Power distribution switch remote control system applied to power transmission and distribution network

Abstract

The invention belongs to the field of power distribution switch control, relates to a data analysis technology, and is used for solving the problems that state monitoring cannot be carried out on a single power distribution switch and abnormal feature marking cannot be carried out in combination with a power distribution switch state monitoring result of a single power transmission and distribution line in the prior art. The power distribution switch remote control system comprises a remote control platform, and the remote control platform is in communication connection with a state monitoring module, a single line evaluation module, a single line screening module and a database. According to the method, the control objects in the screening objects are numbered according to the power transmission and distribution direction, and the variance calculation is performed on the serial number set of the abnormal objects to obtain the distribution coefficient, so that the spatial distribution characteristics of the abnormal objects on the transmission and distribution line can be accurately quantified; this enables the system to further distinguish whether anomalies are concentrated in a particular area or dispersed in different locations; the detailed abnormal feature marks greatly improve the accuracy and efficiency of fault diagnosis.

Description

Technical Field

[0001] This invention belongs to the field of power distribution switch control and involves data analysis technology. Specifically, it is a remote control system for power distribution switches applied to power transmission and distribution networks. Background Technology

[0002] Remote control systems for distribution switches are a core component of modern power distribution network automation. They enable intelligent management of the distribution network by remotely and centrally monitoring and controlling various switching devices distributed throughout the network. This system is evolving from traditional remote control functions to an intelligent power distribution management system with comprehensive perception, intelligent decision-making, and precise control, becoming a key infrastructure for building new power systems.

[0003] The invention patent with publication number CN118659393B discloses a power distribution system and a control method for its power distribution switches. This control method can realize the adaptive switching of the state of the power distribution switches when the power distribution system experiences intermittent load fluctuations, thereby improving the anti-interference capability of the power distribution system during the power distribution process. However, this control method cannot monitor the state of a single power distribution switch or mark abnormal features by combining the state monitoring results of the power distribution switches of a single transmission and distribution line, resulting in low efficiency in macroscopic fault location.

[0004] To address the aforementioned technical problems, this application proposes a solution. Summary of the Invention

[0005] The purpose of this invention is to provide a remote control system for distribution switches applied to power transmission and distribution networks, which solves the problem that existing technologies cannot monitor the status of a single distribution switch or mark abnormal features by combining the status monitoring results of distribution switches on a single power transmission and distribution line.

[0006] The technical problem to be solved by this invention is: how to provide a remote control system for distribution switches in power transmission and distribution networks that can mark abnormal features by combining the status monitoring results of distribution switches of a single power transmission and distribution line.

[0007] The objective of this invention can be achieved through the following technical solutions:

[0008] A remote control system for distribution switches applied in power transmission and distribution networks includes a remote control platform, which is communicatively connected to a status monitoring module, a single-line evaluation module, a single-line screening module, and a database.

[0009] The status monitoring module is used to perform status monitoring and analysis on the power distribution switches of the power transmission and distribution network: marking the power distribution switches of the power transmission and distribution network as monitoring objects, generating a monitoring cycle and setting several monitoring time points with equal time intervals within the monitoring cycle, obtaining the monitoring coefficient of the monitoring object at the monitoring time point, and marking the monitoring object as a normal object or an abnormal object through the monitoring coefficient;

[0010] The single-line evaluation module is used to evaluate and analyze the overall status of the distribution switch of a single transmission and distribution line in the power transmission and distribution network: the transmission and distribution line in the power transmission and distribution network is marked as the evaluation object, the evaluation coefficient is generated by the marking result of the monitoring object in the evaluation object, the evaluation coefficient is used to determine whether the overall status of the evaluation object meets the requirements, and if the requirements are not met, a single-line screening signal is generated and sent to the single-line screening module.

[0011] The single-line screening module is used to perform anomaly screening analysis on the screening targets.

[0012] Furthermore, the process of obtaining the monitoring coefficients of the monitored object includes: acquiring the loop data QL, control response data XK, and opening / closing data KH of the monitored object at the monitoring time point; constructing the monitoring data row vector HK at the monitoring time point from the loop data QL, control response data KX, and opening / closing data KH, where HK = [QL, KX, KH]; and generating a weighted column vector LK for the monitoring time point, where LK = [c1, c2, c3]. t Where c1, c2, and c3 are the weight coefficients corresponding to the flow data QL, the control data KX, and the opening and closing data KH, respectively, and t is the transpose of the column vector; the monitoring coefficient of the monitoring object is obtained by performing a dot product between the row vector HK of the monitoring data of all monitored objects at the monitoring time point and the weight column vector LK.

[0013] Furthermore, the process of acquiring coil current data QL includes: acquiring the coil current of the monitored object, retrieving the current standard range, marking the average of the maximum and minimum values ​​of the current standard range as the current standard value, and marking the absolute value of the difference between the coil current and the current standard value as the coil current data QL; the process of acquiring control response data KX includes: the monitoring period is composed of the current monitoring time point and the previous monitoring time point, acquiring the maximum value of the control response delay when the monitored object switches states within the monitoring period and marking it as the control response data KX; the process of acquiring opening and closing data KH includes: acquiring the opening and closing degree when the monitored object switches states within the monitoring period, marking the absolute value of the difference between the opening and closing degree and the standard opening degree of the corresponding opening and closing state of the monitored object as the opening and closing value, and marking the maximum value of the opening and closing value of the monitored object within the monitoring period as the opening and closing data KH.

[0014] Furthermore, the specific process of marking a monitored object as a normal or abnormal object includes: retrieving the monitoring threshold from the database, comparing the monitoring coefficient of the monitored object with the monitoring threshold; if the monitoring coefficient is less than the monitoring threshold, it is determined that the control status of the monitored object at the monitoring time point meets the requirements, and the corresponding monitored object is marked as a normal object; if the monitoring coefficient is greater than or equal to the monitoring threshold, it is determined that the control status of the monitored object at the monitoring time point does not meet the requirements, the corresponding monitored object is marked as an abnormal object, an immediate processing signal is generated, and the immediate control signal is sent to the mobile terminal of the management personnel.

[0015] Furthermore, the process of obtaining the evaluation coefficient of the evaluation object includes: marking the ratio of the number of abnormal objects corresponding to the evaluation object at the monitoring time point to the total number of monitored objects included in the evaluation object as the evaluation coefficient of the evaluation object.

[0016] Furthermore, the specific process for determining the overall status of the evaluation object includes: obtaining the evaluation threshold from the database, comparing the evaluation coefficient with the evaluation threshold; if the evaluation coefficient is less than the evaluation threshold, the overall status of the evaluation object is determined to meet the requirements; if the evaluation coefficient is greater than or equal to the evaluation threshold, the overall status of the evaluation object is determined to not meet the requirements, and the corresponding evaluation object is marked as a screening object.

[0017] Furthermore, the specific process of the single-line screening module to perform anomaly screening analysis on the screening objects includes: numbering the control objects in the screening objects according to the power transmission and distribution direction, forming an anomaly set by the serial numbers of all abnormal objects in the screening objects, calculating the variance of the anomaly set to obtain the distribution coefficient of the screening objects, and marking the abnormal characteristics of the screening objects through the distribution coefficient.

[0018] Furthermore, the specific process of marking the abnormal characteristics of the screening objects includes: obtaining the distribution threshold through the database, comparing the distribution coefficient with the distribution threshold; if the distribution coefficient is less than the distribution threshold, it indicates that the abnormal objects are concentrated, the abnormal characteristics of the screening objects are marked as regional environmental anomalies, a regional environmental optimization signal is generated and sent to the mobile terminal of the management personnel; if the distribution coefficient is greater than or equal to the distribution threshold, it indicates that the abnormal objects are dispersed, the abnormal characteristics of the screening objects are marked as end equipment faults, an end equipment diagnostic signal is generated and sent to the mobile terminal of the management personnel, and after receiving the end equipment diagnostic signal, the management personnel perform fault diagnosis on the substation or converter station connected to the screening object.

[0019] The present invention has the following beneficial effects:

[0020] 1. By comprehensively considering multiple dimensions of parameters, including current flow data, control response data, and opening / closing data, and assigning different weights based on their importance to the switch status, the obtained monitoring coefficients can comprehensively and accurately reflect the actual operating status of the distribution switches. This multi-parameter weighted fusion evaluation method overcomes the limitations of single-parameter evaluation, effectively avoids misjudgments or omissions caused by incomplete information, and significantly improves the accuracy and reliability of status monitoring. Therefore, it can provide a more solid data foundation when marking monitored objects as normal or abnormal, thereby providing more accurate input for subsequent single-line evaluation and anomaly screening, and enhancing the entire remote control system's ability to provide early warning and diagnosis of power transmission and distribution network faults.

[0021] 2. By using the ratio of the number of abnormal objects corresponding to the monitored time point to the total number of monitored objects within the assessed object as the assessment coefficient, this application provides an objective and quantitative method to measure the overall health status of transmission and distribution lines. This enables the single-line assessment module to determine the overall status of the assessed object based on clear numerical indicators, avoiding the bias of subjective judgment and significantly improving the accuracy and reliability of the assessment results. This quantitative assessment method can more effectively identify transmission and distribution lines with a high proportion of abnormal distribution switches, thereby providing more accurate screening targets for the subsequent single-line screening module and improving the efficiency of the entire remote control system in early warning and handling of transmission and distribution network faults.

[0022] 3. By numbering the control objects in the screening targets according to the power transmission and distribution direction, and calculating the variance of the set of abnormal object numbers to obtain the distribution coefficient, this application can accurately quantify the spatial distribution characteristics of abnormal objects on the power transmission and distribution lines. This enables the system to further distinguish whether the abnormality is concentrated in a specific area or scattered in different locations. This detailed abnormality feature marking greatly improves the accuracy and efficiency of fault diagnosis, enabling managers to take targeted maintenance measures based on the distribution pattern of the abnormality, avoiding blind investigation, and thus effectively reducing the time and cost of fault handling. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 This is a system block diagram of Embodiment 1 of the present invention;

[0025] Figure 2 This is a flowchart of the method in Embodiment 2 of the present invention. Detailed Implementation

[0026] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. 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.

[0027] In remote control systems for distribution switches, monitoring the status of individual switches is impossible, and the monitoring results from switches across a single transmission line cannot be integrated for anomaly identification. This results in low efficiency for macro-level fault location, impacting the stable operation and fault response capabilities of the distribution network. This problem stems from the lack of real-time data acquisition and analysis mechanisms for individual switches, as well as the comprehensive assessment capabilities for the status distribution of switches across the entire line. Consequently, the system struggles to distinguish between localized environmental anomalies and equipment malfunctions when faults occur, reducing the accuracy of maintenance decisions.

[0028] For example, in a 10kV transmission and distribution line in an urban power distribution network, multiple distribution switches are connected. When the line experiences load fluctuations, the existing system can only detect overall line anomalies but cannot identify changes in the status of specific distribution switches. Furthermore, the response delay of the switching equipment is caused by rising ambient temperature, but the system cannot monitor the control response data of individual switches, nor can it determine whether the abnormal characteristics are concentrated in a specific area or scattered based on the switch status distribution of the entire line. This forces maintenance personnel to conduct on-site inspections one by one, extending the fault handling cycle. Specifically, at the monitoring time point, the system cannot obtain the current-carrying data, control response data, and opening / closing data of individual switches, making it impossible to generate monitoring coefficients to mark normal or abnormal objects, and thus unable to effectively assess the overall status of the entire line.

[0029] If the above problems are not addressed, the distribution network will struggle to quickly locate and isolate fault points when they occur, potentially leading to a wider fault range and impacting the power supply continuity for more users. Furthermore, the lack of anomaly marker mechanisms will hinder data-driven operational and maintenance decisions, increasing unnecessary maintenance workload, reducing system efficiency, and impeding the evolution of the distribution network towards a comprehensive, intelligent, and precise distribution management system.

[0030] For ease of understanding, the following explains some key terms in this embodiment:

[0031] The remote control platform is a core component of the remote control system for power distribution switches, responsible for receiving, processing, and distributing various data and instructions. This platform typically connects to various functional modules and field devices via a communication network to achieve centralized management of the entire power transmission and distribution network.

[0032] The database stores operational data, historical data, configuration parameters, threshold information, and various analysis results of the power distribution switches. This database provides data support for each functional module, ensuring the integrity and traceability of the information required for system operation.

[0033] The monitored object refers to the distribution switch in the power transmission and distribution network that is selected for status monitoring and analysis in the status monitoring module. Each distribution switch can be designated as an independent monitored object.

[0034] The monitoring period refers to the time range within which the status monitoring module performs status monitoring and analysis on the monitored object. Within this period, the system will collect and analyze data according to preset time intervals.

[0035] Monitoring time points refer to the specific moments within a monitoring period when the status monitoring module collects data and makes status judgments. These time points are usually set at equal intervals.

[0036] The monitoring coefficient is a value obtained by the status monitoring module through comprehensive calculation of various data obtained by the monitored object at the monitoring time point. It is used to quantify the operating status of the monitored object.

[0037] The assessment object refers to a single transmission and distribution line in the power transmission and distribution network that is selected for overall condition assessment analysis in the single-line assessment module. A single transmission and distribution line can be designated as an assessment object.

[0038] The evaluation coefficient is a value obtained by the single-line evaluation module through statistical calculation of the marking results of the monitored objects included in the evaluation object. It is used to quantify the overall status of the evaluation object.

[0039] The single-line screening signal is a signal generated and sent to the single-line screening module when the single-line evaluation module determines that the overall state of the evaluation object does not meet the requirements. It is used to trigger subsequent anomaly screening analysis.

[0040] Screening targets refer to assessment targets selected by the single-line screening module for anomaly screening analysis after the single-line assessment module determines that the overall status does not meet the requirements.

[0041] Example 1: As Figure 1 As shown, a remote control system for distribution switches applied to power transmission and distribution networks includes a remote control platform, which is communicatively connected to a status monitoring module, a single-line evaluation module, a single-line screening module, and a database.

[0042] The status monitoring module is used to perform status monitoring and analysis on the distribution switches of the power transmission and distribution network. It marks the distribution switches as monitoring objects, generates a monitoring cycle, and sets several monitoring time points with equal time intervals within the monitoring cycle. At each monitoring time point, it acquires the coil current data QL, control response data XK, and opening / closing data KH of the monitored object. The acquisition process of the coil current data QL includes: obtaining the coil current of the monitored object, retrieving the current standard range, marking the average of the maximum and minimum values ​​of the current standard range as the current standard value, and marking the absolute value of the difference between the coil current and the current standard value as the coil current data QL. The acquisition process of the control response data KX includes: the monitoring period is composed of the current monitoring time point and the previous monitoring time point. The maximum control response delay of the monitored object during state switching within the monitoring period is obtained and marked as control response data KX. The process of obtaining opening and closing data KH includes: obtaining the opening and closing degree of the monitored object during state switching within the monitoring period; marking the absolute value of the difference between the opening and closing degree and the standard opening degree of the corresponding opening and closing state of the monitored object as the opening and closing value; and marking the maximum value of the opening and closing value of the monitored object within the monitoring period as opening and closing data KH. The monitoring data row vector HK for the monitoring time point is composed of the circulating data QL, control response data KX, and opening and closing data KH of the monitored object at the monitoring time point, HK=[QL, KX, KH]. A weighted column vector LK is generated for the monitoring time point, LK=[c1, c2, c3]. t Where c1, c2, and c3 are the weight coefficients corresponding to the flow data QL, control response data KX, and opening / closing data KH, respectively, and t is the transpose of the column vector. The monitoring coefficient of the monitoring object is obtained by performing a dot product calculation on the row vector HK of the monitoring data of all monitored objects at the monitoring time point and the weight column vector LK. The monitoring threshold is retrieved from the database, and the monitoring coefficient of the monitoring object is compared with the monitoring threshold. If the monitoring coefficient is less than the monitoring threshold, it is determined that the control status of the monitoring object at the monitoring time point meets the requirements, and the corresponding monitoring object is marked as a normal object. If the monitoring coefficient is greater than or equal to the monitoring threshold, it is determined that the control status of the monitoring object at the monitoring time point does not meet the requirements, and the corresponding monitoring object is marked as an abnormal object. An instant processing signal is generated and an instant control signal is sent to the mobile terminal of the management personnel.

[0043] The coil current data (QL) of the monitored object indicates the degree of abnormality in the coil current of the distribution switch. Coil current is a key parameter for the normal operation of the distribution switch, and its abnormality may indicate mechanical failure or deterioration of electrical performance in the switch mechanism. The coil current data (QL) can be obtained in various ways. For example, it can be obtained by real-time acquisition of coil current values ​​using a current sensor and comparison with a preset normal range, quantifying the deviation as data; or by analyzing historical data, establishing a statistical model of the coil current, and using the deviation between the current value and the model's predicted value as the coil current data (QL). The control response data (KX) reflects the timeliness and accuracy of the distribution switch's control response. The action response time of the distribution switch after receiving a control command is an important indicator of its performance. The control response data (KX) can be obtained by recording the time difference between the control command issuance and the switch action completion time using a timestamp; or by analyzing the changes in current and voltage waveforms during the switch action to identify action delays or jitter, and quantifying these as control response data (KX). The opening and closing data (KH) describes the accuracy of the opening and closing degree of the distribution switch. The opening and closing degree of a power distribution switch directly affects the circuit's continuity and insulation performance. The opening and closing data KH can be obtained by real-time monitoring of the switch contacts using position sensors and comparing the actual position with the standard opening degree, quantifying the deviation as data; alternatively, image recognition technology can be used to identify the switch's mechanical indicators, obtain their opening information, and calculate the difference from the standard value. The monitoring data row vector HK is a data structure that integrates multiple key operating parameters of the monitored object at a specific monitoring time point. Its function is to unify discrete, different types of state data into a multi-dimensional state description, facilitating subsequent comprehensive calculations and analysis. This vector can be constructed by directly arranging these data sequentially; or, in some implementations, these raw data can be preprocessed before constructing the vector to eliminate the influence of different data dimensions. The weighted column vector LK is used to assign different importance or influence to each component in the monitoring data row vector HK. Its function is to reflect the contribution of different operating parameters to the overall state assessment of the power distribution switch, making the assessment results more consistent with reality. The weighting coefficients c1, c2, and c3 can be determined using various methods, including expert experience, historical fault data analysis, and machine learning algorithms. The dot product is a mathematical operation that linearly combines two vectors, resulting in a scalar, i.e., the monitoring coefficient. This calculation aims to integrate multiple operational parameters of the monitored object at a given time point and their corresponding weights to obtain a single, quantifiable value reflecting the overall operational status of the monitored object.

[0044] This application's solution systematically collects three key operating parameters of the power distribution switch at each monitoring time point: current-carrying data QL, control response data KX, and opening / closing data KH. These parameters comprehensively reflect the real-time operating status of the power distribution switch from three dimensions: electrical performance, control response, and mechanical action. To effectively integrate and quantify this multi-dimensional information, this solution constructs a monitoring data row vector HK. Simultaneously, considering the varying degrees of influence of different operating parameters on the overall state of the power distribution switch, the system presets corresponding weighting coefficients c1, c2, and c3 for each parameter, organizing them into a weighted column vector LK. By performing a dot product calculation on the monitoring data row vector HK and the weighted column vector LK, multiple operating parameters of the power distribution switch and their importance can be comprehensively considered, resulting in a single monitoring coefficient with clear physical meaning. This monitoring coefficient is a comprehensive indicator that quantifies the overall health status or degree of abnormality of the power distribution switch at the current monitoring time point. This quantification process enables the status monitoring module to determine the control status of the monitored object based on a unified numerical value. This avoids the complexity and inconsistencies that can arise from judging multiple independent parameters separately, providing a precise and reliable basis for subsequently marking the monitored object as normal or abnormal. Compared to relying solely on a single parameter or simple threshold, this multi-parameter weighted comprehensive evaluation method can more comprehensively and accurately capture potential anomalies in power distribution switches, significantly improving the precision and accuracy of status monitoring.

[0045] The single-line evaluation module is used to evaluate and analyze the overall status of the distribution switches of a single transmission and distribution line in the power transmission and distribution network. It marks the transmission and distribution lines in the power transmission and distribution network as evaluation objects, and marks the ratio of the number of abnormal objects corresponding to the evaluation object at the monitoring time point to the total number of monitored objects within the evaluation object as the evaluation coefficient of the evaluation object. It obtains the evaluation threshold from the database and compares the evaluation coefficient with the evaluation threshold. If the evaluation coefficient is less than the evaluation threshold, the overall status of the evaluation object is determined to meet the requirements; if the evaluation coefficient is greater than or equal to the evaluation threshold, the overall status of the evaluation object is determined to not meet the requirements. The corresponding evaluation object is then marked as a screening object, a single-line screening signal is generated, and the single-line screening signal is sent to the single-line screening module.

[0046] Specifically, "the number of abnormal objects corresponding to the assessed object at the monitoring time point" refers to the total number of distribution switches (monitored objects) marked as abnormal by the status monitoring module in an assessed transmission and distribution line (assessed object) at a specific monitoring time point. This number is a direct indicator of the local abnormality of the transmission and distribution line. It can be obtained by traversing all monitoring objects within the assessed object and counting the number marked as abnormal; or by querying the database to filter out and count the monitoring object records belonging to the assessed object and whose status is abnormal. "The total number of monitoring objects contained within the assessed object" refers to the total number of all distribution switches (monitored objects) in an assessed transmission and distribution line (assessed object). This number represents the scale of the transmission and distribution line or the density of equipment contained therein. It can be obtained by pre-setting system configuration data; or by querying the database in real time to count all monitoring object records associated with the assessed object. "Ratio" refers to the mathematical relationship between two values, usually obtained through division. In this context, it quantifies the number of abnormal objects by comparing it to the total number, resulting in a value between 0 and 1 that intuitively reflects the density or proportion of abnormal situations. The "evaluation coefficient marked as an evaluation object" is a quantitative indicator calculated using the aforementioned ratio, used to characterize the overall health status of the evaluation object (transmission and distribution line) at a specific monitoring time point. This coefficient is the basis for subsequent determination of whether the overall status of the evaluation object meets the requirements. This marking process can either directly store the calculated ratio as the evaluation coefficient, or map the ratio to a preset evaluation coefficient range before storing it.

[0047] The single-line screening module is used to perform anomaly screening analysis on the screening objects: the control objects in the screening objects are numbered according to the power transmission and distribution direction, and an anomaly set is formed by the serial numbers of all abnormal objects in the screening objects. The variance of the anomaly set is calculated to obtain the distribution coefficient of the screening objects. The distribution threshold is obtained from the database, and the distribution coefficient is compared with the distribution threshold: if the distribution coefficient is less than the distribution threshold, the abnormal characteristics of the screening objects are marked as regional environmental anomalies, a regional environmental optimization signal is generated, and the regional environmental optimization signal is sent to the mobile terminal of the management personnel; if the distribution coefficient is greater than or equal to the distribution threshold, the abnormal characteristics of the screening objects are marked as end equipment faults, an end equipment diagnostic signal is generated, and the end equipment diagnostic signal is sent to the mobile terminal of the management personnel. After receiving the end equipment diagnostic signal, the management personnel perform fault diagnosis on the substation or converter station connected to the screening object.

[0048] This application further proposes a specific process for anomaly screening analysis of the screening objects using a single-line screening module. Specifically, the control objects in the screening objects are numbered according to the transmission and distribution direction, aiming to provide an ordered spatial or logical reference for subsequent anomaly analysis. For example, based on the physical connection sequence of the distribution switches on the transmission and distribution line, incrementally increasing integer numbers can be assigned from the power source side to the load side; or, in the case of branch lines, a hierarchical numbering method can be used to ensure that each control object has a unique identifier that reflects its relative position. An anomaly set is formed by the serial numbers of all anomaly objects in the screening objects. The purpose is to centralize the identifiers of all identified distribution switches with abnormal states for unified statistical analysis. This anomaly set can be a dynamic list, collecting the numbers of control objects marked as anomalies in real time during the monitoring period; or it can be a hash table for efficient storage and retrieval of the unique serial numbers of these anomaly objects. The variance of the anomaly set is calculated to obtain the distribution coefficient of the screening objects. This step is used to quantify the concentration or dispersion of anomalies on the screening objects (i.e., the transmission and distribution lines). Variance, as an important indicator in statistics, can effectively reflect the dispersion of data points. For example, the variance of the abnormal object serial number can be calculated using standard statistical formulas, or the value can be quickly obtained using existing mathematical calculation library functions. The abnormal characteristics of the screened objects are labeled using the distribution coefficient. Its function is to classify and describe the abnormal patterns exhibited by the screened objects based on the calculated distribution coefficient. For example, one or more thresholds can be set. When the distribution coefficient is less than a certain threshold, it is labeled as "regional environmental anomaly," indicating that the anomaly is concentrated in a small area; when the distribution coefficient is greater than or equal to the threshold, it is labeled as "end device failure," indicating that the anomaly is more dispersed and may involve multiple devices.

[0049] This application's solution overcomes the limitation of merely identifying line anomalies without pinpointing specific problem patterns by conducting deeper anomaly analysis on the screening targets. Specifically, when the single-line assessment module determines that the overall condition of a transmission and distribution line does not meet the requirements and marks it as a screening target, the single-line screening module initiates refined analysis. First, the system treats each distribution switch included in the screening target as a control object and systematically numbers them according to their actual transmission and distribution direction in the power grid. This numbering method provides a spatial reference for subsequent quantitative analysis, enabling the digitization of anomaly location information. Next, the system filters out all distribution switches marked as abnormal during monitoring from these numbered control objects and aggregates their corresponding numbers to form an anomaly set. Subsequently, variance calculation is performed on the numbers in this anomaly set to obtain a distribution coefficient. This distribution coefficient is a key indicator for measuring the degree of concentration or dispersion of anomalies along the entire transmission and distribution line. For example, a smaller distribution coefficient usually means that anomalies are spatially concentrated, possibly pointing to local environmental problems; while a larger distribution coefficient may indicate that anomalies are widely distributed, possibly related to general equipment failures. Ultimately, the system will use this calculated distribution coefficient to clearly label the abnormal characteristics of the screened objects, such as "abnormal regional environment" or "terminal equipment failure." This labeling not only indicates that there is an anomaly in the line, but also reveals the nature of the anomaly and its possible root causes, enabling managers to take more accurate and efficient troubleshooting and handling strategies based on the distribution pattern of the anomaly.

[0050] Example 2: Figure 2 As shown, a remote control method for distribution switches applied in power transmission and distribution networks includes the following steps:

[0051] Step 1: Perform status monitoring and analysis on the power distribution switches of the power transmission and distribution network: Mark the power distribution switches of the power transmission and distribution network as monitoring objects, generate a monitoring cycle, and set several monitoring time points with equal time intervals within the monitoring cycle. Obtain the monitoring coefficient of the monitoring object at the monitoring time point, and mark the monitoring object as a normal object or an abnormal object based on the monitoring coefficient.

[0052] Step 2: Evaluate and analyze the overall status of the distribution switches of a single transmission and distribution line in the power transmission and distribution network: Mark the transmission and distribution lines in the power transmission and distribution network as evaluation objects, obtain the evaluation coefficients of the evaluation objects, and mark the screening objects using the evaluation coefficients;

[0053] Step 3: Perform anomaly screening analysis on the screening objects: Obtain the distribution coefficient of the screening objects, and mark the abnormal characteristics of the screening objects through the distribution coefficient.

[0054] A remote control system for distribution switches in a power transmission and distribution network, during operation, marks the distribution switches in the power transmission and distribution network as monitoring objects, generates a monitoring cycle, and sets several monitoring time points with equal time intervals within the monitoring cycle. At each monitoring time point, the monitoring coefficient of the monitored object is obtained, and the monitored object is marked as a normal object or an abnormal object based on the monitoring coefficient. The transmission and distribution lines in the power transmission and distribution network are marked as evaluation objects, and the evaluation coefficient of the evaluation objects is obtained and used to mark the screening objects. The distribution coefficient of the screening objects is obtained, and the abnormal characteristics of the screening objects are marked based on the distribution coefficient.

[0055] The above description is merely an example and illustration of the structure of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the structure of the invention or exceed the scope defined in the claims, all of which should fall within the protection scope of the present invention.

[0056] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0057] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A remote control system for distribution switches applied in power transmission and distribution networks, characterized in that, It includes a remote control platform, which is communicatively connected to a status monitoring module, a single-line evaluation module, a single-line screening module, and a database; The status monitoring module is used to perform status monitoring and analysis on the power distribution switches of the power transmission and distribution network: marking the power distribution switches of the power transmission and distribution network as monitoring objects, generating a monitoring cycle and setting several monitoring time points with equal time intervals within the monitoring cycle, obtaining the monitoring coefficient of the monitoring object at the monitoring time point, and marking the monitoring object as a normal object or an abnormal object through the monitoring coefficient; The single-line evaluation module is used to evaluate and analyze the overall status of the distribution switch of a single transmission and distribution line in the power transmission and distribution network: the transmission and distribution line in the power transmission and distribution network is marked as the evaluation object, the evaluation coefficient is generated by the marking result of the monitoring object in the evaluation object, the evaluation coefficient is used to determine whether the overall status of the evaluation object meets the requirements, and if the requirements are not met, a single-line screening signal is generated and sent to the single-line screening module. The single-line screening module is used to perform anomaly screening analysis on the screening targets.

2. The remote control system for distribution switches applied to power transmission and distribution networks according to claim 1, characterized in that, The process of obtaining the monitoring coefficients of the monitored object includes: acquiring the monitoring object's loop flow data QL, control response data XK, and opening / closing data KH at the monitoring time point; constructing the monitoring data row vector HK at the monitoring time point from the monitoring object's loop flow data QL, control response data KX, and opening / closing data KH, where HK = [QL, KX, KH]; and generating a weighted column vector LK for the monitoring time point, where LK = [c1, c2, c3]. t Where c1, c2, and c3 are the weight coefficients corresponding to the flow data QL, the control data KX, and the opening and closing data KH, respectively, and t is the transpose of the column vector; the monitoring coefficient of the monitoring object is obtained by performing a dot product between the row vector HK of the monitoring data of all monitored objects at the monitoring time point and the weight column vector LK.

3. The remote control system for distribution switches applied to power transmission and distribution networks according to claim 2, characterized in that, The process of acquiring coil current data QL includes: acquiring the coil current of the monitored object, retrieving the current standard range, marking the average of the maximum and minimum values ​​of the current standard range as the current standard value, and marking the absolute value of the difference between the coil current and the current standard value as the coil current data QL; the process of acquiring control response data KX includes: the monitoring period is composed of the current monitoring time point and the previous monitoring time point, acquiring the maximum value of the control response delay when the monitored object switches states within the monitoring period and marking it as the control response data KX; the process of acquiring opening and closing data KH includes: acquiring the opening and closing degree when the monitored object switches states within the monitoring period, marking the absolute value of the difference between the opening and closing degree and the standard opening degree of the corresponding opening and closing state of the monitored object as the opening and closing value, and marking the maximum value of the opening and closing value of the monitored object within the monitoring period as the opening and closing data KH.

4. The remote control system for distribution switches applied to power transmission and distribution networks according to claim 3, characterized in that, The specific process of marking a monitored object as a normal or abnormal object includes: retrieving the monitoring threshold from the database, comparing the monitoring coefficient of the monitored object with the monitoring threshold; if the monitoring coefficient is less than the monitoring threshold, it is determined that the control status of the monitored object at the monitoring time point meets the requirements, and the corresponding monitored object is marked as a normal object; if the monitoring coefficient is greater than or equal to the monitoring threshold, it is determined that the control status of the monitored object at the monitoring time point does not meet the requirements, the corresponding monitored object is marked as an abnormal object, an immediate processing signal is generated, and the immediate control signal is sent to the mobile terminal of the management personnel.

5. A remote control system for distribution switches applied to power transmission and distribution networks according to claim 4, characterized in that, The process of obtaining the evaluation coefficient of the evaluation object includes: marking the ratio of the number of abnormal objects corresponding to the evaluation object at the monitoring time point to the total number of monitored objects included in the evaluation object as the evaluation coefficient of the evaluation object.

6. A remote control system for distribution switches applied to power transmission and distribution networks according to claim 5, characterized in that, The specific process for determining the overall status of the evaluation object includes: obtaining the evaluation threshold from the database, comparing the evaluation coefficient with the evaluation threshold; if the evaluation coefficient is less than the evaluation threshold, the overall status of the evaluation object is determined to meet the requirements; if the evaluation coefficient is greater than or equal to the evaluation threshold, the overall status of the evaluation object is determined to not meet the requirements, and the corresponding evaluation object is marked as a screening object.

7. A remote control system for distribution switches applied to power transmission and distribution networks according to claim 6, characterized in that, The specific process of the single-line screening module to perform anomaly screening analysis on the screening objects includes: numbering the control objects in the screening objects according to the power transmission and distribution direction; forming an anomaly set by the serial numbers of all abnormal objects in the screening objects; calculating the variance of the anomaly set to obtain the distribution coefficient of the screening objects; and marking the abnormal characteristics of the screening objects through the distribution coefficient.

8. A remote control system for distribution switches applied to power transmission and distribution networks according to claim 7, characterized in that, The specific process of marking the abnormal characteristics of the screening objects includes: obtaining the distribution threshold through the database, comparing the distribution coefficient with the distribution threshold; if the distribution coefficient is less than the distribution threshold, it indicates that the abnormal objects are concentrated, the abnormal characteristics of the screening objects are marked as regional environmental anomalies, a regional environmental optimization signal is generated and sent to the mobile terminal of the management personnel; if the distribution coefficient is greater than or equal to the distribution threshold, it indicates that the abnormal objects are dispersed, the abnormal characteristics of the screening objects are marked as end equipment faults, an end equipment diagnostic signal is generated and sent to the mobile terminal of the management personnel, and after receiving the end equipment diagnostic signal, the management personnel perform fault diagnosis on the substation or converter station connected to the screening object.

Images