A power grid line loss real-time monitoring device and a detection system thereof

Abstract

A power grid line loss real-time monitoring device and its detection system belong to the technical field of power grid line loss monitoring. In order to solve the problem that the existing line loss analysis lacks real-time, comprehensiveness and accuracy, and cannot correctly evaluate the loss; the existing personnel cannot timely find the problems existing in line loss management, such as metering device error, collection error, transcription error, electricity stealing and the like, resulting in a large work intensity of the management personnel. The numerical value is compared with the set parameter, a warning alarm is sent out when the actual numerical value exceeds the set threshold, the numerical value monitoring efficiency is improved, the warning is effectively given according to the numerical value comparison, the line loss troubleshooting efficiency is improved, the cost of multi-party troubleshooting is reduced, various communications are used, the corresponding communication mode is selected according to the needs of different areas, the communication quality is effectively improved, the line loss situation is effectively understood, the line loss is intuitively and clearly understood through various chart modes, and the processing efficiency is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power grid line loss monitoring, and particularly relates to a power grid line loss real-time monitoring device and a detection system thereof. BACKGROUND

[0002] At present, power system loss calculation and analysis is based on the analysis and statistical calculation of line loss according to the meter reading of transformer substations, high-voltage special transformer users and low-voltage scattered households. Since the meter reading time cannot be unified, it belongs to post hoc conversion qualitative analysis.

[0003] 1. The existing line loss analysis lacks real-time, comprehensiveness and accuracy, and cannot correctly evaluate the loss.

[0004] 2. Secondly, the existing personnel cannot timely find the problems such as measurement device error, collection error, transcription error and electricity stealing in line loss management, resulting in a large work intensity of management personnel. SUMMARY

[0005] The present application aims to provide a power grid line loss real-time monitoring device and a detection system thereof, and compare the value with the set parameter. When the actual value exceeds the set threshold, a warning alarm is sent to improve the value monitoring efficiency, effectively warn according to the value comparison, improve the line loss troubleshooting efficiency, reduce the cost of multi-party troubleshooting, select the corresponding communication mode according to the needs of different regions through various communications, effectively improve the communication quality, effectively understand the line loss situation, and present through various charts, which can intuitively and clearly understand the loss and improve the processing efficiency, so as to solve the problems in the above background technology.

[0006] To achieve the above object, the present application provides the following technical scheme:

[0007] A power grid line loss real-time monitoring device and a detection system thereof, comprising:

[0008] A real-time monitoring device for monitoring line loss in the power grid;

[0009] The real-time monitoring device is provided with multiple groups, which are used for separate real-time monitoring of line loss at different positions in the power grid;

[0010] And a line loss detection system for calculating and analyzing the data monitored by the real-time monitoring device;

[0011] The line loss detection system processes and serves the results calculated and analyzed by the real-time monitoring device according to the line loss in the power grid.

[0012] Further, the real-time monitoring device comprises a temperature detection module, a voltage detection module, a current detection module, an oil pressure detection module, an environment detection module, a line loss detection module and an electric leakage detection module, and the temperature detection module, the voltage detection module, the current detection module, the oil pressure detection module, the environment detection module, the line loss detection module and the electric leakage detection module are set at multiple nodes in the power grid system in batches.

[0013] Further, the temperature detection module is used for monitoring the temperature of a transmission line in the power grid in real time, the voltage detection module is used for monitoring the movement of electric charges in the power grid, the current detection module is used for monitoring the current conducted between lines in the power grid, the oil pressure detection module is used for monitoring the oil pressure in a transmission in the power grid, the environment detection module is used for monitoring the environment in the entire power grid area, the line loss detection module is used for monitoring the line loss in the power grid, and the electric leakage detection module is used for monitoring and alarming the electric leakage between circuits.

[0014] Further, the electric leakage detection module further comprises the following electric leakage alarming steps, comprising:

[0015] Step 1: acquiring real-time positions and monitoring data of each node of the power grid system, and generating a position set W = x1, x2, x3, …, xn; i ; wherein,

[0016] x i represents the position parameter of the i-th node; W represents the position set; i ∈ n, there are n nodes, and i is a positive integer;

[0017] Step 2: establishing an adjacency matrix based on the power grid system according to the position set and the monitoring data;

[0018]

[0019] wherein, C i represents the monitoring value of the monitoring data of the i-th node;

[0020] Step 3: calculating a performance model of each node according to the adjacency matrix:

[0021]

[0022] wherein, H represents the monitoring value of the reference monitoring detection data of each position; and K represents the lowest threshold value of the monitoring value;

[0023] Step 4: constructing an electric leakage judgment model according to the performance model:

[0024]

[0025] When the performance model conforms to A1, it indicates that there is no electric leakage; when the performance model conforms to A2, it indicates that there is electric leakage.

[0026] Further, the multiple monitoring modules in the real-time monitoring device are detected by setting multiple groups of penetrating sensors, and each group of sensors is provided with a matching signal collector, and the signal collector is provided with a unified signal conversion module, which can convert the signals monitored by multiple types of sensors into a unified type of data signal for unified data collection, and the real-time monitoring device is further provided with a general control module for transmitting data in the multiple groups of detection modules, and the general control module is provided with a database for data backup storage.

[0027] Further, the line loss detection system includes a parameter setting module, a system interface module, a data entry module, a statistical calculation module, a data query module, a data analysis and processing module, a fault troubleshooting and early warning module, and an environment control module. The parameter setting module is used to set uniform parameters for multiple groups of detection data in the real-time monitoring device. The system interface module is used to access a remote system to transcribe and count data. The data entry module enters data detected by multiple monitoring systems in the real-time monitoring device, and the data entry module is further provided with a database for data storage. The statistical calculation module is used to calculate the statistical line loss rate of the power grid and various line loss sub-indicators. The data query module queries and retrieves the data stored in the data entry module in real time. The data analysis and processing module analyzes and processes the data detected by the real-time monitoring device. The fault troubleshooting and early warning module compares the analyzed indicators to perform early warning processing on data anomalies. The environment control module adjusts internal equipment in the environment according to the monitoring data indicators.

[0028] The data analysis and processing module is provided with a line loss analysis module for analyzing and calculating various line loss data, a graphical statistical module for statistically analyzing data, a graphical topology module for topology of analyzed data, and a report module for summarizing the above data.

[0029] Further, the power grid line loss real-time monitoring includes the following steps:

[0030] S1: Determine the range of the power grid for line loss detection, and plan the nodes to be detected in the power grid according to the power grid range;

[0031] S2: Set multiple detection devices in the real-time monitoring device on the planned nodes, and connect the communication system and the line loss detection system;

[0032] S3: Real-time monitoring equipment detects line loss data in the power grid in real time, and transmits the detected data to the line loss detection system through the communication system;

[0033] S4: The line loss detection system calculates and analyzes the real-time detected data, observes the line loss according to the drawing image, and realizes internal adjustment.

[0034] Further, the line loss detection system in S4 includes the following steps:

[0035] S401: The parameter setting module uniformly sets the accessed data in advance, which is used as a unified standard for collecting data;

[0036] S402: The system interface module accesses external systems for data collection and reception, and the received data is entered through the data entry module;

[0037] S403: The statistical calculation module calculates the entered data and gives the analyzed data parameters, and draws charts according to needs;

[0038] S404: The fault troubleshooting and early warning module compares the actual parameters with the unified parameters, and troubleshoots and warns according to the numerical difference.

[0039] Further, the statistical calculation module in S403 includes the following steps:

[0040] S4031: The line loss analysis module classifies various types of data, converts the divided data, calculates the line loss, and finally obtains the specific value of the line loss;

[0041] S4032: The graphic statistical module draws various types of graphs according to the performance needs of the obtained data;

[0042] S4033: The graph topology module displays the specific value of the line loss by drawing a topology graph;

[0043] S4034: The report module records the above data, archives and uploads each item of data in the form of a table.

[0044] Further, the report module includes:

[0045] Data specimen unit: used for setting a contrast recognition interface for the recorded data, respectively identifying different types of data, and obtaining data capacity, data source and data range value in the above data;

[0046] The weight unit is configured to generate a feature vector based on the data capacity, data source and data range value, calculate the correlation degree of any two adjacent contrast recognition interfaces based on the feature vectors recognized by the two adjacent contrast recognition interfaces at each time, and calculate the weight coefficient of each contrast recognition interface based on the correlation degree;

[0047] The influence coefficient calculation unit is configured to obtain data values of each contrast recognition interface at different times within a period of time, calculate the data influence coefficient of each contrast recognition interface based on the data values and weight coefficients of adjacent two contrast recognition interfaces;

[0048] The category division unit is configured to classify each contrast recognition interface based on the data influence coefficient to obtain multiple categories.

[0049] The recognition parameter calculation unit is configured to obtain feature data values in each category, calculate the state coefficient of each contrast recognition interface based on the feature data values, and calculate the contrast recognition parameter of each contrast recognition interface based on the data influence coefficient and the state coefficient of each contrast recognition interface in the same category.

[0050] The data anomaly recognition unit is configured to calculate the category weight coefficient of the contrast recognition interface in each category based on the contrast recognition parameter of each contrast recognition interface, obtain a data state value by weighted summation of the data capacity, data source and data range value in the category weight coefficient data, and perform data anomaly monitoring according to the data state value and a set threshold.

[0051] Compared with the prior art, the power grid line loss real-time monitoring equipment and the detection system thereof have the following beneficial effects:

[0052] 1、The power grid line loss real-time monitoring equipment and the detection system thereof, the signal collector is provided with a unified signal conversion module, which can convert the signals monitored by various sensors into a unified type of data signal for unified data collection.

[0053] 2、The power grid line loss real-time monitoring equipment and detection system thereof, the statistical calculation module is used for calculating the statistical line loss rate of the power grid and various line loss small indicators, the data query module is used for querying and calling the data stored in the data input module in real time, the data analysis processing module is used for analyzing and post-processing the data monitored by the real-time monitoring equipment, the fault troubleshooting and early warning module is used for comparing the indicators after analysis, early warning processing is performed on the data abnormal position, the environment control module can adjust the internal equipment in the environment according to the monitoring data indicators, the fault troubleshooting and early warning module obtains the analyzed values, and the values are compared with the set parameters, when the actual values exceed the set threshold, a warning alarm is sent, the value monitoring efficiency is improved, early warning is effectively performed according to value comparison, the line loss fault troubleshooting efficiency is improved, and the cost of multi-party troubleshooting is reduced.

[0054] 3、The power grid line loss real-time monitoring equipment and detection system thereof, according to the divided nodes, the real-time monitoring equipment is installed in multiple groups of monitoring modules. The line loss detection system and the real-time monitoring equipment are connected by a communication system for data transmission. The communication system includes various types, such as a wireless communication system or a wired communication system. The former uses electromagnetic wave propagation in free space, and the latter uses transmission mechanism in guided media. According to different communication services, the communication system can be divided into telephone communication system, data communication system, facsimile communication system and image communication system, etc. Through various communications, according to the needs of different areas, the corresponding communication mode is selected, and the communication quality is effectively improved.

[0055] 4、The power grid line loss real-time monitoring equipment and detection system thereof, the line loss analysis module is used for calculating the statistical line loss rate of the power grid and various line loss small indicators. The module automatically runs on the server side according to basic parameters. Only when the basic table data is adjusted or the statistical relationship is modified, manual statistical calculation is needed. The statistical relationship calculation module includes statistical relationship initialization, statistical relationship detection and statistical calculation. In order to compare and analyze various statistical line losses, it is convenient to find and solve various problems existing in management. The line loss analysis module can perform comparative analysis of the same period and the same period according to various indicators. The power consumption composition can also be analyzed. The graphical statistical module can visually display the statistical calculation results, generate curve graphs, bar graphs and pie charts according to requirements, calculate the line loss data in the region through the line loss analysis module, effectively understand the line loss situation, and display through various charts, so that the loss can be understood intuitively and clearly, and the processing efficiency is improved. BRIEF DESCRIPTION OF DRAWINGS

[0056] Figure 1 The overall module diagram of the present application;

[0057] Figure 2Module diagram of real-time monitoring equipment of the present application;

[0058] Figure 3 Module diagram of line loss detection system of the present application;

[0059] Figure 4 Module diagram of data analysis processing module of the present application;

[0060] Figure 5 Flow chart of the present application;

[0061] Figure 6 Flow chart of line loss detection system of the present application;

[0062] Figure 7 Flow chart of data analysis processing module of the present application.

[0063] In the figure: 1, real-time monitoring equipment; 11, temperature detection module; 12, voltage detection module; 13, current detection module; 14, oil pressure detection module; 15, environment detection module; 16, line loss detection module; 17, leakage detection module; 18, total control module; 2, line loss detection system; 21, parameter setting module; 22, system interface module; 23, data entry module; 24, statistical calculation module; 25, data query module; 26, data analysis processing module; 261, line loss analysis module; 262, graphical statistical module; 263, graphical topology module; 264, report module; 27, fault troubleshooting and early warning module; 28, environment control module. DETAILED DESCRIPTION

[0064] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all the other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of protection of the present application.

[0065] Please refer to Figure 1 A real-time monitoring equipment for power grid line loss, comprising:

[0066] The real-time monitoring device 1 for monitoring the line loss in the power grid needs to determine the area and range of the power grid before monitoring the line loss in the power grid, and the types of line loss in the determined range and the nodes to be monitored, and multiple groups of monitoring modules in the real-time monitoring device 1 are installed according to the divided nodes. The line loss detection system 2 and the real-time monitoring device 1 are connected by a communication system for data transmission. The communication system includes multiple types, such as a wireless communication system or a wired communication system. The former relies on the propagation of electromagnetic waves in free space, and the latter relies on the transmission mechanism in the guided media. According to different communication services, the communication system can be divided into telephone communication system, data communication system, facsimile communication system and image communication system, etc. Through multiple communications, the corresponding communication mode is selected according to the needs of different areas to effectively improve the communication quality.

[0067] Please refer to Figure 2 The temperature detection module 11 is used for real-time monitoring of the temperature of the transmission line in the power grid, the voltage detection module 12 is used for monitoring the movement of electric charge when the power grid is running, the current detection module 13 is used for monitoring the current conducted between the lines in the power grid, the oil pressure detection module 14 is used for monitoring the oil pressure in the transmission of the power grid, the environmental detection module 15 is used for monitoring the environmental conditions in the entire power grid area, the line loss detection module 16 is used for monitoring the line loss in the power grid, and the leakage detection module 17 is used for monitoring and alarming the leakage between the circuits. The above modules are used for power grid monitoring and have real-time monitoring of temperature, voltage, current, oil pressure, sunrise and sunset environment, line loss and leakage parameters at each position of the power grid. The detection data includes: electric meter whole point data (including reading, voltage and current, etc.), electric meter daily data (total, peak, flat, valley and sharp), electric meter power statistics data (year / month / day curve or report, report within any day), transformer substation loss data, transformer substation bus loss data, transformer substation main transformer loss data, transmission line loss data, etc. Multiple monitoring modules in the real-time monitoring device 1 are detected by setting multiple groups of sensors, and a matching signal collector is arranged on each group of sensors. A unified signal conversion module is arranged in the signal collector, which can convert the signals monitored by multiple types of sensors into a unified type of data signal for unified data collection. The real-time monitoring device 1 is also provided with a total control module 18 for transmitting data in multiple detection modules. The total control module 18 is provided with a database for data backup storage. Multiple and multiple groups of different types of sensors are used to detect multiple parameters to improve the detection type and achieve accurate loss positioning, and to ensure that the detected value and the actual value are within a certain range.

[0068] Please refer to Figure 3The parameter setting module 21 is used for setting unified parameters for a plurality of groups of detection data in the real-time monitoring device 1, and the parameter setting includes index qualified range, power grid parameter and statistical relationship parameter setting parts: the index qualified range sets the annual planned line loss rate index and the partial voltage line loss rate index; the power grid parameter sets voltage grade, centralized control station, transformer substation, main transformer, bus, line, feeder, large user and meter position parameters; the statistical relationship parameter is the basis for calculating various line losses, that is, the calculation formula in statistics, and the statistical relationship parameter sets various key point power amount statistical relationships, various bus power amount imbalance rates and partition, partial voltage, partial line and main transformer loss rates; the system has the following features in the statistical relationship parameter setting: one set of statistical relationship corresponds to a batch of data, the system sets various statistical relationships when being established, and then automatically copies the statistical relationships of the last month's data, and if adjustment is needed, local adjustment can be performed, and adjustment of this month's statistical relationships does not affect the statistical relationships and statistical results of the last month;

[0069] The system interface module 22 is used for accessing a remote system to copy and count data, the system interface module 22 is used for accessing data in a power amount remote meter reading system of a transformer substation, a marketing information management system and a load management system, improves the efficiency and accuracy of line loss counting work, a system interface module is designed to set the corresponding relationship between the system and power automation system data, so that the system automatically accesses real-time data and monthly data according to the set relationship, the data entry module 23 is used for entering data detected by a plurality of monitoring systems in the real-time monitoring device 1, and a database for storing data is further arranged in the data entry module 23, the statistical calculation module 24 is used for calculating the statistical line loss rate of the power grid and various line loss sub-indices, the data query module 25 is used for querying and calling the data stored in the data entry module 23 in real time, the data analysis processing module 26 is used for analyzing the data monitored by the real-time monitoring device 1, the fault troubleshooting and early warning module 27 is used for comparing the index after analysis, and is used for early warning processing of data abnormities, the environment control module 28 can adjust the internal equipment in the environment according to the monitoring data index, the analyzed value is obtained in the fault troubleshooting and early warning module 27, and the value is compared with the set parameter, when the actual value exceeds the set threshold value, a warning alarm is sent to improve the value monitoring efficiency, effectively early warning according to the value comparison, improve the line loss fault troubleshooting efficiency, and reduce the cost of multi-party troubleshooting.

[0070] Please refer to Figure 4The data analysis processing module 26 is provided with a line loss analysis module 261 for analyzing and calculating data of various line losses, a graph statistics module 262 for counting analyzed data, a graph topology module 263 for topology of analyzed data, and a report module 264 for summarizing the above data. The line loss analysis module 261 is used for calculating statistical line loss rate of the power grid and various line loss small indicators. The module is automatically run on the server side according to basic parameters. Only when the basic table data is adjusted or the statistical relationship is modified, manual statistical calculation is needed. The statistical relationship calculation module includes three parts of statistical relationship initialization, statistical relationship detection and statistical calculation. In order to compare and analyze various statistical line losses, facilitate timely discovery and solution of various problems existing in management, the line loss analysis module 261 can perform comparative analysis of same period and period comparison according to various indicators. The power consumption composition can also be analyzed. The graph statistics module 262 directly displays the statistical calculation results. Curve graph, bar graph and pie chart can be generated according to requirements. The line loss analysis module 261 is used for calculating line loss data in the region, effectively understanding line loss situation, and displaying through various charts, so that the loss can be directly and clearly understood, and the processing efficiency is improved.

[0071] Please refer to Figure 5 The real-time monitoring of the power grid line loss includes the following steps:

[0072] S1: Determine the range of the line loss detection power grid region, and plan the nodes to be detected in the power grid according to the power grid range;

[0073] S2: A variety of detection devices are arranged in the real-time monitoring device 1 on the planned nodes, and the communication system is connected between the line loss detection system 2;

[0074] S3: The real-time monitoring device 1 detects the line loss data in the power grid in real time, and transmits the detected data to the line loss detection system 2 through the communication system;

[0075] S4: The line loss detection system 2 calculates and analyzes the real-time detection data, draws images according to the line loss observation, and realizes internal adjustment.

[0076] Please refer to Figure 6 The detection method of the line loss detection system 2 in S4 includes the following steps:

[0077] S401: The parameter setting module 21 uniformly sets the parameters of the accessed data, which is used as a unified standard for collecting data;

[0078] S402: The system interface module 22 accesses external systems for data collection and reception. The received data is entered through the data entry module 23;

[0079] S403: The statistical calculation module 24 calculates the entered data and gives the analyzed data parameters, which are drawn into charts as needed;

[0080] S404: The troubleshooting and early warning module 27 compares the actual parameters with the unified parameters, and performs troubleshooting and early warning according to the numerical difference.

[0081] Please refer to Figure 7 , the statistical calculation module 24 in S403 analysis method includes the following steps:

[0082] S4031: The line loss analysis module 261 classifies various types of data, converts the classified data, calculates the line loss, and finally obtains the specific value of the line loss;

[0083] S4032: The graphic statistical module 262 draws various types of graphs according to the performance needs of the obtained data;

[0084] S4033: The graphic topology module 263 displays the specific value of the line loss by drawing a topology graph;

[0085] S4034: The report module 264 records the above data, archives and uploads each item of data in the form of a table.

[0086] In summary, the power grid line loss real-time monitoring equipment and its detection system, the signal collector is provided with a unified signal conversion module, which can convert the signals monitored by various sensors into a unified type of data signal for unified data collection, and the real-time monitoring equipment 1 is also provided with a total control module 18 for transmitting data in multiple detection modules, the total control module 18 is provided with a database for data backup storage, through multiple and multiple groups of different types of sensors, for detecting various parameters, improving the detection type, achieving accurate loss positioning, ensuring that the difference between the detected value and the actual value is within a certain range, the statistical calculation module 24 is used for calculating the statistical line loss rate of the power grid and various line loss small indicators, the data query module 25 is used for real-time query and retrieval of the data stored in the data input module 23, the data analysis processing module 26 is used for analyzing the data monitored by the real-time monitoring equipment 1, and the fault troubleshooting and early warning module 27 is used for comparing the analyzed indicators, for early warning processing of data abnormality, the environment control module 28 can adjust the internal equipment in the environment according to the monitoring data index; the fault troubleshooting and early warning module 27 obtains the analyzed value, and compares the value with the set parameter, when the actual value exceeds the set threshold, an early warning alarm is sent, the value monitoring efficiency is improved, the early warning is effectively carried out according to the value comparison, the line loss fault troubleshooting efficiency is improved, the cost of multi-party troubleshooting is reduced, and multiple monitoring modules in the real-time monitoring equipment 1 are installed according to the divided nodes.The line loss detection system 2 and the real-time monitoring device 1 are in data transmission by a communication system, which includes various types, such as a wireless communication system or a wired communication system, the former is by means of electromagnetic wave propagation in free space, and the latter is realized by transmission mechanism in guided media, according to different communication services, the communication system can be divided into telephone communication system, data communication system, facsimile communication system and image communication system, etc., through various communications, according to the needs of different areas, the corresponding communication mode is selected, and the communication quality is effectively improved, the line loss analysis module 261 is used for calculating the statistical line loss rate of the power grid and various line loss small indicators, the module is automatically operated on the server side according to the basic parameters, only when the basic table position data is adjusted or the statistical relationship is modified, manual statistical calculation is needed, the statistical relationship calculation module includes three parts of statistical relationship initialization, statistical relationship detection and statistical calculation; in order to compare and analyze various statistical line losses, it is convenient to timely find and solve various problems existing in management, the line loss analysis module 261 can perform comparative analysis of same period and period according to various indicators, and the power composition situation can also be analyzed; the graphic statistical module 262 directly displays the statistical calculation results, and can generate curve graph, bar graph and pie chart according to requirements, the line loss data in the region is calculated through the line loss analysis module 261, the line loss situation is effectively understood, the loss is directly and clearly understood through various chart modes, and the processing efficiency is improved.

[0087] Further, the leakage detection module further comprises the following leakage alarm steps, comprising:

[0088] Step 1: obtaining the real-time position and monitoring data of each node of the power grid system, generating a position set W=x1, x2, x3……x i ; wherein,

[0089] x i represents the position parameter of the i th node; W represents the position set; i∈n, there are n nodes, and i is a positive integer;

[0090] Step 2: establishing an adjacency matrix based on the power grid system according to the position set and the monitoring data;

[0091]

[0092] Wherein, C i represents the monitoring value of the monitoring data of the i th node;

[0093] Step 3: calculating the performance model of each node according to the adjacency matrix:

[0094]

[0095] Wherein, H represents the monitoring value of the reference monitoring detection data of each position; K represents the minimum threshold value of the monitoring value;

[0096] Step 4: According to the performance model, an electric leakage judgment model is constructed:

[0097]

[0098] Wherein, when the performance model meets A1, it represents that there is no electric leakage; when the performance model meets A2, it represents that there is electric leakage.

[0099] The electric leakage detection module of the present application is mainly used for monitoring and alarming. The monitoring and alarming of the prior art is mainly through voice alarm or automatic sending of alarm messages after failure. However, if the alarm device of the failure point is also damaged, electric leakage alarm cannot be realized. In order to solve this technical problem, the present application constructs an adjacency matrix of the power grid by the node positions and the monitoring data of the power grid system. The adjacency matrix is used to determine the correlation between different nodes. Since the present application does not alarm by the failure point itself, but judges whether there is electric leakage by the global monitoring data, the present application constructs a performance model, because the monitoring data is the performance parameter data of different nodes received by the system center. i C i H is the monitoring value of each position minus the reference monitoring value. Since this value is negative, the present application has square brackets, which is to ensure that the monitoring value exceeds the average monitoring value. If it does not exceed, it means that the performance is not good, but it does not mean that there is a failure. K is the minimum threshold value. If it is lower than this value, there may be a failure. Therefore, the performance model of the present application takes this minimum value as the minimum reference value, and the performance parameter is also calculated based on the reference performance parameter. In the electric leakage monitoring model, A1 represents that the monitoring value is greater than the performance parameter. In this case, it means that there is no electric leakage, because its performance must be higher than the minimum performance. A2 represents that the monitoring value is less than the performance parameter. In this case, it means that there is electric leakage, because its performance must be higher than the minimum performance.

[0100] Further, the report module comprises:

[0101] The data specimen unit is used for setting a contrast recognition interface for the recorded data, identifying different types of data respectively, and obtaining the data capacity, data source and data range value in the above-mentioned data;

[0102] The weight unit is used for generating a feature vector based on the data capacity, data source and data range value, calculating the correlation degree of any two adjacent contrast recognition interfaces based on the feature vectors identified by the adjacent two contrast recognition interfaces at each time, and calculating the weight coefficient of each contrast recognition interface based on the correlation degree;

[0103] The influence coefficient calculation unit respectively acquires data values of each contrast recognition interface at different time points within a period of time, and calculates data influence coefficients of each contrast recognition interface based on data values and weight coefficients of adjacent two contrast recognition interfaces;

[0104] The category division unit classifies each contrast recognition interface based on the data influence coefficients, and obtains multiple categories;

[0105] The recognition parameter calculation unit is used for respectively acquiring feature data values in each category, calculating state coefficients of each contrast recognition interface based on the feature data values, and calculating contrast recognition parameters of each contrast recognition interface based on data influence coefficients and state coefficients of each contrast recognition interface in the same category;

[0106] The data anomaly recognition unit calculates category weight coefficients of contrast recognition interfaces in each category based on the contrast recognition parameters of each contrast recognition interface, performs weighted summation on data capacity, data source and data range values in the category weight coefficient data to obtain a data state value, and performs data anomaly monitoring according to the data state value and a set threshold.

[0107] The principle of the above technical solution is that the report module mainly identifies the uploaded data to determine whether the uploaded data is abnormal. In this determination process, a contrast recognition interface is set in advance, the contrast recognition interface can recognize different types of data, and the information of the data, including "data capacity, data source and data range value", can be acquired when the data is uploaded. The weight unit is used to convert the feature quantity of the uploaded data, so as to determine the importance of the data in the form of weight value. The correlation degree is used to determine the correlation degree of each contrast recognition interface and other interfaces. The higher the correlation degree value is, the more important the recognized data is, so that the abnormal state value is larger when the anomaly is determined. The influence coefficient calculation unit is calculated based on the weight value, which can determine how high the influence coefficient of a data is. The influence coefficient, that is, the importance of the data, can classify the contrast recognition interfaces, and then determine the state coefficient of the data when each recognition interface identifies the data. The contrast recognition parameters can be obtained through these data. When the data anomaly is determined, the small abnormal state is expanded through weighted summation, so that the anomaly can be more accurately recognized when the data is uploaded.

[0108] The above technical solution has the beneficial effect that the anomaly can be recognized when the data is uploaded, and it is determined whether the data collected by the interface is in a normal state, so that the data can be screened when the data is uploaded, and it is determined whether there is a fault.

[0109] The above merely describes preferred specific embodiments of the present application, but the protection scope of the present application is not limited thereto, and any person skilled in the art, according to the technical solution and inventive concept of the present application, makes equivalent replacement or change within the technical range disclosed by the present application, should be covered within the protection scope of the present application.

Claims

1. A power grid line loss real-time monitoring device, characterized in that: The utility model relates to a line loss detection system (2) and real-time monitoring equipment (1), and the real-time monitoring equipment (1) is set up multiple groups, is used for the line loss in the power grid in different places and carries out separate real-time monitoring, and the line loss detection system (2) is used for calculating and analyzing the data monitored by the real-time monitoring equipment (1), and the line loss in the power grid is carried out targeted processing and service according to the result of the calculation and analysis of the monitoring data of the real-time monitoring equipment (1). The real-time monitoring equipment (1) includes temperature detection module (11), voltage detection module (12), current detection module (13), oil pressure detection module (14), environment detection module (15), line loss detection module (16) and electric leakage detection module (17), and temperature detection module (11), voltage detection module (12), current detection module (13), oil pressure detection module (14), environment detection module (15), line loss detection module (16) and electric leakage detection module (17) are set up in batches at multiple nodes in the power grid system. The electric leakage detection module (17) further includes the following electric leakage alarm steps, comprising: Step 2: according to the position set and monitoring data, an adjacency matrix based on the power grid system is established; Step 3: according to the adjacency matrix, the performance model of each node is calculated: Wherein, H represents the monitoring value of the reference monitoring detection data of each position; K represents the lowest threshold value of the monitoring value; Step 4: according to the performance model, an electric leakage judgment model is constructed: Step 1: Obtain real-time location and monitoring data of each node of the power grid system, generate a location set W = x1, x2, x3…x i ; wherein, x i Xi represents the position parameter of the ith node; W represents the position set, i ∈ n, there are n nodes in total, i is a positive integer; Wherein, when the performance model meets A1, it indicates that there is no electric leakage; when the performance model meets A2, it indicates that there is electric leakage. wherein C i represents the monitoring value of the monitoring data of the i-th node; The temperature detection module (11) is used for real-time monitoring the temperature of the transmission line in the power grid, the voltage detection module (12) is used for monitoring the electric charge movement when the power grid is running, the current detection module (13) is used for monitoring the current conducted between the lines in the power grid, the oil pressure detection module (14) is used for monitoring the oil pressure in the transmission of the power grid, the environment detection module (15) is used for monitoring the environment in the whole power grid area, the line loss detection module (16) is used for monitoring the line loss in the power grid, and the electric leakage detection module (17) is used for monitoring and alarming the electric leakage between the circuits. The real-time monitoring equipment (1) and the line loss detection system (2) are included, a plurality of monitoring modules in the real-time monitoring equipment (1) are detected by setting multiple groups of sensors, and a matching signal collector is arranged on each group of sensors, a unified signal conversion module is arranged in the signal collector, signals monitored by various sensors are converted into a unified type of data signal, data is uniformly collected, and a total control module (18) for transmitting data in the multiple groups of detection modules is further arranged in the real-time monitoring equipment (1), and a database for data backup storage is arranged in the total control module (18). ​ ​ 2. The power grid line loss real-time monitoring device according to claim 1, characterized in that: ​ 3. The detection system of the power grid line loss real-time monitoring device according to any one of claims 1-2, characterized in that: ​ 4. The detection system of the power grid line loss real-time monitoring device according to claim 3, characterized in that: The line loss detection system (2) comprises a parameter setting module (21), a system interface module (22), a data entry module (23), a statistical calculation module (24), a data query module (25), a data analysis and processing module (26), a fault troubleshooting and early warning module (27) and an environment control module (28). The parameter setting module (21) is used for setting uniform parameters for multiple groups of detection data in the real-time monitoring device (1). The system interface module (22) is used for accessing a remote system to transcribe and count data. The data entry module (23) is used for entering data detected by multiple monitoring systems in the real-time monitoring device (1), and a database for data storage is further arranged in the data entry module (23). The statistical calculation module (24) is used for calculating the statistical line loss rate of the power grid and various line loss sub-indicators. The data query module (25) is used for real-time querying and retrieving the data stored in the data entry module (23). The data analysis and processing module (26) is used for analyzing and post-processing the data monitored by the real-time monitoring device (1). The fault troubleshooting and early warning module (27) is used for comparing the analyzed indicators to perform early warning processing on data anomalies. The environment control module (28) can adjust the internal equipment in the environment according to the monitoring data indicators. The data analysis and processing module (26) is provided with a line loss analysis module (261) for analyzing and calculating various line loss data, a graph statistical module (262) for statistically analyzing the data, a graph topology module (263) for topologizing the analyzed data, and a report module (264) for aggregating and processing the analyzed data.

5. The detection system of the power grid line loss real-time monitoring device according to claim 4, characterized in that: The power grid line loss real-time monitoring comprises the following steps: S1: determining the power grid area range for line loss detection, and planning the nodes to be detected in the power grid according to the power grid range; S2: arranging various detection devices in the real-time monitoring device (1) on the planned nodes, and connecting the communication system and the line loss detection system (2); S3: the real-time monitoring device (1) detects the line loss data in the power grid in real time, and transmits the detected data to the line loss detection system (2) through the communication system; S4: the line loss detection system (2) calculates and analyzes the real-time detection data, observes the line loss according to the drawn images, and realizes internal adjustment.

6. The detection system of a power grid line loss real-time monitoring device according to claim 5, characterized in that: The line loss detection system (2) detection in S4 comprises the following steps: S401: the parameter setting module (21) uniformly sets the parameters of the accessed data, which is used as a unified standard for collecting data; S402: the system interface module (22) accesses the external system for data collection and reception, and the received data is entered through the data entry module (23); S403: the statistical calculation module (24) calculates the entered data and gives the data parameters after analysis, and draws charts according to needs; S404: the fault troubleshooting and early warning module (27) compares the actual parameters with the uniform parameters, and troubleshoots and warns according to the numerical difference.

7. The detection system of a power grid line loss real-time monitoring device according to claim 6, characterized in that: In S403, the statistical calculation module (24) analyzes, including the following steps: S4031: The line loss analysis module (261) classifies various types of data, converts the divided data, calculates the line loss, and finally obtains the specific value of the line loss; S4032: The graphic statistical module (262) draws various graphs according to the performance needs of the obtained data; S4033: The graphic topology module (263) displays the specific value of the line loss by drawing a topology graph; S4034: The report module (264) records the above data, archives and uploads each item of data in the form of a table.

8. The detection system of the power grid line loss real-time monitoring device according to claim 7, characterized in that: The report module includes: Data specimen unit: used to set a contrast recognition interface for the recorded data, identify different types of data respectively, and obtain the data capacity, data source and data range value in the above data; Weight unit: used to generate a feature vector based on the data capacity, data source and data range value, calculate the correlation degree of any two adjacent contrast recognition interfaces based on the feature vectors identified by the adjacent two contrast recognition interfaces at each time, and calculate the weight coefficient of each contrast recognition interface based on the correlation degree; Influence coefficient calculation unit: respectively obtain the data values of each contrast recognition interface at different times within a period of time, calculate the data influence coefficient of each contrast recognition interface based on the data values and weight coefficients of adjacent two contrast recognition interfaces; Class division unit: classify each contrast recognition interface based on the data influence coefficient to obtain multiple categories; Identification parameter calculation unit: used to respectively obtain feature data values in each category, calculate the state coefficient of each contrast recognition interface based on the feature data values; calculate the contrast recognition parameter of each contrast recognition interface based on the data influence coefficient and state coefficient of each contrast recognition interface in the same category; Data anomaly recognition unit: calculate the category weight coefficient of each category contrast recognition interface based on the contrast recognition parameter of each contrast recognition interface, weight sum the data capacity, data source and data range value in the category weight coefficient data to obtain the data state value, and perform data anomaly monitoring according to the data state value and the set threshold.

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