposition weights of each hyperedge to obtain the electromagnetic interference component, fault component and residual component.

8. The outdoor primary and secondary integrated pole-mounted circuit breaker based on remote control as described in claim 7, characterized in that, The process of determining the decomposition weights of each hyperedge based on the node interpretation strength includes: When the sum of the node interpretation strengths of each hyperedge is not greater than one, the node interpretation strength is determined as the decomposition weight of the corresponding candidate hyperedge, and the difference between one and the sum of the decomposition weights is determined as the residual weight. When the sum of the node interpretation strengths of each hyperedge is greater than one, the node interpretation strengths are normalized to obtain the decomposition weights of the corresponding hyperedges, and the residual weights are set to zero.

9. The outdoor primary and secondary integrated pole-mounted circuit breaker based on remote control as described in claim 7, characterized in that, The method for obtaining the fault correlation strength includes: Based on the fault feature template corresponding to the target fault mechanism, the target time-frequency node set in the abnormal electrical response tensor is reconstructed, and the reduction in the reconstruction residual energy before and after introducing the fault feature template is calculated. The fault association strength of the corresponding fault superedge is determined by the proportion of the residual energy reduction to the abnormal electrical response energy of the target time-frequency node set.

10. The outdoor primary and secondary integrated pole-mounted circuit breaker based on remote control as described in claim 9, characterized in that, The causal attribution module further includes: determining the threshold values ​​of the proportions of fault component energy, electromagnetic interference component energy, and residual component energy to the abnormal electrical response tensor energy to determine whether an electromagnetic interference alarm is triggered. The local protection module further includes: after the local protection criterion is released, a threshold judgment is made on the energy ratio of the fault component and the energy ratio of the residual component to determine whether to release the remote control closing interlock state.

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