A system and method for controlling line loss in substations based on big data

Abstract

The present application discloses a substation line loss control system and method based on big data, mainly relating to the technical field of data analysis, and is used to solve the technical problem that the existing technology cannot accurately control the line loss data of substations. It includes: an acquisition module for acquiring the line loss data uploaded by a preset substation; a processing module for determining the edge computing device corresponding to the preset substation and transmitting the substation data to the edge computing module; an edge computing module for determining the preset substations with abnormal line losses, generating line loss abnormal tasks, and sending them to the maintenance terminals corresponding to the substation identifiers; a visual monitoring module for displaying the line loss data of the preset substations with abnormal line losses and the status of the line loss abnormal tasks, and switching the status of the line loss abnormal tasks according to the data uploaded by the maintenance terminals. Through the above method, the present application realizes the timely discovery of voltage abnormalities and more intuitively and clearly displays the line loss data, enabling line loss management personnel to clearly master the line loss situation of substations.

Description

Technical Field

[0001] This application relates to the technical field of power data monitoring, and particularly to a substation line loss control system and method based on big data. Background Art

[0002] Line loss refers to the energy loss generated during the process of power transmission in a line. In the environment of a sharp increase in the demand for power resources, reducing losses and increasing efficiency has become an urgent goal for power enterprises to achieve.

[0003] At the present stage, the main methods for line loss control used by power enterprises to reduce losses and increase efficiency are as follows: line loss management personnel control the line losses of all substations through the integrated power quantity and line loss management system; control the power consumption of all substations through the power user power consumption information acquisition system; control the operation of substations through the State Grid system. Thereby realizing the reduction of power losses and the increase of efficiency.

[0004] However, due to the large number and large base of substations, any abnormal meter will affect the line loss, and the wiring of substations is complex and the site is disordered, etc. As a result, the substation line loss data obtained through the existing technology is very large and complex, and it is very difficult for line loss management personnel to accurately control the substation line loss data through the above systems. Summary of the Invention

[0005] In view of the above deficiencies of the prior art, the present invention provides a substation line loss control system and method based on big data to solve the above technical problems.

[0006] In a first aspect, an embodiment of the present application provides a substation line loss control system based on big data. The system includes: an acquisition module for acquiring substation data uploaded by a preset substation, where the substation data includes a substation identifier and line loss data; a processing module for determining, according to the substation identifier, an edge computing module corresponding to the preset substation and transmitting the substation data to the edge computing module; an edge computing module for determining whether there is a line loss anomaly in the preset substation according to the line loss data; when there is a line loss anomaly, generating a line loss anomaly task and sending it to a maintenance terminal corresponding to the preset substation; a visualization monitoring module for displaying the line loss data with a line loss anomaly, the status of the line loss anomaly task, and switching the status of the line loss anomaly task according to the status data uploaded by the maintenance terminal.

[0007] In an implementation manner of the present application, the line loss data includes cumulative voltage-dividing data, line loss rate data, and line loss power data.

[0008] In an implementation manner of the present application, the edge computing module includes a voltage division calculation unit, a line loss calculation unit, and an electricity quantity calculation unit; the voltage division calculation unit is used to determine the voltage division difference between the cumulative voltage division data and the year-on-year cumulative voltage division data of the previous month stored in advance according to the cumulative voltage division data; when the voltage division difference is greater than the preset voltage division difference threshold, it is determined that there is a line loss anomaly in the substation area; the line loss calculation unit is used to generate a line loss rate curve based on the line loss rate data; to determine whether there is a line loss anomaly in the preset substation area corresponding to the line loss rate data through the trained curve fluctuation algorithm; the electricity quantity calculation unit is used to determine whether there is a line loss anomaly in the preset substation area according to the relationship between the line loss electricity quantity data and the preset electricity quantity threshold.

[0009] In an implementation manner of the present application, the edge computing module further includes a waiting quantity unit and a transmission unit; the waiting quantity unit is used to monitor the quantity of substation area data waiting to be processed corresponding to the edge computing module; the transmission unit is used to determine the next edge computing module corresponding to the substation area data according to the preset substation area-edge computing database when the quantity of substation area data is greater than the preset quantity threshold, and send the substation area data to the next edge computing module.

[0010] In an implementation manner of the present application, the maintenance terminal at least includes any one or more of the following: a password verification protocol end, a computer end, and a mobile phone end.

[0011] In a second aspect, an embodiment of the present application provides a method for controlling the line loss of a substation area based on big data. The method includes: the server obtains the substation area data uploaded by the preset substation area, where the substation area data includes a substation area identifier and line loss data; the server determines the edge computing device corresponding to the preset substation area according to the substation area identifier, and transmits the substation area data to the edge computing device; the server determines whether there is a line loss anomaly in the preset substation area through the edge computing device and the line loss data; generates a line loss anomaly task through the edge computing device and sends it to the maintenance terminal corresponding to the preset substation area; the server displays the line loss data with a line loss anomaly, the status of the line loss anomaly task, and switches the status of the line loss anomaly task according to the status data uploaded by the maintenance terminal.

[0012] In an implementation manner of the present application, to determine the preset substation area with a line loss anomaly through the edge computing device and the line loss data specifically includes: the edge computing device determines the voltage division difference between the cumulative voltage division data and the year-on-year cumulative voltage division data of the previous month stored in advance according to the cumulative voltage division data; when the voltage division difference is greater than the preset voltage division difference threshold, it is determined that there is a line loss anomaly in the substation area; and / or, the edge computing device generates a line loss rate curve based on the line loss rate data; to determine whether there is a line loss anomaly in the preset substation area corresponding to the line loss rate data through the trained curve fluctuation algorithm; and / or, the edge computing device determines whether there is a line loss anomaly in the preset substation area according to the relationship between the line loss electricity quantity data and the preset electricity quantity threshold.

[0013] In one implementation of the present application, the method further includes: an edge computing device monitors the number of substation area data waiting to be processed; when the number of substation area data is greater than a preset number threshold, the edge computing device determines the next edge computing device corresponding to the substation area data according to a preset substation area - edge computing database, and sends the substation area data to the next edge computing device.

[0014] Those skilled in the art can understand that the aforementioned big data - based substation area line loss control system of the present disclosure has at least the following beneficial effects:

[0015] Through the processing module, the line loss data of several preset substation areas can be transmitted to different edge computing modules, avoiding the time loss caused by calculating all the preset substation area data on a single computing device, and improving the speed of processing line loss data. By calculating the line loss data through the edge computing module, abnormal line loss can be detected in a timely manner, monthly voltage division non - compliance can be avoided, suspected electricity theft households can be accurately verified on - site, more accurate substation area governance can be carried out, and economic losses can be reduced. Using the visual monitoring module, information such as power supply line loss data can be intuitively reflected. Through the visual monitoring and sorting of the substation area line loss, the latent information of the line loss data is presented more intuitively and clearly, enabling line loss management personnel to clearly master the substation area line loss situation. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The following describes some embodiments of the present disclosure with reference to the accompanying drawings, in which:

[0017] Figure 1 is a block diagram of a big data - based substation area line loss control system provided by an embodiment of the present application.

[0018] Figure 2 is a flowchart of a big data - based substation area line loss control method provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0019] Those skilled in the art should understand that the embodiments described below are only preferred embodiments of the present disclosure, and do not mean that the present disclosure can only be implemented through these preferred embodiments. These preferred embodiments are only used to explain the technical principles of the present disclosure, rather than to limit the protection scope of the present disclosure. Based on the preferred embodiments provided by the present disclosure, all other embodiments obtained by those of ordinary skill in the art without creative efforts should still fall within the protection scope of the present disclosure.

[0020] It should also be noted that the term "including", "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, commodity or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, commodity or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, commodity or device comprising said element.

[0021] Line loss refers to the energy loss generated during the process of power transmission in a line, which causes direct economic losses to enterprises. Reducing line loss and increasing efficiency has always been a task for our power grid enterprises. Due to the large number, large base, complex wiring and chaotic on-site conditions in the substations, it is very difficult for line loss management personnel to achieve precise control, and digital application products are urgently needed to assist.

[0022] Based on this, the embodiments of the present application provide a substation line loss control system and method based on big data to solve the above technical problems.

[0023] The technical solutions proposed in the embodiments of the present application will be described in detail below with reference to the accompanying drawings.

[0024] Figure 1 This is a substation line loss control system based on big data provided by the embodiments of the present application. As Figure 1 shown, the substation line loss control system provided by the embodiments of the present application mainly includes: an acquisition module 110, an acquisition module 110, an edge computing module 130, and a visualization monitoring module 140.

[0025] Among them, the acquisition module 110 can be any feasible device or apparatus capable of acquiring data, and is mainly used to acquire substation data uploaded by a preset substation. It should be noted that the substation data may include a substation identifier and line loss data. Among them, the substation identifier is unique, and the source of the substation data can be determined through the substation identifier. The line loss data may include a substation identifier, cumulative voltage division data, line loss rate data, and line loss power data. Among them, the cumulative voltage division data may be the cumulative voltage division value of the month / quarter corresponding to the preset substation. The line loss rate data may be the line loss rate values of each day of the month / quarter corresponding to the preset substation. The line loss power data may be the cumulative loss power of the month / quarter corresponding to the preset substation.

[0026] The processing module 120 can be any feasible device or apparatus capable of allocating the edge computing module 130 according to the substation area identifier and capable of data transmission. It is mainly used to determine the edge computing module 130 corresponding to the preset substation area according to the substation area identifier and transmit the substation area data to the edge computing module 130. As an example, the corresponding relationship between the substation area identifier and the edge computing module 130 is pre-stored in the processing module 120, so that the processing module 120 can determine the edge computing module 130 corresponding to the substation area identifier according to this corresponding relationship.

[0027] The edge computing module 130 can be any possible device capable of data calculation, etc., and the number of edge computing modules 130 can be increased or decreased according to actual needs. The edge computing module 130 is mainly used to determine the preset substation area with abnormal line loss according to the line loss data; generate a line loss abnormal task and send it to the maintenance terminal corresponding to the substation area identifier.

[0028] As an example, the edge computing module 130 includes a voltage division calculation unit 131, a line loss calculation unit 132, and a power calculation unit 133.

[0029] The voltage division calculation unit 131 is used to determine the voltage division difference between the cumulative voltage division data and the year-on-year cumulative voltage division data of the previous month according to the cumulative voltage division data and the pre-stored year-on-year cumulative voltage division data of the previous month; when the voltage division difference is greater than the preset voltage division difference threshold, it is determined that there is an abnormal line loss (abnormal voltage division value) in the substation area. Those skilled in the art can understand that if the voltage division this month exceeds the reasonable range compared with previous months, the problem point must occur on the day. Combining the line loss data of the substation area on that day, the abnormality can be detected in time, avoiding the unqualified monthly voltage division.

[0030] The line loss calculation unit 132 is used to generate a line loss rate curve according to the line loss rate data; and determine whether there is an abnormal line loss (abnormal line loss rate) in the preset substation area corresponding to the line loss rate data through the trained curve fluctuation algorithm. Specifically, the curve fluctuation algorithm is an algorithm that can determine whether there is a large fluctuation in the line loss rate curve in the near future according to the line loss rate curve. When it is detected that the line loss rate curve has a large fluctuation, it is determined that there is an abnormal line loss rate in the preset substation area corresponding to the line loss rate curve. Those skilled in the art can understand that according to the daily line loss rate data of the substation area, if the data suddenly shows a high loss, it is easier to detect and process, improving the daily loss qualification rate. Moreover, through preliminary verification and selection based on system power, meter codes, current and voltage, power and other data, it is possible to accurately verify suspected electricity theft households on site.

[0031] The power consumption calculation unit 133 is used to determine whether there is an abnormal power loss in the preset power distribution area according to the power loss data. Specifically, the edge computing module 130 compares the size relationship between the power loss data and the preset power threshold. When the power loss data is greater than the preset power threshold, it is determined that there is an abnormal power loss in the preset power distribution area. It should be noted that the power loss data can be the cumulative monthly power loss. The preset power threshold can be any feasible value. Those skilled in the art can understand that the above-mentioned power loss rate only reflects the ratio relationship between the loss power and the power supply amount, without considering the size of the loss power, and ignores the problems of large loss power distribution areas that need to be renovated and small economic benefits of small power consumption areas. The present invention can more accurately manage the power distribution area and reduce economic losses by counting the power distribution areas with monthly losses exceeding the preset power threshold.

[0032] In addition, in order to achieve the purpose of processing power distribution area data in a timely manner, when the number of data to be processed waiting in the edge computing module 130 of the present invention is too large, part of the power distribution area data can be transferred to other edge computing modules 130 for calculation.

[0033] As an example, the edge computing module 130 further includes a waiting quantity unit 134 and a transmission unit 135.

[0034] The waiting quantity unit 134 is used to monitor the quantity of power distribution area data to be processed corresponding to the edge computing module 130. The transmission unit 135 is used to determine the next edge computing module 130 corresponding to the power distribution area data according to the preset power distribution area - edge computing database when the quantity of power distribution area data is greater than the preset quantity threshold, and send the power distribution area data to the next edge computing module 130. It should be noted that the preset power distribution area - edge computing database is used to store the preset power distribution areas, edge computing modules 130, and several edge computing modules 130 corresponding to the preset power distribution areas. Those skilled in the art can obtain this preset power distribution area - edge computing database through multiple experiments.

[0035] When the edge computing module 130 determines that there is a power loss abnormality in the uploaded power distribution area data, a power loss abnormality task will be generated and sent to the maintenance terminal corresponding to the power distribution area identifier.

[0036] It should be noted that the power loss abnormality task contains the abnormal data detected by the edge computing module 130 to prompt the maintenance focus of the maintenance personnel corresponding to the maintenance terminal. The maintenance terminal includes at least any one or more of the following: password verification protocol end, computer end, mobile phone end.

[0037] The visual monitoring module 140 can be any feasible device capable of displaying data. This device is mainly used to display the power loss data of the preset power distribution area with power loss abnormalities and the status of the power loss abnormality task, and switch the status of the power loss abnormality task according to the status data uploaded by the maintenance terminal.

[0038] Based on the above description, those skilled in the art can understand that the present invention can transmit the line loss data of several preset power supply areas to different edge computing modules 130 through the processing module 120, avoiding the time loss caused by calculating all the data of the preset power supply areas on a single computing device, and improving the speed of processing line loss data. By calculating the line loss data through the edge computing module 130, line loss anomalies can be detected in a timely manner, monthly voltage division non-conformities can be avoided, suspected electricity theft households can be accurately verified on-site, and more precise management of power supply areas can be carried out, reducing economic losses. Using the visual monitoring module 140, information such as power supply line loss data can be intuitively reflected. Through the visual monitoring and sorting of the line loss of the power supply area, the latent information of the line loss data is presented more intuitively and clearly, enabling line loss management personnel to clearly master the line loss situation of the power supply area.

[0039] In addition, by using the analysis tool to visually display the power supply area data and handle anomalies in a timely manner, the end-of-month voltage division non-conformity can be avoided; the daily loss situation can be monitored, and it can assist in the investigation of electricity theft; large-loss power supply areas can be statistically identified, enabling precise management and reducing economic losses. It improves the level of line loss management, while enhancing the depth and breadth of data utilization. The analysis tool is easy to operate, the product has strong practicability and is easy to promote, providing a reference for line loss management personnel.

[0040] In addition, the embodiment of the present application also provides a method for controlling the line loss of a power supply area based on big data. As Figure 2 shown, the method for controlling the line loss of a power supply area provided by the embodiment of the present application mainly includes the following steps:

[0041] Step 201, the server obtains the power supply area data uploaded by the preset power supply area, where the power supply area data includes the power supply area identifier and the line loss data.

[0042] Step 202, the server determines the edge computing device corresponding to the preset power supply area according to the power supply area identifier, and transmits the power supply area data to the edge computing device.

[0043] Step 203, the server determines whether there is a line loss anomaly in the preset power supply area through the edge computing device and the line loss data; generates a line loss anomaly task through the edge computing device and sends it to the maintenance terminal corresponding to the power supply area identifier.

[0044] As an example, the edge computing device determines the voltage division difference between the cumulative voltage division data and the year-on-year cumulative voltage division data stored in the previous month according to the cumulative voltage division data; when the voltage division difference is greater than the preset voltage division difference threshold, it determines that there is a line loss anomaly in the power supply area; the edge computing device generates a line loss rate curve according to the line loss rate data; determines whether there is a line loss anomaly in the preset power supply area corresponding to the line loss rate data through the trained curve fluctuation algorithm; the edge computing device determines whether there is a line loss anomaly in the preset power supply area according to the magnitude relationship between the line loss power data and the preset power threshold.

[0045] In addition, in order to achieve the purpose of processing the data of the power distribution area in a timely manner, when the number of data waiting to be processed in the edge computing device of the present invention is too large, part of the data of the power distribution area can be transferred to other edge computing devices for calculation.

[0046] As an example, the edge computing device monitors the number of data of the power distribution area waiting to be processed; when the number of data of the power distribution area is greater than the preset number threshold, the edge computing device determines the next edge computing device corresponding to the data of the power distribution area according to the preset power distribution area-edge computing database, and sends the data of the power distribution area to the next edge computing device.

[0047] When the edge computing device determines that there is a line loss anomaly in the uploaded data of the power distribution area, a line loss anomaly task will be generated and sent to the maintenance terminal corresponding to the power distribution area identifier.

[0048] It should be noted that the line loss anomaly task includes the abnormal data detected by the edge computing device to prompt the maintenance focus of the maintenance personnel corresponding to the maintenance terminal. The maintenance terminal includes at least any one or more of the following: password verification protocol end, computer end, and mobile phone end.

[0049] Step 204: The server displays the line loss data with line loss anomalies, the status of the line loss anomaly task, and switches the status of the line loss anomaly task according to the status data uploaded by the maintenance terminal.

[0050] It should be noted that the status data can include any one of the following: waiting for maintenance status data, being maintained status data, and completed maintenance status data. The status of the line loss anomaly task includes waiting for maintenance status, being maintained status, and completed maintenance status.

[0051] So far, the technical solutions of the present disclosure have been described in combination with multiple foregoing embodiments. However, it is easy for those skilled in the art to understand that the protection scope of the present disclosure is not limited to these specific embodiments. Without departing from the technical principle of the present disclosure, those skilled in the art can split and combine the technical solutions in the above-mentioned various embodiments, and can also make equivalent changes or replacements to the relevant technical features. Any changes, equivalent replacements, improvements, etc. made within the technical concept and / or technical principle of the present disclosure will fall within the protection scope of the present disclosure.

Claims

1. A substation line loss control system based on big data, characterized in that, The system includes: An acquisition module, configured to acquire substation area data uploaded by a preset substation area, where the substation area data includes a substation area identifier and line loss data; A processing module, configured to determine, according to the substation area identifier, an edge computing module corresponding to the preset substation area, and transmit the substation area data to the edge computing module; The edge computing module is configured to determine whether there is a line loss anomaly in the preset substation area according to the line loss data; when there is a line loss anomaly, generate a line loss anomaly task and send it to a maintenance terminal corresponding to the preset substation area; A visualization monitoring module, configured to display the line loss data with a line loss anomaly, the status of the line loss anomaly task, and switch the status of the line loss anomaly task according to the status data uploaded by the maintenance terminal; The edge computing module further includes a waiting quantity unit and a transmission unit; The waiting quantity unit is configured to monitor the quantity of substation area data waiting to be processed corresponding to the edge computing module; The transmission unit is configured to, when the quantity of substation area data is greater than a preset quantity threshold, determine a next edge computing module corresponding to the substation area data according to a preset substation area - edge computing database, and send the substation area data to the next edge computing module.

2. The big data - based substation area line loss control system according to claim 1, wherein The line loss data at least includes: cumulative voltage - division data, line loss rate data, and line loss power data.

3. The system for controlling the line loss of a transformer substation area based on big data according to claim 2, wherein, The edge computing module includes a voltage - division calculation unit, a line loss calculation unit, and a power calculation unit; The voltage - division calculation unit is configured to, according to the cumulative voltage - division data and the pre - stored cumulative voltage - division data of the same month of the previous year; Determine the voltage - division difference between the cumulative voltage - division data and the cumulative voltage - division data of the same month of the previous year; when the voltage - division difference is greater than a preset voltage - division difference threshold, determine that there is a line loss anomaly in the substation area; The line loss calculation unit is configured to generate a line loss rate curve according to the line loss rate data; Use a trained curve fluctuation algorithm to determine whether there is a line loss anomaly in the preset substation area corresponding to the line loss rate data; The power calculation unit is configured to determine whether there is a line loss anomaly in the preset substation area according to the relationship between the line loss power data and a preset power threshold.

4. The system for controlling line loss in a substation area based on big data according to claim 1, wherein The maintenance terminal includes at least any one or more of the following: a password verification protocol terminal, a computer terminal, and a mobile phone terminal.

5. A method for controlling the line loss of a transformer substation area based on big data, characterized in that, The method includes: The server acquires substation area data uploaded by a preset substation area, where the substation area data includes a substation area identifier and line loss data; The server determines an edge computing device corresponding to the preset substation area according to the substation area identifier, and transmits the substation area data to the edge computing device; The server determines whether there is a line loss anomaly in the preset substation area through the edge computing device and the line loss data; generates a line loss anomaly task through the edge computing device and sends it to a maintenance terminal corresponding to the preset substation area; The server displays the line loss data with a line loss anomaly, the status of the line loss anomaly task, and switches the status of the line loss anomaly task according to the status data uploaded by the maintenance terminal; The method further includes: The edge computing device monitors the quantity of substation area data waiting to be processed. When the quantity of substation area data is greater than a preset quantity threshold, the edge computing device determines the next edge computing device corresponding to the substation area data according to a preset substation area-edge computing database, and sends the substation area data to the next edge computing device.

6. The method for controlling line loss of transformer substation area based on big data according to claim 5, characterized in that, The line loss data includes cumulative voltage-dividing data, line loss rate data, and line loss power data. The server determines whether there is a line loss anomaly in a preset substation area through the edge computing device and the line loss data, specifically including: The edge computing device determines a voltage-dividing difference between the cumulative voltage-dividing data and the year-on-year cumulative voltage-dividing data of the previous month according to the cumulative voltage-dividing data and the pre-stored year-on-year cumulative voltage-dividing data of the previous month; when the voltage-dividing difference is greater than a preset voltage-dividing difference threshold, it is determined that there is a line loss anomaly in the substation area; and / or, The edge computing device generates a line loss rate curve based on the line loss rate data; and determines whether there is a line loss anomaly in the preset substation area corresponding to the line loss rate data through a trained curve fluctuation algorithm; and / or, The edge computing device determines whether there is a line loss anomaly in the preset substation area according to the relationship between the line loss power data and a preset power threshold.

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