Power grid power supply data abnormity monitoring system and monitoring method thereof

Abstract

The invention relates to the technical field of power systems, and discloses a power grid power supply data abnormity monitoring system and a monitoring method thereof, and the system comprises a data collection module, a data analysis module, an abnormity detection module, an abnormity processing module, and a data recording and feedback module. Compared with the prior art, the method has the advantages that the system can find abnormal data in time, and risks of power grid dispatching decision errors and equipment damage caused by data abnormity are reduced; power grid faults can be prevented, and the stability and reliability of a power grid are enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems, and in particular to a power grid power supply data anomaly monitoring system and a monitoring method thereof. Background Art

[0002] The power system is a complex network that integrates power generation, transmission, distribution and consumption. Its core purpose is to convert natural energy (such as fossil fuels, nuclear energy, hydropower, wind energy, solar energy, etc.) into electrical energy through a series of equipment and technical means, such as generators, transformers, transmission lines, switchgear and protection devices, and safely, efficiently and reliably transmit it to various user ends to meet the demand for electricity in social production, life and economic development. With the in-depth advancement of smart grid construction, the accuracy and real-time nature of power data are crucial to the safe and stable operation of the power grid. However, due to various factors such as equipment failure and communication interruption, there may be anomalies in power data, which may lead to problems such as grid dispatch decision errors and equipment damage; and the stability and reliability of the power grid are low. Summary of the invention

[0003] The purpose of the present invention is to solve the shortcomings of the prior art and propose a power grid power supply data abnormality monitoring system, the system comprising:

[0004] (1) Data acquisition module, used to collect power grid power supply data in real time, including voltage, current, and power factor, and ensure the real-time and accuracy of data acquisition;

[0005] (2) Data analysis module, which receives data from the data acquisition module, processes and analyzes the data, and extracts key features for subsequent anomaly detection;

[0006] (3) an anomaly detection module, which performs anomaly detection on the data processed by the data analysis module based on a preset anomaly detection algorithm. The anomaly detection algorithm includes but is not limited to threshold comparison and trend analysis to determine whether the data exceeds a normal range or has an abnormal trend;

[0007] (4) an abnormality handling module, which, when the abnormality detection module detects an abnormality, takes corresponding handling measures according to the type and degree of the abnormality, including but not limited to issuing an alarm signal and automatically cutting off the power supply, so as to ensure the stable operation of the power system;

[0008] (5) Data recording and feedback module: This module records relevant information of abnormal events, such as abnormality type, occurrence time, and handling measures, and feeds back abnormal events to staff for subsequent analysis and processing.

[0009] As a further description of the above technical solution:

[0010] The anomaly detection algorithms used by the anomaly detection module include but are not limited to the following types:

[0011] (1) Based on the threshold comparison algorithm, by setting the thresholds of parameters such as voltage and current, it is determined whether the data exceeds the normal range;

[0012] (2) Based on the trend analysis algorithm, by analyzing historical data, the changing trend of future data is predicted and whether there is an abnormal trend.

[0013] As a further description of the above technical solution:

[0014] (1) Data collection step: The data collection module collects power grid power supply data in real time to ensure the real-time and accuracy of the data;

[0015] (2) Data processing step: Use the data analysis module to process and analyze the collected data and extract key features for subsequent anomaly detection;

[0016] (3) Anomaly detection step: Based on the preset anomaly detection algorithm, the processed data is subjected to anomaly detection to determine whether the data exceeds the normal range or has an abnormal trend;

[0017] (4) Exception handling step: When an exception is detected, the exception handling module takes appropriate measures according to the type and severity of the exception to ensure the stable operation of the power system;

[0018] (5) Data recording and feedback step: Record relevant information of abnormal events and feedback the abnormal events to staff for subsequent analysis and processing.

[0019] As a further description of the above technical solution:

[0020] The power grid data collected in the data collection step includes but is not limited to the following parameters:

[0021] (1) Voltage parameters, such as three-phase voltage, line voltage, and phase voltage;

[0022] (2) Current parameters, such as three-phase current and phase current;

[0023] (3) Power factor parameters, such as power factor and reactive power.

[0024] The present invention has the following beneficial effects:

[0025] 1. In the present invention, through real-time monitoring of power grid power supply data, the system can promptly detect abnormal data and reduce the risk of power grid dispatching decision errors and equipment damage caused by data anomalies.

[0026] 2. In the present invention, timely discovery and processing of abnormal data in the power grid helps prevent the occurrence of power grid failures and enhance the stability and reliability of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 The present invention provides a block diagram of a system for monitoring abnormal power supply data in a power grid. DETAILED DESCRIPTION

[0028] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0029] Reference Figure 1 , an embodiment of the present invention provides: a power grid power supply data abnormality monitoring system, the system comprising:

[0030] (1) Data acquisition module, used to collect power grid power supply data in real time, including voltage, current, and power factor, and ensure the real-time and accuracy of data acquisition;

[0031] (2) Data analysis module, which receives data from the data acquisition module, processes and analyzes the data, and extracts key features for subsequent anomaly detection;

[0032] (3) an anomaly detection module, which performs anomaly detection on the data processed by the data analysis module based on a preset anomaly detection algorithm. The anomaly detection algorithm includes but is not limited to threshold comparison and trend analysis to determine whether the data exceeds a normal range or has an abnormal trend;

[0033] (4) an abnormality handling module, which, when the abnormality detection module detects an abnormality, takes corresponding handling measures according to the type and degree of the abnormality, including but not limited to issuing an alarm signal and automatically cutting off the power supply, so as to ensure the stable operation of the power system;

[0034] (5) Data recording and feedback module, which records relevant information of abnormal events, such as abnormality type, occurrence time, and treatment measures, and feeds back abnormal events to staff for subsequent analysis and processing;

[0035] The anomaly detection algorithms used by the anomaly detection module include but are not limited to the following types:

[0036] (1) Based on the threshold comparison algorithm, by setting the thresholds of parameters such as voltage and current, it is determined whether the data exceeds the normal range;

[0037] (2) Based on the trend analysis algorithm, by analyzing historical data, the changing trend of future data is predicted and whether there is an abnormal trend.

[0038] A method for monitoring abnormal power supply data of a power grid, comprising the following steps:

[0039] (1) Data collection step: The data collection module collects power grid power supply data in real time to ensure the real-time and accuracy of the data;

[0040] (2) Data processing step: Use the data analysis module to process and analyze the collected data and extract key features for subsequent anomaly detection;

[0041] (3) Anomaly detection step: Based on the preset anomaly detection algorithm, the processed data is subjected to anomaly detection to determine whether the data exceeds the normal range or has an abnormal trend;

[0042] (4) Exception handling step: When an exception is detected, the exception handling module takes appropriate measures according to the type and severity of the exception to ensure the stable operation of the power system;

[0043] (5) Data recording and feedback step: record relevant information of abnormal events and feedback the abnormal events to the staff for subsequent analysis and processing;

[0044] The power grid data collected in the data collection step includes but is not limited to the following parameters:

[0045] (1) Voltage parameters, such as three-phase voltage, line voltage, and phase voltage;

[0046] (2) Current parameters, such as three-phase current and phase current;

[0047] (3) Power factor parameters, such as power factor and reactive power.

[0048] Working principle: By collecting power supply data in the power grid in real time and using advanced data transmission technology to transmit the data to the processing center; in the processing center, the system first pre-processes the data to improve the analysis quality, and then uses preset thresholds or machine learning algorithms to detect abnormal data; once an abnormality is found, the system will immediately trigger the alarm mechanism and notify the operation and maintenance personnel in a variety of ways; it can realize real-time monitoring and accurate analysis of power supply data of the power grid, thereby ensuring the safe and stable operation of the power grid and providing strong support for the sustainable development of the power industry.

[0049] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A power grid power supply data abnormality monitoring system, characterized in that: The system comprises: (1) Data acquisition module, used to collect power grid power supply data in real time, including voltage, current, and power factor, and ensure the real-time and accuracy of data acquisition; (2) Data analysis module, which receives data from the data acquisition module, processes and analyzes the data, and extracts key features for subsequent anomaly detection; (3) an anomaly detection module, which performs anomaly detection on the data processed by the data analysis module based on a preset anomaly detection algorithm. The anomaly detection algorithm includes but is not limited to threshold comparison and trend analysis to determine whether the data exceeds a normal range or has an abnormal trend; (4) an abnormality handling module, which, when the abnormality detection module detects an abnormality, takes corresponding handling measures according to the type and degree of the abnormality, including but not limited to issuing an alarm signal and automatically cutting off the power supply, so as to ensure the stable operation of the power system; (5) Data recording and feedback module: This module records relevant information of abnormal events, such as abnormality type, occurrence time, and handling measures, and feeds back abnormal events to staff for subsequent analysis and processing.

2. A power grid power supply data abnormality monitoring system according to claim 1, wherein: The anomaly detection algorithms used by the anomaly detection module include but are not limited to the following types: (1) Based on the threshold comparison algorithm, by setting the thresholds of parameters such as voltage and current, it is determined whether the data exceeds the normal range; (2) Based on the trend analysis algorithm, by analyzing historical data, the changing trend of future data is predicted and whether there is an abnormal trend.

3. A method for monitoring abnormal power supply data of a power grid, characterized in that: The following steps are involved: (1) Data collection step: The data collection module collects power supply data in real time to ensure the real-time and accuracy of the data; (2) Data processing step: Use the data analysis module to process and analyze the collected data and extract key features for subsequent anomaly detection; (3) Anomaly detection step: Based on the preset anomaly detection algorithm, the processed data is subjected to anomaly detection to determine whether the data exceeds the normal range or has an abnormal trend; (4) Exception handling step: When an exception is detected, the exception handling module takes appropriate measures according to the type and severity of the exception to ensure the stable operation of the power system; (5) Data recording and feedback step: Record relevant information of abnormal events and feedback the abnormal events to staff for subsequent analysis and processing.

4. A method for monitoring abnormal power supply data of a power grid according to claim 3, wherein: The power grid power supply data collected in the data collection step includes but is not limited to the following parameters: (1) Voltage parameters, such as three-phase voltage, line voltage, and phase voltage; (2) Current parameters, such as three-phase current and phase current; (3) Power factor parameters, such as power factor and reactive power.

Images