An artificial intelligence-based power grid dispatching comprehensive management system

Abstract

This invention discloses an artificial intelligence-based integrated power grid dispatching management system. Based on the cooperation of a data acquisition subsystem, a data processing subsystem, and a remote dispatching subsystem, it achieves remote intelligent power dispatching by acquiring and analyzing power data from the front end of the power grid. This enhances the control of technical personnel over the entire power grid system and simplifies equipment operation and maintenance procedures. By setting up a safety decision-making subsystem, it monitors the status of the area under the jurisdiction of the power grid dispatching agency in real time, preventing unnecessary economic losses caused by potential safety hazards within the area. Furthermore, maintenance personnel do not need to constantly visit remote sites to check equipment status, effectively mitigating safety risks for maintenance personnel.

Description

Technical Field

[0001] This invention relates to the field of integrated power grid dispatching and management technology, and specifically to an integrated power grid dispatching and management system based on artificial intelligence. Background Technology

[0002] Power grid dispatching refers to the organization, command, guidance, and coordination of power grid operation by power grid dispatching agencies to ensure the safe, high-quality, and economical operation of the power grid. With the development of microelectronics, computer, and communication technologies, integrated automation technology has also developed rapidly. Integrated automation has become a hot topic, attracting attention and importance from various sectors of the power industry, and has become one of the key areas for technological advancement in my country's power industry. Power grid dispatching integrated management adopts more remote centralized control, centralized operation, and anti-accident measures, utilizing modern computer and communication technologies to provide advanced technical equipment. This can change the traditional secondary equipment model, achieve information sharing, simplify the system, reduce cables, reduce floor space, and facilitate timely monitoring of the operation of the power grid and substations, providing numerous conveniences. To enrich the functions of power grid dispatching integrated management, for example, CN114707761M, "A Power Intelligent Dispatch Management System," discloses "a power intelligent dispatch management system, including: a main control terminal for issuing power dispatch control commands and issuing location tags to connect power dispatch equipment; and a model prediction module for predicting the control commands of the power dispatch equipment and connecting or disconnecting power." The system comprises: a network; a data acquisition module for collecting data from the power dispatching equipment within its safe positioning range; an information interaction module for receiving execution instructions from the data acquisition module and allowing modification of operation parameter values; an intelligent dispatch center for providing feedback on power dispatching status within the system and communicating with the warehouse management information system network; and a channel switching module for providing feedback on intelligent dispatch center operation instructions and transmitting them to the main control terminal for real-time tracking and management via a converter. Implementing this invention allows for timely and effective information transmission when the dispatch center needs to dispatch power to a certain area in an emergency, improving dispatching efficiency. However, this invention lacks monitoring of the operating environment of the power grid dispatching agency. When the dispatching agency faces safety hazards due to environmental issues, it cannot provide timely warnings, potentially causing unnecessary losses and resulting in poor performance. Summary of the Invention

[0003] To address the aforementioned technical problems, this invention provides an artificial intelligence-based integrated power grid dispatching management system. The integrated power grid dispatching management system includes a data acquisition subsystem, a data processing subsystem, and a remote dispatching subsystem, wherein:

[0004] The data acquisition subsystem is communicatively connected to the data processing subsystem and is used to acquire power data from the front end of the power grid and transmit it to the remote data processing subsystem. The data acquisition subsystem is located at the power grid equipment within the jurisdiction of the power grid dispatching agency and includes a voltage acquisition module, a current acquisition module, a load detection module, and an infrared temperature measurement module.

[0005] The data processing subsystem is communicatively connected to the remote dispatching subsystem and is used to perform data analysis on the acquired power grid front-end data, obtain analysis results, and transmit them to the remote dispatching subsystem.

[0006] The remote dispatch subsystem includes an intelligent dispatch module, a state estimation module, an intelligent security analysis module, an intelligent power quality coordination module, a dispatch visualization module, and a load forecasting module. The intelligent dispatch module is used to perform intelligent dispatching of the power grid based on the analysis results. The state estimation module is used to obtain the state information of the power grid after power dispatching and transmit the state information to the intelligent security analysis module to determine whether there are any safety hazards in the power grid. The intelligent power quality coordination module is used to transmit data to upstream or downstream power plants. The dispatch visualization module is used to visualize and demonstrate power dispatching information. The load forecasting module is used to obtain load reports after power dispatching of the power grid.

[0007] Preferably, the power data at the front end of the power grid includes transformer voltage, transformer load current, transformer active power, and transformer oil temperature.

[0008] Preferably, the data processing subsystem includes a control module and a data analysis module. The control module is used to aggregate the power grid front-end power data transmitted by the data acquisition subsystem, and transmit the aggregated power grid front-end power data and data analysis instructions to the data analysis module. The data analysis module is used to perform data analysis on the acquired power grid front-end power data to obtain analysis results. The data analysis specifically includes:

[0009] Acquire historical power data from the front end of the power grid, and preset the standard load F2, standard transformer oil temperature, and the proportional relationship between oil temperature and load based on the historical power data from the front end of the power grid.

[0010] The real-time load F1 is calculated based on the aggregated power grid front-end data;

[0011] If F1 ≤ F2 * 0.85, then the intelligent scheduling operation will not be performed;

[0012] If F2*0.85<F1≤F2*0.95, the real-time transformer oil temperature in the aggregated power grid front-end data is compared with the standard transformer oil temperature. If the real-time transformer oil temperature is less than or equal to the standard transformer oil temperature, the maximum load F3 is obtained based on the difference between the real-time and standard transformer oil temperatures and the ratio between oil temperature and load. If F3≥F2*1.1, the intelligent dispatch operation is not executed. If F3<F2*1.1, the intelligent dispatch operation is executed.

[0013] If F1 > F2 * 0.95, then execute the intelligent scheduling operation.

[0014] Preferably, intelligent dispatching of the power grid based on the analysis results specifically involves increasing the power generation of substations.

[0015] Preferably, the power grid dispatching and management system further includes a safety decision-making subsystem, which includes a safety data acquisition module, a safety data analysis module, and a decision-making module. The safety data acquisition module is used to collect environmental data information within the jurisdiction of the power grid dispatching agency in real time and transmit it to the safety data analysis module. The safety data analysis module analyzes the safety hazards existing in the current environment through the environmental data information to obtain analysis results. The decision-making module makes corresponding decisions based on the analysis results.

[0016] Preferably, the safety data acquisition module is used to collect environmental data information in real time within the jurisdiction of the power grid dispatching agency, specifically as follows:

[0017] The safety data acquisition module includes an image acquisition device, a temperature and humidity sensor, a smoke sensor, and a water immersion sensor. The environmental data information includes real-time image data between power grid lines, temperature and humidity data of substations, smoke content data of substations, and water immersion level data of substations.

[0018] Preferably, the safety data analysis module obtains analysis results by analyzing environmental data information to identify existing safety hazards in the current environment, specifically as follows:

[0019] Feature extraction is performed on real-time image data, and the safety of the line and the surrounding area is obtained through feature analysis;

[0020] Set temperature and humidity thresholds, smoke thresholds, and water immersion thresholds. Compare the real-time collected temperature and humidity data, smoke content data, and water immersion degree data with the set corresponding thresholds to obtain temperature and humidity comparison results, smoke comparison results, and water immersion comparison results.

[0021] Preferably, the decision-making module makes corresponding decisions based on the analysis results as follows:

[0022] Based on the safety conditions of the line and the surrounding area, notify maintenance personnel to go to the fault site for repairs;

[0023] Based on the temperature and humidity comparison results, the heat dissipation and dehumidification devices installed inside the substation are controlled to regulate temperature and humidity.

[0024] Based on the smoke comparison results and water immersion comparison results, the substation staff were notified to go to the site to check for any water or fire safety hazards.

[0025] Preferably, the data processing subsystem further includes a data storage module, the input end of which is electrically connected to the output end of the control module, for storing the aggregated power grid front-end power data. When the memory of the data storage module is less than a preset memory threshold, the control module issues a deletion command to the data storage module to delete the earliest stored data until the memory is greater than or equal to the preset memory threshold.

[0026] Preferably, the power grid dispatching and management system further includes a paper archiving module, the input end of which is electrically connected to the output end of the data analysis module, for printing analysis results for staff to view and save.

[0027] Compared with the prior art, the beneficial effects of the present invention are:

[0028] This invention provides an artificial intelligence-based integrated power grid dispatching management system. Based on the cooperation of a data acquisition subsystem, a data processing subsystem, and a remote dispatching subsystem, it achieves remote intelligent power dispatching by acquiring and analyzing power data from the front end of the power grid. This enhances the control of technical personnel over the entire power grid system and simplifies equipment operation and maintenance procedures. By setting up a safety decision-making subsystem, it monitors the status of the area under the jurisdiction of the power grid dispatching agency in real time, preventing unnecessary economic losses caused by potential safety hazards within the area. Furthermore, maintenance personnel do not need to constantly visit remote sites to check equipment status, effectively mitigating safety risks for maintenance personnel. Attached Figure Description

[0029] Figure 1 This is a schematic diagram of the system structure in an embodiment of the present invention. Detailed Implementation

[0030] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0031] This invention discloses an artificial intelligence-based integrated power grid dispatching management system, which includes a data acquisition subsystem, a data processing subsystem, and a remote dispatching subsystem.

[0032] M1, Data Acquisition Subsystem;

[0033] The data acquisition subsystem is communicatively connected to the data processing subsystem and is used to acquire power data from the front end of the power grid and transmit it to the remote data processing subsystem. The data acquisition subsystem is located at the power grid equipment within the jurisdiction of the power grid dispatching agency and includes a voltage acquisition module, a current acquisition module, a load detection module, and an infrared temperature measurement module.

[0034] Preferably, the power data at the front end of the power grid includes transformer voltage, transformer load current, transformer active power, and transformer oil temperature;

[0035] M2, Data Processing Subsystem;

[0036] The data processing subsystem is communicatively connected to the remote dispatching subsystem and is used to perform data analysis on the acquired power grid front-end data, obtain analysis results, and transmit them to the remote dispatching subsystem.

[0037] Preferably, the data processing subsystem includes a control module and a data analysis module. The control module is used to aggregate the power grid front-end power data transmitted by the data acquisition subsystem, and transmit the aggregated power grid front-end power data and data analysis instructions to the data analysis module. The data analysis module is used to perform data analysis on the acquired power grid front-end power data to obtain analysis results.

[0038] In this embodiment, the control module is specifically a programmable PLC, model NX7-28MDT. A programmable PLC is a digital computing electronic device specifically designed for industrial applications. It uses a programmable memory to store instructions for performing logical operations, sequential operations, timing, counting, and arithmetic operations, and can control various types of machinery or production processes through digital or analog inputs and outputs.

[0039] Preferably, the data analysis process is as follows:

[0040] Acquire historical power data from the front end of the power grid, and preset the standard load F2, standard transformer oil temperature, and the proportional relationship between oil temperature and load based on the historical power data from the front end of the power grid.

[0041] The real-time load F1 is calculated based on the aggregated power grid front-end data;

[0042] If F1 ≤ F2 * 0.85, then the intelligent scheduling operation will not be performed;

[0043] If F2*0.85<F1≤F2*0.95, compare the real-time transformer oil temperature in the aggregated power grid front-end data with the standard transformer oil temperature:

[0044] If the real-time transformer oil temperature is higher than the standard transformer oil temperature, stop data analysis and output an early warning signal.

[0045] If the real-time transformer oil temperature is less than or equal to the standard transformer oil temperature, the maximum load F3 is obtained based on the difference between the real-time transformer oil temperature and the standard transformer oil temperature and the ratio between oil temperature and load; if F3 ≥ F2 * 1.1, the intelligent scheduling operation is not executed; if F3 < F2 * 1.1, the intelligent scheduling operation is executed.

[0046] If F1 > F2 * 0.95, then execute the intelligent scheduling operation;

[0047] Preferably, the data processing subsystem further includes an early warning module, the input end of which is electrically connected to the output end of the data analysis module, for acquiring early warning signals and issuing warnings;

[0048] Preferably, the data processing subsystem further includes a data storage module, the input end of which is electrically connected to the output end of the control module, for storing the aggregated power grid front-end power data. When the memory of the data storage module is less than a preset memory threshold, the control module issues a deletion command to the data storage module to delete the earliest stored data until the memory is greater than or equal to the preset memory threshold.

[0049] M3, Remote Dispatch Subsystem;

[0050] The remote dispatch subsystem includes an intelligent dispatch module, a state estimation module, an intelligent security analysis module, an intelligent power quality coordination module, a dispatch visualization module, and a load forecasting module. The intelligent dispatch module is used to intelligently dispatch the power grid based on analysis results; preferably, intelligent dispatching based on analysis results specifically involves increasing the power generation of substations. The state estimation module is used to obtain the state information of the power grid after power dispatching and transmit this state information to the intelligent security analysis module to determine whether there are any security risks in the power grid. The intelligent power quality coordination module is used to transmit data to upstream or downstream power stations. The dispatch visualization module is used to visualize and demonstrate power dispatching information. The load forecasting module is used to obtain load reports after power dispatching.

[0051] M4, Security Decision Subsystem;

[0052] Preferably, the power grid dispatching and management system further includes a safety decision-making subsystem, which includes a safety data acquisition module, a safety data analysis module, and a decision-making module. The safety data acquisition module is used to collect environmental data information in real time within the jurisdiction of the power grid dispatching agency and transmit it to the safety data analysis module. The safety data analysis module analyzes the safety hazards existing in the current environment through the environmental data information to obtain analysis results. The decision-making module makes corresponding decisions based on the analysis results.

[0053] Preferably, the safety data acquisition module is used to collect environmental data information in real time within the jurisdiction of the power grid dispatching agency, specifically as follows:

[0054] The safety data acquisition module includes an image acquisition device, a temperature and humidity sensor, a smoke sensor, and a water immersion sensor. The environmental data information includes real-time image data between power grid lines, temperature and humidity data of substations, smoke content data of substations, and water immersion level data of substations.

[0055] In this embodiment, the image acquisition device is a surveillance camera, and the temperature and humidity sensor is model TH-902. Temperature and humidity sensors often use integrated temperature and humidity probes as temperature measuring elements to acquire temperature and humidity signals. After processing by circuits such as voltage regulation filtering, operational amplification, nonlinear correction, V / I conversion, constant current and reverse protection, the signals are converted into current or voltage signals that are linearly related to temperature and humidity and output.

[0056] The smoke sensor model is MQ-2. It can detect smoke generated during a fire, is easy to install, and can perform fire safety monitoring of the environment.

[0057] Preferably, the safety data analysis module obtains analysis results by analyzing environmental data information to identify existing safety hazards in the current environment, specifically as follows:

[0058] Feature extraction is performed on real-time image data, and the safety of the line and the surrounding area is obtained through feature analysis;

[0059] Set temperature and humidity thresholds, smoke thresholds, and water immersion thresholds. Compare the real-time collected temperature and humidity data, smoke content data, and water immersion degree data with the set corresponding thresholds to obtain temperature and humidity comparison results, smoke comparison results, and water immersion comparison results.

[0060] Preferably, the decision-making module makes corresponding decisions based on the analysis results as follows:

[0061] Based on the safety conditions of the line and the surrounding area, notify maintenance personnel to go to the fault site for repairs;

[0062] Based on the temperature and humidity comparison results, the heat dissipation and dehumidification devices installed inside the substation are controlled to regulate temperature and humidity.

[0063] Based on the smoke comparison results and water immersion comparison results, the substation staff were notified to go to the site to check for any water or fire safety hazards.

[0064] M5, Paper Archive Module

[0065] Preferably, the power grid dispatching and management system further includes a paper archiving module, the input end of which is electrically connected to the output end of the data analysis module, for printing analysis results for staff to view and save;

[0066] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," and "counterclockwise," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0067] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0068] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

[0069] 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 the specific implementations described. 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. An artificial intelligence-based power grid dispatching integrated management system, characterized in that, The power grid dispatch and management system includes a data acquisition subsystem, a data processing subsystem, a remote dispatch subsystem, and a security decision-making subsystem, wherein: The data acquisition subsystem is communicatively connected to the data processing subsystem and is used to acquire power data from the front end of the power grid and transmit it to the remote data processing subsystem. The data acquisition subsystem is located at the power grid equipment within the jurisdiction of the power grid dispatching agency and includes a voltage acquisition module, a current acquisition module, a load detection module, and an infrared temperature measurement module. The power data from the front end of the power grid includes transformer voltage, transformer load current, transformer active power, and transformer oil temperature. The data processing subsystem is communicatively connected to the remote dispatching subsystem and is used to perform data analysis on the acquired power grid front-end data to obtain analysis results and transmit them to the remote dispatching subsystem. The data processing subsystem includes a control module and a data analysis module. The control module is used to aggregate the power grid front-end data transmitted by the data acquisition subsystem and transmit the aggregated power grid front-end data and data analysis instructions to the data analysis module. The data analysis module is used to perform data analysis on the acquired power grid front-end data to obtain analysis results. The data analysis specifically includes: Acquire historical power data from the front end of the power grid, and preset the standard load F2, standard transformer oil temperature, and the proportional relationship between oil temperature and load based on the historical power data from the front end of the power grid. The real-time load F1 is calculated based on the aggregated power grid front-end data; If F1 ≤ F2 * 0.85, then the intelligent scheduling operation will not be performed; If F2*0.85<F1≤F2*0.95, the real-time transformer oil temperature in the aggregated power grid front-end data is compared with the standard transformer oil temperature. If the real-time transformer oil temperature is less than or equal to the standard transformer oil temperature, the maximum load F3 is obtained based on the difference between the real-time and standard transformer oil temperatures and the ratio between oil temperature and load. If F3≥F2*1.1, the intelligent dispatch operation is not executed. If F3<F2*1.1, the intelligent dispatch operation is executed. If F1 > F2 * 0.95, then execute the intelligent scheduling operation; The remote dispatch subsystem includes an intelligent dispatch module, a state estimation module, an intelligent security analysis module, an intelligent power quality coordination module, a dispatch visualization module, and a load forecasting module. The intelligent dispatch module performs intelligent dispatch of the power grid based on analysis results. The state estimation module obtains the power grid's state information after power dispatch and transmits this information to the intelligent security analysis module to determine if there are any security risks in the power grid. The intelligent power quality coordination module transmits data to upstream or downstream power plants. The dispatch visualization module provides a visual demonstration of power dispatch information. The load forecasting module obtains load reports after power dispatch. The safety decision-making subsystem includes a safety data acquisition module, a safety data analysis module, and a decision-making module. The safety data acquisition module is used to collect environmental data information in real time within the jurisdiction of the power grid dispatching agency and transmit it to the safety data analysis module. The safety data analysis module analyzes the safety hazards existing in the current environment through the environmental data information to obtain analysis results. The decision-making module makes corresponding decisions based on the analysis results.

2. The power grid dispatching integrated management system based on artificial intelligence according to claim 1, characterized in that, Based on the analysis results, intelligent dispatching of the power grid specifically involves increasing the power generation of substations. 3.The power grid dispatching integrated management system based on artificial intelligence according to claim 2, characterized in that, The safety data acquisition module is used to collect environmental data information in the area under the jurisdiction of the power grid dispatching agency in real time, specifically: The safety data acquisition module includes an image acquisition device, a temperature and humidity sensor, a smoke sensor, and a water immersion sensor. The environmental data information includes real-time image data between power grid lines, temperature and humidity data of substations, smoke content data of substations, and water immersion level data of substations.

4. The power grid dispatching integrated management system based on artificial intelligence according to claim 3, characterized in that, The security data analysis module obtains analysis results by analyzing environmental data information to identify potential security risks in the current environment. Specifically, the analysis results are as follows: Feature extraction is performed on real-time image data, and the safety of the line and the surrounding area is obtained through feature analysis; Set temperature and humidity thresholds, smoke thresholds, and water immersion thresholds. Compare the real-time collected temperature and humidity data, smoke content data, and water immersion degree data with the set corresponding thresholds to obtain temperature and humidity comparison results, smoke comparison results, and water immersion comparison results.

5. The power grid dispatching integrated management system based on artificial intelligence according to claim 4, characterized in that, The decision-making module makes corresponding decisions based on the analysis results, specifically as follows: Based on the safety conditions of the line and the surrounding area, notify maintenance personnel to go to the fault site for repairs; Based on the temperature and humidity comparison results, the heat dissipation and dehumidification devices installed inside the substation are controlled to regulate temperature and humidity. Based on the smoke comparison results and water immersion comparison results, the substation staff were notified to go to the site to check for any water or fire safety hazards.

6. The integrated power grid dispatching and management system based on artificial intelligence according to claim 1, characterized in that, The data processing subsystem also includes a data storage module. The input end of the data storage module is electrically connected to the output end of the control module and is used to store the aggregated power grid front-end power data. When the memory of the data storage module is less than a preset memory threshold, the control module issues a deletion command to the data storage module to delete the earliest stored data until the memory is greater than or equal to the preset memory threshold. 7.The power grid dispatching integrated management system based on artificial intelligence according to claim 1, characterized in that, The power grid dispatch and management system also includes a paper archiving module. The input end of the paper archiving module is electrically connected to the output end of the data analysis module, and is used to print the analysis results for staff to view and save.

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