Data detection and analysis method and equipment based on power operation and medium

Abstract

The invention discloses a data detection and analysis method and equipment based on power operation and a medium, and relates to the technical field of data detection and analysis processing, and the method comprises the following steps: obtaining historical power operation data which comprises a weather influence coefficient, power generation equipment abnormal rate data and a power transmission line influence coefficient; constructing a power operation data anomaly detection objective function according to the power operation data to obtain a power operation data anomaly rate; comparing the obtained abnormal rate of the power operation data with a preset standard threshold value to obtain a data accuracy signal; and performing accuracy grading processing on the low-accuracy data signal to obtain a data exception grade.

Description

Technical Field

[0001] The present invention relates to the technical field of data detection and analysis, and more specifically, to a data detection and analysis method, device and medium based on power operation. Background Art

[0002] ‌Power operation mainly involves the process of power production, transmission, distribution and sales, ensuring the stable, safe and efficient operation of the power system. Power operation plays a vital role in modern society, not only providing impetus for economic development, but also playing an important role in energy transformation and sustainable development. In the face of future challenges, power operation is developing in the direction of intelligence and renewable energy integration. The power operation system is mainly composed of two categories: power generation equipment and power supply equipment.

[0003] Power generation equipment includes power plant boilers, steam turbines, gas turbines, water turbines, generators, etc. These devices are mainly responsible for the generation of electrical energy. Power supply equipment mainly includes transmission lines of various voltage levels, transformers, contactors, etc. These devices are responsible for transmitting electrical energy from power plants to users. However, since current technology fails to correctly identify and process outliers in data, it will lead to deviations in analysis results.

[0004] In view of the above problems, the present invention proposes a solution. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, the embodiments of the present invention provide a data detection and analysis method, device and medium based on power operation, which solve the problem of high inaccuracy of analysis results of data detection by processing power operation data.

[0006] To achieve the above object, the present invention provides the following technical solutions: A data detection and analysis method, device and medium based on power operation, characterized in that it includes the following steps: obtaining historical power operation data, the power operation data including weather influence coefficient, power generation equipment abnormality rate data, and transmission line influence coefficient; constructing a power operation data anomaly detection objective function according to the power operation data to obtain the power operation data anomaly rate; comparing the obtained power operation data anomaly rate with a preset standard threshold to obtain a data accuracy signal; performing accuracy grading processing on low-accuracy data signals to obtain a data anomaly level.

[0007] In a preferred embodiment, the weather impact coefficient is obtained by the following method: record the current air temperature and dew point temperature, and calculate the maximum amount of water vapor that the air can hold at the current temperature and the saturated water vapor pressure at the current dew point temperature, indicating the actual amount of water vapor in the air; calculate the relative humidity data of the detection point based on the obtained data; install a precipitation sensor at the monitoring location to collect the precipitation at the detection point in real time; and calculate the weather impact coefficient based on the obtained weather impact parameters.

[0008] In a preferred embodiment, the method for acquiring the abnormal rate data of the power generation equipment is as follows: acquiring the temperature, pressure, vibration parameters of the power generation facility and the numerical range of the temperature, pressure, and vibration parameters during normal operation; directly measuring the power generation through an electric energy metering device; calculating the power generation efficiency of the power generation set by measuring fuel consumption and power generation according to the type and scale of the power generation facility; recording the number of data on the temperature, pressure, vibration parameters and power generation of the power generation facility that are not within the numerical range during normal operation, and calculating the abnormal occurrence rate of the power generation equipment; calculating the abnormal rate data of the power generation equipment based on the obtained power generation efficiency of the power generation set and the abnormal occurrence rate of the power generation equipment.

[0009] In a preferred embodiment, the method for obtaining the transmission line influence coefficient is as follows: deploying current sensors, voltage sensors and power sensors on the transmission system equipment, and the sensors regularly collect the current size of each node cable equipment and the node voltage on the cable equipment; calculating the circuit power consumption and power efficiency based on the acquired current, voltage and power data; recording the resistance and reactance of the transmission line, and calculating the impedance of the transmission line.

[0010] In a preferred embodiment, a device using the data detection and analysis method based on power operation as described in any one of claims 1 to 7 is characterized in that it includes: a data collection module: used to obtain power operation data including weather influence coefficient, power generation equipment abnormality rate data, and transmission line influence coefficient; a data processing module: used to construct a power operation data anomaly detection objective function based on the power operation data obtained by the data collection module, and obtain the power operation data anomaly rate in the data processing module; a comprehensive analysis module: used to compare the calculated power operation data anomaly rate with a pre-set standard threshold, and analyze the comparison results of the mean value and standard deviation with the preset standard threshold.

[0011] In a preferred embodiment, an electronic device is characterized in that the electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute a data detection and analysis method based on power operation as described in any one of claims 1 to 7.

[0012] In a preferred embodiment, a computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, the method for data detection and analysis based on power operation as described in any one of claims 1 to 7 is implemented.

[0013] The technical effects and advantages of the data detection and analysis method, device and medium based on power operation of the present invention are as follows: 1. The present invention obtains the accuracy of the detected data through a data detection and analysis method based on power operation.

[0014] 2. The present invention obtains the data anomaly level of the detected abnormal data through a data detection and analysis method based on power operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A schematic diagram of a flow chart of a data detection and analysis method based on power operation of the present invention; Figure 2 This is a functional module diagram of a data detection and analysis device based on power operation of the present invention; Figure 3 A schematic diagram of the structure of an electronic device for implementing the data detection and analysis method based on power operation according to the present invention.

[0016] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0017] 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.

[0018] Embodiment 1, Figure 1 A flow chart of a data detection and analysis method based on power operation of the present invention is given. In this embodiment, the data detection and analysis method based on power operation includes: Acquire historical power operation data, wherein the power operation data includes weather influence coefficient, power generation equipment abnormality rate data, and transmission line influence coefficient; According to the power operation data, an anomaly detection objective function of the power operation data is constructed to obtain the anomaly rate of the power operation data; Compare the obtained abnormal rate of power operation data with a preset standard threshold to obtain a data accuracy signal; The low-accuracy data signal is subjected to accuracy grading processing to obtain the data anomaly level.

[0019] The power operation data includes weather impact coefficient, power generation equipment abnormality rate data, and transmission line impact coefficient, specifically including: The weather influence coefficient includes temperature data, humidity data and wind speed of the detection point; The power generation equipment abnormality rate data includes the real-time operating status, power generation, and power generation efficiency of the power generation facilities; The transmission line influence coefficient includes the current, voltage, power and transmission loss of each node in the transmission system.

[0020] The importance of obtaining weather impact coefficients includes the following points: Wind and solar power generation forecast: Weather factors such as temperature, humidity and wind speed are crucial for forecasting wind and solar power generation. Wind speed directly affects the power generation of wind turbines, while sunlight intensity directly affects the power generation efficiency of photovoltaic panels. By obtaining accurate weather factors, it can help power companies and operators optimize energy production plans, reasonably arrange power generation resources, and improve power generation efficiency. Grid load forecasting and management: Weather factors such as temperature and humidity have a significant impact on grid load. For example, in hot weather, the use of air conditioners increases, which increases the load on the grid. By monitoring and analyzing the weather impact coefficient, load changes in the next few days can be predicted, helping power companies adjust power generation plans and rationally allocate power resources to ensure the stability and reliability of power supply; Disaster warning and emergency response: Weather impact factors are also crucial for disaster warning and emergency response. For example, strong storms, thunderstorms, and extreme weather conditions may cause problems such as power line damage, equipment failure, or power outages. Timely acquisition and analysis of weather impact factors can help power companies make corresponding emergency plans, reduce losses and impacts caused by disasters, and restore power supply as soon as possible; Environmental impact assessment: Weather factors such as temperature, humidity and wind speed are also used to assess the impact of electricity production on the environment. For example, high temperature and humidity conditions may lead to higher operating efficiency of air conditioning equipment, thereby increasing electricity consumption and environmental load. Understanding these data can help formulate environmental protection policies and measures, promote the development of clean energy and sustainable electricity production.

[0021] The method for obtaining the weather influence coefficient is as follows: Obtain weather influencing parameters of the detection point, wherein the weather influencing parameters include daily temperature difference value data, relative humidity data, and wind speed; Record the current air temperature and dew point temperature, and calculate the maximum amount of water vapor that the air can hold at the current temperature and the saturated water vapor pressure at the current dew point temperature, indicating the actual amount of water vapor in the air; Calculate the relative humidity data of the detection point based on the acquired data; Install precipitation sensors at monitoring locations to collect precipitation at the detection points in real time; The weather impact coefficient is calculated based on the obtained weather impact parameters.

[0022] The calculation formula of the relative humidity is as follows:

[0023] Where: s is the relative humidity data of the detection point, Td is the saturated water vapor pressure at the dew point temperature, and T is the saturated water vapor pressure at the current temperature.

[0024] The calculation formula of the weather influence coefficient is as follows:

[0025] Where: TQ is the weather influence coefficient, t is the daily temperature difference value data of the detection point, s is the relative humidity data of the detection point, f is the wind speed of the detection point, and d is the precipitation of the detection point.

[0026] It should be noted that the weight coefficient reflects the actual impact of various weather factors on the accuracy, and the impact of weather factors on detection accuracy is usually negative. When the weather impact coefficient is negative, it means that under these weather conditions, the detection accuracy is greatly affected.

[0027] The importance of obtaining abnormal rate data of power generation equipment includes the following points: Real-time operation status monitoring: Real-time monitoring of the operation status of power generation facilities is the key to ensuring the continuity and stability of power production. By obtaining real-time operation data of power generation facilities, problems such as equipment failure, component damage or abnormal operation can be discovered in a timely manner, so that timely repair and maintenance measures can be taken to avoid increased downtime and improve the reliability and durability of equipment; Power generation and efficiency optimization: The power generation and power generation efficiency in the power generation equipment abnormality rate data directly affect the cost and benefits of power production. Understanding the real-time power generation of each generator set can help power companies adjust power generation strategies and plans, arrange resources reasonably to meet power demand, and maximize power generation efficiency. Optimizing power generation efficiency can also help reduce the production cost per unit of electricity and improve the competitiveness of power companies. Load dispatch and grid balance: Data on abnormal rates of power generation equipment is crucial to load dispatch and balance of the power grid. By understanding the power generation capacity and availability of different power generation facilities in real time, flexible adjustments can be made according to changes in power demand. This helps avoid overload or underload conditions of the power grid, maintains the stability and reliability of the power grid, and ensures the continuity of power supply. Market operation and energy supply strategy: The abnormal rate data of power generation equipment has an important impact on the operation of the power market and the energy supply strategy. Understanding the power generation capacity and cost structure of each power generation facility can help power companies formulate reasonable market transaction strategies, optimize the power supply chain, and improve market competitiveness and economic benefits. The method for obtaining the abnormal rate data of the power generation equipment is as follows: Install temperature sensors, pressure sensors, and vibration sensors at generators, bearings, and transformers to obtain the temperature, pressure, and vibration parameters of the power generation facilities and the numerical ranges of the temperature, pressure, and vibration parameters during normal operation; Directly measure power generation through energy metering devices; Calculate the power generation efficiency of the generating unit by measuring fuel consumption and power generation, depending on the type and size of the generating facility; Record the number of data on temperature, pressure, vibration parameters and power generation of power generation facilities that are not within the normal operating range, and calculate the abnormality rate of power generation equipment; The power generation equipment abnormality rate data is calculated based on the obtained power generation efficiency of the power generation set and the abnormality occurrence rate of the power generation equipment.

[0028] The calculation formula of the abnormal occurrence rate of the power generation equipment is as follows:

[0029] Where: Y is the abnormality rate of the power generation equipment, p is the number of abnormalities, and m is the total number of data obtained.

[0030] It should be noted that the abnormality rate refers to the number of abnormal faults of power generation equipment within a certain period of time. The higher the abnormality rate, the lower the reliability of the equipment, and the greater the impact on the detection accuracy. The lower the abnormality rate, the higher the reliability of the equipment, and the smaller the impact on the detection accuracy.

[0031] The power generation efficiency calculation formula of the generator set is as follows:

[0032] The calculation formula of the abnormal rate data of the power generation equipment is as follows:

[0033] Where: P j is the power generation of the jth power generation facility, FD is the abnormal rate data of the power generation equipment, is the power generation efficiency of the generator set.

[0034] The importance of obtaining the transmission line influence coefficient includes the following points: Network stability and operational safety: The current, voltage and other data of each node in the power transmission system are crucial to ensure the stable operation of the power grid. The current and voltage data can help operators monitor the power grid load and power transmission conditions in real time, and promptly detect potential problems in the power grid, such as overload, short circuit or voltage fluctuation, so as to take measures to prevent accidents and ensure the safety and stability of the power system; Load management and optimization: Current and power data are key information for grid load management and optimization. Understanding the real-time load conditions and current power distribution of each node can help operators reasonably dispatch power resources, avoid grid congestion and overload, and optimize grid operation efficiency and energy utilization; Energy efficiency and loss monitoring: Transmission loss refers to the energy loss caused by resistance and other factors during the transmission process. Monitoring and analyzing transmission loss data can help power companies evaluate transmission efficiency, identify potential factors that lead to energy loss, and take measures to reduce losses, thereby improving energy efficiency and reducing economic costs; Compliance and regulatory requirements: The collection and analysis of transmission line impact coefficients is also an important part of the regulatory and compliance requirements of the power industry. Regulators usually require operators to record and report grid operation data to ensure that they meet safety, environmental protection and efficiency standards to protect public interests and user rights.

[0035] The method for obtaining the transmission line influence coefficient is as follows: Current sensors, voltage sensors and power sensors are deployed on the power transmission system equipment. The sensors regularly collect the current size of each node cable equipment and the node voltage on the cable equipment; Calculate circuit power consumption and power efficiency based on acquired current, voltage and power data; Record the resistance and reactance of the transmission line and calculate the impedance of the transmission line.

[0036] The calculation formula of the transmission line influence coefficient is as follows:

[0037] Where: SD is the transmission line influence coefficient, is the output power of the transmission system, is the input power of the transmission system, I k is the current sensitivity coefficient of the kth node in the transmission system, is the impedance of the transmission line.

[0038] The power system is usually composed of power stations, transmission networks, and distribution networks. Each node can be an important part of the power system, such as power stations, substations, transformers, and users.

[0039] Transmission loss is the energy loss caused by resistance during the transmission and distribution of electricity. The transmission loss mainly includes conductor resistance loss and transformer iron loss. The calculation of transmission loss needs to consider factors such as current, voltage, line length, and conductor material.

[0040] It should be noted that the transmission network includes substations and transmission lines, and the distribution network includes transformers, distribution lines and users.

[0041] The transmission loss is calculated as follows:

[0042] Where: P loss is the transmission loss, I is the current transmitted through the transmission line, and R is the resistance of the transmission line.

[0043] The calculation formula of the power efficiency is as follows:

[0044] Where: is the power efficiency of the transmission system, is the output power of the transmission system, is the input power of the system.

[0045] The calculation formula of the power operation data anomaly detection objective function is as follows:

[0046] Where: D is the objective function of power operation data anomaly detection, is the power efficiency of the transmission system, P loss is the transmission loss, TQ is the weather influence coefficient, SD is the transmission line influence coefficient, and FD is the abnormal rate data of power generation equipment.

[0047] It should be noted that if the value of the power operation data anomaly rate obtained by the power operation data anomaly detection objective function is a low value close to 0, it means that there are few anomalies in the data being tested. If the value of the power operation data anomaly rate is a medium value, it means that there are some anomalies in the data being tested and further analysis is needed. If the value of the power operation data anomaly rate is a high value, it means that there are obvious anomalies in the data being tested and the cause of the anomaly needs to be found immediately.

[0048] The obtained abnormal rate of power operation data is compared and analyzed with the preset standard threshold, and the results of the comparison and analysis are as follows: If the abnormal rate of power operation data is less than the preset standard threshold, a high-accuracy data signal is generated, and no early warning is issued for the high-accuracy data signal; If the abnormal rate of power operation data is greater than or equal to the preset standard threshold, a low-accuracy data signal is generated and an early warning prompt is issued for the low-accuracy data signal.

[0049] The accuracy grading process is performed on the low-accuracy data signal to obtain the data abnormality level. The accuracy grading process is performed as follows: The abnormal rate of the power operation data that is a low-accuracy data signal as a result of the comparison analysis is put into the abnormal data set; Calculating the result of the comparison analysis in the abnormal data set as the average value of the abnormal rate of the power operation data of the low-accuracy data signal and the standard deviation of the abnormal rate of the power operation data and a preset standard threshold value; The obtained average value and standard deviation are compared with the preset standard threshold values ​​respectively, and the abnormal level of the abnormal rate data of the power operation data in the abnormal data set is obtained according to the comparison result.

[0050] The abnormal data set is represented as follows:

[0051] Where: is an abnormal data set that stores the abnormal rate of power operation data with low-accuracy data signals; n is a positive integer, indicating the total number of data in the abnormal data set, d i is the abnormal rate data of the i-th power operation data in the abnormal data set.

[0052] The result of the comparison analysis in the calculation abnormal data set is the average value of the abnormal rate of the power operation data of the low-accuracy data signal, and the calculation formula is as follows:

[0053] The obtained average value and standard deviation are compared with the preset standard thresholds respectively, and the abnormal level of the abnormal rate data of the power operation data in the abnormal data set is obtained according to the comparison results, including: When the average value is less than the preset standard threshold and the standard deviation is less than the preset standard threshold, a low abnormality level is generated; When the average value is greater than the preset standard threshold and the standard deviation is less than the preset standard threshold, a medium or low abnormal level is generated; When the average value is less than the preset standard threshold and the standard deviation is greater than the preset standard threshold, a medium or high abnormality level is generated; When the average value is greater than the preset standard threshold and the standard deviation is greater than the preset standard threshold, a high abnormality level is generated.

[0054] The abnormal rate of power operation data at a low abnormal level, the data tends to be low overall, and the fluctuation range of the data is small, and the abnormal level of the data is low; The abnormal rate of power operation data at the medium and low abnormal levels has a high average value, but the fluctuation range of the data is small and the abnormal level is also low. It can be considered that the data as a whole tends to be high but relatively stable. The abnormal rate of power operation data at medium and high abnormal levels, at which the average value of the data is low and the data fluctuation is large, indicating that there are some abnormal values ​​in the data or the distribution of the data set is uneven, and the abnormal level is relatively high; The abnormal rate of power operation data at a high abnormal level has a high average value and a large fluctuation range of the data, indicating that there are more fluctuations and possible abnormal values ​​in the data, and the abnormal level is high.

[0055] like Figure 2 The figure shows a functional module diagram of a device for processing personnel performance data. According to the functions to be implemented, the data detection and analysis device based on power operation may include a module xx. The module described in the present invention may also be referred to as a unit, which refers to a series of computer program segments that can be executed by a processor of a data detection and analysis device based on power operation and can complete fixed functions, which are stored in the memory of the device for processing personnel performance data.

[0056] In this embodiment, the functions of each module / unit are as follows: Data collection module: used to obtain power operation data including weather impact coefficient, power generation equipment abnormality rate data, and transmission line impact coefficient; Data processing module: used to construct an abnormality detection objective function of power operation data according to the power operation data obtained by the data collection module, and obtain the abnormality rate of power operation data in the data processing module; Comprehensive analysis module: used to compare the calculated abnormal rate of power operation data with the preset standard threshold, and analyze the comparison results of the average value and standard deviation with the preset standard threshold.

[0057] In detail, the modules described in the data detection and analysis device based on power operation described in the embodiment of the present invention adopt the same technical means as the data detection and analysis method based on power operation described in the accompanying drawings when used, and can produce the same technical effects, which will not be repeated here.

[0058] like Figure 3 The figure is a schematic diagram of the structure of an electronic device for implementing the data detection and analysis method based on power operation according to the present invention.

[0059] The electronic device may include a processor, a memory, a communication bus, and a communication interface, and may also include a computer program stored in the memory and executable on the processor, such as a data detection and analysis model generation program based on power operation.

[0060] Among them, the processor is the control core (Control Unit) of the electronic device, which uses various interfaces and lines to connect the various components of the entire electronic device, and executes various functions of the electronic device and processes data by running or executing programs or modules stored in the memory and calling data stored in the memory.

[0061] The memory includes at least one type of readable storage medium, and in some embodiments, the memory may be an internal storage unit of the electronic device, such as a mobile hard disk of the electronic device. The memory may be used to store not only application software installed in the electronic device but also various data.

[0062] The communication bus is configured to realize connection and communication between the memory and at least one processor.

[0063] The communication interface is used for communication between the above electronic device and other devices, including a network interface and a user interface.

[0064] The figure only shows an electronic device with components. Those skilled in the art will understand that the structure shown in the figure does not constitute a limitation on the electronic device, and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0065] It should be understood that the embodiment is for illustration only and the scope of the patent application is not limited to this structure.

[0066] The data detection and analysis model generation program based on power operation stored in the memory of the electronic device is a combination of multiple instructions. When running in the processor, the steps in the above-mentioned data detection and analysis method based on power operation can be implemented.

[0067] Specifically, the specific implementation system of the processor for the above instructions can refer to the description of the relevant steps in the corresponding embodiment of the accompanying drawings, which will not be repeated here.

[0068] The present invention also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor of an electronic device, it can implement the steps in the above-mentioned data detection and analysis method based on power operation.

[0069] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0070] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product.

[0071] Those of ordinary skill in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0072] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0073] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0074] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. 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 data detection and analysis method based on power operation, characterized in that: The steps include: Acquire historical power operation data, wherein the power operation data includes weather influence coefficient, power generation equipment abnormality rate data, and transmission line influence coefficient; According to the power operation data, an anomaly detection objective function of the power operation data is constructed to obtain the anomaly rate of the power operation data; Compare the obtained abnormal rate of power operation data with a preset standard threshold to obtain a data accuracy signal; The low-accuracy data signal is subjected to accuracy grading processing to obtain the data anomaly level.

2. The data detection and analysis method based on power operation according to claim 1 is characterized in that: The weather influence coefficient is obtained as follows: Record the current air temperature and dew point temperature, and calculate the maximum amount of water vapor that the air can hold at the current temperature and the saturated water vapor pressure at the current dew point temperature, indicating the actual amount of water vapor in the air; Calculate the relative humidity data of the detection point based on the acquired data; Install precipitation sensors at monitoring locations to collect precipitation at the detection points in real time; The weather impact coefficient is calculated based on the obtained weather impact parameters.

3. The data detection and analysis method based on power operation according to claim 2 is characterized in that: The method for obtaining the abnormal rate data of the power generation equipment is as follows: Obtain the temperature, pressure, vibration parameters of power generation facilities and the numerical ranges of temperature, pressure, and vibration parameters during normal operation; Directly measure power generation through energy metering devices; Calculate the power generation efficiency of the generating unit by measuring fuel consumption and power generation, depending on the type and size of the generating facility; Record the number of data on temperature, pressure, vibration parameters and power generation of power generation facilities that are not within the normal operating range, and calculate the abnormality rate of power generation equipment; The power generation equipment abnormality rate data is calculated based on the obtained power generation efficiency of the power generation set and the abnormality occurrence rate of the power generation equipment.

4. The data detection and analysis method based on power operation according to claim 3 is characterized in that: The method for obtaining the transmission line influence coefficient is as follows: Current sensors, voltage sensors and power sensors are deployed on the power transmission system equipment. The sensors regularly collect the current size of each node cable equipment and the node voltage on the cable equipment; Calculate circuit power consumption and power efficiency based on acquired current, voltage and power data; Record the resistance and reactance of the transmission line and calculate the impedance of the transmission line.

5. The data detection and analysis method based on power operation according to claim 4 is characterized in that: The calculation formula of the power operation data anomaly detection objective function is as follows: Where: D is the objective function of power operation data anomaly detection, is the power efficiency of the transmission system, P loss is the transmission loss, TQ is the weather influence coefficient, SD is the transmission line influence coefficient, and FD is the abnormal rate data of power generation equipment.

6. The data detection and analysis method based on power operation according to claim 5 is characterized in that: The calculation formula of the weather influence coefficient is as follows: Where: TQ is the weather influence coefficient, t is the daily temperature difference value data of the detection point, s is the relative humidity data of the detection point, f is the wind speed of the detection point, and d is the precipitation of the detection point.

7. The data detection and analysis method based on power operation according to claim 6 is characterized in that: The calculation formula of the transmission line influence coefficient is as follows: Where: SD is the transmission line influence coefficient, is the output power of the transmission system, is the input power of the transmission system, I k is the current sensitivity coefficient of the kth node in the transmission system, is the impedance of the transmission line.

8. A device using the data detection and analysis method based on power operation according to any one of claims 1 to 7, characterized in that: include: Data collection module: used to obtain power operation data including weather impact coefficient, power generation equipment abnormality rate data, and transmission line impact coefficient; Data processing module: used to construct an abnormality detection objective function of power operation data according to the power operation data obtained by the data collection module, and obtain the abnormality rate of power operation data in the data processing module; Comprehensive analysis module: used to compare the calculated abnormal rate of power operation data with the preset standard threshold, and analyze the comparison results of the average value and standard deviation with the preset standard threshold.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute a data detection and analysis method based on power operation as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, it implements a data detection and analysis method based on power operation as described in any one of claims 1 to 7.

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