Power grid data acquisition method and system based on data identification

Abstract

The invention discloses a power grid data acquisition method and system based on data identification, and belongs to the field of power supply or power distribution circuit systems.The power grid data acquisition method comprises the steps that an operation abnormity evaluation model is constructed, acquired operation data of power generation equipment in an operation period is imported into the operation abnormity evaluation model for operation abnormity evaluation, and a power generation proportion evaluation model is constructed; and importing the obtained power generation load data and power generation quality data in the operation cycle into a power generation proportion evaluation model for power generation proportion evaluation, and importing the obtained operation abnormity evaluation result and power generation proportion evaluation result into a next operation cycle load division strategy for load division of the next operation cycle. The power generation equipment outputs the load according to the load division of the next operation cycle, load distribution comprehensive analysis is carried out based on the power generation evaluation data and the operation abnormity evaluation data of the power generation equipment, the load distribution output distribution efficiency is improved, and the load distribution output safety is improved.

Description

Technical Field

[0001] The present invention belongs to the field of power supply or power distribution circuit systems, and more specifically, relates to a power grid data acquisition method and system based on data identification. Background Art

[0002] Grid data collection based on data recognition refers to the use of modern information technology and automation equipment to monitor and analyze the operation status of the power grid in real time to ensure the safe, efficient and reliable operation of the power system. This data collection method usually includes the following key components: sensors and monitoring equipment; communication network; data processing and analysis platform; monitoring center; early warning and emergency response system; predictive maintenance; automated control and repair and user service and support. With the popularization of smart meters, a good foundation for realizing digital information collection has been provided. The prior art cannot conduct a comprehensive analysis of load distribution based on the power generation evaluation data and operation abnormality evaluation data of the power generation equipment when collecting power grid data, which reduces the efficiency of load distribution output distribution and easily causes equipment damage. The above problems exist in the prior art (for example, in the invention patents with authorization publication numbers CN112787402B and CN111384778B); In order to solve these problems, the present application designs a power grid data collection method and system based on data identification. Summary of the invention

[0003] In view of the deficiencies in the prior art, the present invention proposes a power grid data collection method and system based on data identification. The present invention obtains the operating data of power generation equipment in the power grid operation cycle, the power generation load data and the power generation quality data in the operation cycle, constructs an operation abnormality assessment model, imports the obtained operating data of the power generation equipment in the operation cycle into the operation abnormality assessment model to perform operation abnormality assessment, constructs a power generation proportion assessment model, imports the obtained power generation load data and power generation quality data in the operation cycle into the power generation proportion assessment model to perform power generation proportion assessment, imports the obtained operation abnormality assessment results and the power generation proportion assessment results into the load division strategy for the next operation cycle to perform load division for the next operation cycle, the power generation equipment outputs the load according to the load division of the next operation cycle, and performs a comprehensive load distribution analysis based on the power generation assessment data and the operation abnormality assessment data of the power generation equipment, thereby improving the load distribution output distribution efficiency and improving the safety of the load distribution output.

[0004] To achieve the above object, the present invention provides the following technical solution: a power grid data acquisition method based on data identification, which includes the following specific steps: Obtain the operating data of power generation equipment during the power grid operation cycle, the power generation load data and power generation quality data during the operation cycle; Constructing an operation abnormality assessment model, and importing the acquired operation data of the power generation equipment in the operation cycle into the operation abnormality assessment model to conduct operation abnormality assessment; Construct a power generation ratio assessment model, and import the power generation load data and power generation quality data obtained during the operation cycle into the power generation ratio assessment model to conduct power generation ratio assessment; The obtained operation abnormality assessment results and power generation ratio assessment results are introduced into the load division strategy for the next operation cycle to perform load division for the next operation cycle; The power generation equipment outputs the load according to the load division of the next operating cycle.

[0005] It should be specifically explained here that the acquisition of the operation data of the power generation equipment during the operation period of the power grid, the power generation load data and the power generation quality data during the operation period includes the following specific steps: S11, collecting the operating data of each power generation device during the power grid operation cycle through the power generation device data collection terminal, wherein the operating data of the power generation device includes temperature data, vibration amplitude, vibration frequency and oil pressure data of the power generation device, and storing the acquired operating data of each power generation device in a first storage component; S12. Collect the power generation load data and power generation quality data of each power generation equipment during the operation cycle of the power grid through the power generation data collection terminal, wherein the power generation load data is the power generation data during the operation cycle, and the power generation quality data is the average proportion of the power generation voltage to the rated power generation voltage, and store the acquired power generation load data and power generation quality data of each power generation equipment in the second storage component.

[0006] It should be specifically explained here that the construction of the operation abnormality assessment model and importing the acquired operation data of the power generation equipment in the operation cycle into the operation abnormality assessment model to perform the operation abnormality assessment includes the following specific contents: S21, obtaining the operation data of each power generation equipment at a set time interval from the beginning to the end of the operation cycle; S22, extracting the operation data of each power generation equipment at the start set time interval within the operation cycle and the operation data of each power generation equipment at the end set time interval within the operation cycle, and respectively substituting them into the time period equipment abnormality evaluation coefficient calculation formula to calculate the time period equipment abnormality evaluation coefficient of the start set time interval and the time period equipment abnormality evaluation coefficient of the end set time interval, wherein the time period equipment abnormality evaluation coefficient calculation formula is: , where st is the equipment abnormality assessment coefficient for the time period, m is the number of types of operating data of the power generation equipment, and S is the length of the set time period. is the proportion coefficient of the operating data of the j-th power generation equipment, is the specific value of the operating data of the j-th power generation equipment at time t, is the median value of the safe range of operating data of the j-th power generation equipment, is the maximum value of the safe range of the operating data of the j-th power generation equipment, is the minimum value of the safe range of the operating data of the jth power generation equipment, dt is the time integral, where, ; S23, obtaining the calculated equipment abnormality assessment coefficients for the time period of the starting set time interval and the equipment abnormality assessment coefficients for the time period of the ending set time interval, and substituting them into the equipment abnormality assessment coefficient change amount calculation formula for the operation cycle to calculate the equipment abnormality assessment coefficient change amount, wherein the equipment abnormality assessment coefficient change amount calculation formula for the operation cycle is: ,in, The change in the equipment abnormality assessment coefficient for the running cycle, Set the equipment abnormality assessment coefficient for the time interval at the end of the operating cycle. The equipment abnormality assessment coefficient for the time period of the time interval set at the start of the operation cycle; S24, substituting the operation data of each power generation equipment in all time periods of the operation cycle into the time period equipment abnormality evaluation coefficient calculation formula to calculate the time period equipment abnormality evaluation coefficient of the operation cycle ; S25. The calculated equipment abnormality assessment coefficient for the time period of the operating cycle is Substitute the change in the equipment abnormality assessment coefficient during the operation cycle into the calculation formula of the abnormal operation assessment value of the power generation equipment to calculate the abnormal operation assessment value of the power generation equipment, where the calculation formula of the abnormal operation assessment value of the i-th power generation equipment is: ,in, is the proportion of equipment abnormality assessment coefficient in the time period, is the equipment abnormality assessment coefficient of the time period of the operating cycle of the i-th power generation equipment, is the change in the equipment abnormality assessment coefficient during the operation cycle of the i-th power generation equipment; It should be specifically explained here that the construction of the power generation proportion evaluation model and the importation of the acquired power generation load data and power generation quality data within the operation cycle into the power generation proportion evaluation model for power generation proportion evaluation include the following specific steps: S31, obtaining power generation load data and power generation quality data of each power generation equipment in the last operation cycle; S32, importing the power generation load data and power generation quality data of each power generation equipment into the power generation proportion evaluation value formula to calculate the power generation proportion evaluation value, wherein the power generation proportion evaluation value calculation formula of the i-th power generation equipment is: ,in, is the power generation quality data of the i-th power generation equipment in the last operation cycle, is the power generation load data of the ith power generation equipment in the last operating cycle, and N is the number of power generation equipment in operation in the last operating cycle.

[0007] It should be specifically explained here that the step of importing the obtained operation abnormality assessment result and power generation proportion assessment result into the load division strategy for the next operation cycle to perform load division for the next operation cycle includes the following specific steps: Obtain the calculated operation abnormality assessment value and power generation proportion assessment value of each power generation equipment, import the calculated operation abnormality assessment value and power generation proportion assessment value of each power generation equipment into the load partition value calculation formula of the next operation cycle to calculate the load partition value of each power generation equipment in the next operation cycle, wherein the load partition value calculation formula of the i-th power generation equipment in the next operation cycle is: , where Q is the total load required to be output in the next operating cycle, is the rated load of the i-th generating equipment.

[0008] It should be specifically explained here that the specific steps for the power generation equipment to output the load according to the load division of the next operation cycle are as follows: Obtain the calculated load division value of each power generation equipment in the next operating cycle, compare the obtained load division value of each power generation equipment in the next operating cycle with the rated power generation load of the corresponding power generation equipment, if there is a power generation equipment whose load division value is greater than the rated power generation load of the corresponding power generation equipment, then set the actual load of the corresponding power generation equipment to the rated power generation load of the corresponding power generation equipment, and after removing the corresponding power generation equipment, the remaining power generation load is again introduced into the load division value calculation formula of the next operating cycle to calculate the load division value of each power generation equipment in the next operating cycle; This setting prevents the load division value from being greater than the rated power generation load of the corresponding power generation equipment, which may cause damage to the power generation equipment; The power grid data acquisition system based on data identification is implemented based on the above-mentioned power grid data acquisition method based on data identification, and specifically includes: A data acquisition module is used to obtain the operating data of power generation equipment during the power grid operation cycle, the power generation load data within the operation cycle, and the power generation quality data; An operation abnormality assessment model building module is used to build an operation abnormality assessment model, and import the operation data of the power generation equipment in the acquired operation cycle into the operation abnormality assessment model to perform operation abnormality assessment; A power generation proportion assessment model construction module is used to construct a power generation proportion assessment model, and import the power generation load data and power generation quality data acquired during the operation cycle into the power generation proportion assessment model to perform power generation proportion assessment; A load division module is used to import the obtained operation abnormality assessment results and power generation proportion assessment results into the load division strategy for the next operation cycle to perform load division for the next operation cycle; Load output module, used for power generation equipment to output load according to the load division of the next operation cycle; The control module is used to control the operation of the data acquisition module, the operation abnormality assessment model construction module, the power generation proportion assessment model construction module, the load division module and the load output module.

[0009] An electronic device comprises: a processor and a memory, wherein the memory stores a computer program that can be called by the processor; The processor executes the above-mentioned power grid data collection method based on data identification by calling the computer program stored in the memory.

[0010] A computer-readable storage medium stores instructions, which, when executed on a computer, enable the computer to execute the above-mentioned power grid data collection method based on data identification.

[0011] Compared with the prior art, the present invention has the following beneficial effects: The present invention obtains the operation data of power generation equipment in the operation cycle of the power grid, the power generation load data and the power generation quality data in the operation cycle, constructs an operation abnormality assessment model, imports the operation data of the power generation equipment in the operation cycle obtained into the operation abnormality assessment model to perform operation abnormality assessment, constructs a power generation proportion assessment model, imports the power generation load data and the power generation quality data in the operation cycle obtained into the power generation proportion assessment model to perform power generation proportion assessment, imports the obtained operation abnormality assessment result and the power generation proportion assessment result into the load division strategy of the next operation cycle to perform load division of the next operation cycle, the power generation equipment outputs the load according to the load division of the next operation cycle, and performs a comprehensive load distribution analysis based on the power generation assessment data and the operation abnormality assessment data of the power generation equipment, thereby improving the load distribution output distribution efficiency and improving the safety of the load distribution output. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0013] Figure 1 It is a schematic diagram of the overall process of the power grid data collection method based on data identification of the present invention; Figure 2 It is a schematic flow chart of the steps of constructing an abnormal operation assessment model in the power grid data collection method based on data identification of the present invention; Figure 3It is a schematic diagram of the overall framework of the power grid data acquisition system based on data identification of the present invention. DETAILED DESCRIPTION

[0014] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0015] In the following description, many specific details are set forth to facilitate a full understanding of the present application, but the present application may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present application. Therefore, the present application is not limited to the specific embodiments disclosed below.

[0016] Example 1

[0017] When conducting a comprehensive load distribution analysis on the power generation assessment data and operation abnormality assessment data of power generation equipment, it is very important to ensure load balance and output distribution efficiency. If the load distribution is unbalanced or the output efficiency does not meet the standard, the following problems may occur: Equipment overload: If some power generation equipment is assigned too large a load, it may cause the equipment to operate at overload, increasing the risk of equipment loss and failure; Poor operating performance: Unreasonable load distribution and low output efficiency will affect the overall operating performance of power generation equipment, and affect power generation efficiency and stability.

[0018] Equipment damage and increased repair costs: Long-term load imbalance or low output efficiency will increase equipment loss and failure rate, increase maintenance costs and downtime; In this context, load balancing analysis and output distribution efficiency analysis are crucial to reducing equipment damage and improving operating efficiency. Reasonable load distribution and high output efficiency can effectively reduce the operating load of equipment, reduce the risk of equipment damage, extend the service life of equipment, and ensure the reliability and safety of equipment. See also Figure 1-Figure 2 , an embodiment provided by the present invention: the technical problem solved by this embodiment is: the prior art cannot perform comprehensive analysis of load distribution based on power generation assessment data and operation abnormality assessment data of power generation equipment, which reduces the efficiency of load distribution output distribution and easily causes equipment damage; The power grid data collection method based on data identification includes the following specific steps: Obtain the operating data of power generation equipment during the power grid operation cycle, the power generation load data and power generation quality data during the operation cycle; Constructing an operation abnormality assessment model, and importing the acquired operation data of the power generation equipment in the operation cycle into the operation abnormality assessment model to conduct operation abnormality assessment; Construct a power generation ratio assessment model, and import the power generation load data and power generation quality data obtained during the operation cycle into the power generation ratio assessment model to conduct power generation ratio assessment; The obtained operation abnormality assessment results and power generation ratio assessment results are introduced into the load division strategy for the next operation cycle to perform load division for the next operation cycle; The power generation equipment outputs the load according to the load division of the next operation cycle; In this embodiment, it should be specifically explained that obtaining the operation data of the power generation equipment during the operation period of the power grid, the power generation load data and the power generation quality data during the operation period includes the following specific steps: S11, collecting the operating data of each power generation device during the power grid operation cycle through the power generation device data collection terminal, wherein the operating data of the power generation device includes temperature data, vibration amplitude, vibration frequency and oil pressure data of the power generation device, and storing the acquired operating data of each power generation device in a first storage component; The operating data of power generation equipment covers various information and is used to monitor the performance, operating status and health of the equipment. The following are some common operating data of power generation equipment: 1. Electrical parameters: - Voltage: actual value and fluctuation of output voltage; - Current: actual value and change of output current; - Power: actual value and change of output power; - Frequency: actual value and stability of output frequency; 2. Temperature data: - Oil temperature: the temperature of the oil inside the generator; - Cooling water temperature: the temperature of the engine cooling system; - Power generation equipment casing temperature: the temperature of the equipment casing surface; 3. Pressure data: - Oil pressure: actual value of engine oil pressure; - Cooling water pressure: the pressure of the engine cooling system; 4. Fuel consumption data: - Fuel tank oil level: the actual value of the fuel tank oil level; - Fuel consumption rate: the fuel consumption rate of the engine; - Oil temperature: fuel temperature; 5. Vibration data: - Vibration amplitude: the degree of vibration of the generator or engine; - Vibration frequency: frequency of vibration; 6. Run time and load data: - Running time: the accumulated running time of the equipment; - Load rate: The load rate of the equipment, that is, the ratio of the actual output power to the rated power; By monitoring and recording these operating data, operation and maintenance personnel can monitor the operating status of the equipment in real time, find problems in time and perform repairs and maintenance to ensure efficient and stable operation of the equipment. Some advanced power generation equipment can also transmit these data to remote servers through remote monitoring systems, allowing operation and maintenance personnel to monitor the equipment status anytime and anywhere. S12, collecting power generation load data and power generation quality data of each power generation device during the operation cycle of the power grid through the power generation data collection terminal, wherein the power generation load data is the power generation data during the operation cycle, and the power generation quality data is the average proportion of the power generation voltage to the rated power generation voltage, and storing the acquired power generation load data and power generation quality data of each power generation device in the second storage component; In this embodiment, it should be specifically explained that constructing an operation abnormality assessment model and importing the acquired operation data of the power generation equipment in the operation cycle into the operation abnormality assessment model to perform operation abnormality assessment includes the following specific contents: S21, obtaining the operation data of each power generation equipment at a set time interval from the beginning to the end of the operation cycle; S22, extracting the operation data of each power generation equipment at the start set time interval within the operation cycle and the operation data of each power generation equipment at the end set time interval within the operation cycle, and respectively substituting them into the time period equipment abnormality evaluation coefficient calculation formula to calculate the time period equipment abnormality evaluation coefficient of the start set time interval and the time period equipment abnormality evaluation coefficient of the end set time interval, wherein the time period equipment abnormality evaluation coefficient calculation formula is: , where st is the equipment abnormality assessment coefficient for the time period, m is the number of types of operating data of the power generation equipment, and S is the length of the set time period. is the proportion coefficient of the operating data of the j-th power generation equipment, is the specific value of the operating data of the j-th power generation equipment at time t, is the median value of the safe range of operating data of the j-th power generation equipment, is the maximum value of the safe range of the operating data of the j-th power generation equipment, is the minimum value of the safe range of the operating data of the jth power generation equipment, dt is the time integral, where, ; S23, obtaining the calculated equipment abnormality assessment coefficients for the time period of the starting set time interval and the equipment abnormality assessment coefficients for the time period of the ending set time interval, and substituting them into the equipment abnormality assessment coefficient change amount calculation formula for the operation cycle to calculate the equipment abnormality assessment coefficient change amount, wherein the equipment abnormality assessment coefficient change amount calculation formula for the operation cycle is: ,in, The change in the equipment abnormality assessment coefficient for the running cycle, Set the equipment abnormality assessment coefficient for the time interval at the end of the operating cycle. The equipment abnormality assessment coefficient for the time period of the time interval set at the start of the operation cycle; S24, substituting the operation data of each power generation equipment in all time periods of the operation cycle into the time period equipment abnormality evaluation coefficient calculation formula to calculate the time period equipment abnormality evaluation coefficient of the operation cycle ; S25. The calculated equipment abnormality assessment coefficient for the time period of the operating cycle is Substitute the change in the equipment abnormality assessment coefficient during the operation cycle into the calculation formula of the abnormal operation assessment value of the power generation equipment to calculate the abnormal operation assessment value of the power generation equipment, where the calculation formula of the abnormal operation assessment value of the i-th power generation equipment is: ,in, is the proportion of equipment abnormality assessment coefficient in the time period, is the equipment abnormality assessment coefficient of the time period of the operating cycle of the i-th power generation equipment, is the change in the equipment abnormality assessment coefficient during the operation cycle of the i-th power generation equipment; In this embodiment, it should be specifically explained that constructing a power generation proportion evaluation model and importing the power generation load data and power generation quality data acquired during the operation cycle into the power generation proportion evaluation model to perform power generation proportion evaluation includes the following specific steps: S31, obtaining power generation load data and power generation quality data of each power generation equipment in the last operation cycle; S32, importing the power generation load data and power generation quality data of each power generation equipment into the power generation proportion evaluation value formula to calculate the power generation proportion evaluation value, wherein the power generation proportion evaluation value calculation formula of the i-th power generation equipment is: ,in, is the power generation quality data of the i-th power generation equipment in the last operation cycle, is the power generation load data of the ith power generation equipment in the last operation cycle, and N is the number of power generation equipment in operation in the last operation cycle; In this embodiment, it should be specifically explained that the operation abnormality assessment result and the power generation proportion assessment result are introduced into the load division strategy of the next operation period to divide the load of the next operation period, which includes the following specific steps: Obtain the calculated operation abnormality assessment value and power generation proportion assessment value of each power generation equipment, import the calculated operation abnormality assessment value and power generation proportion assessment value of each power generation equipment into the load partition value calculation formula of the next operation cycle to calculate the load partition value of each power generation equipment in the next operation cycle, wherein the load partition value calculation formula of the i-th power generation equipment in the next operation cycle is: , where Q is the total load required to be output in the next operating cycle, is the rated load of the i-th generating equipment; In this embodiment, it should be specifically explained that the specific steps of the power generation equipment outputting the load according to the load division of the next operation cycle are as follows: Obtain the calculated load division value of each power generation equipment in the next operating cycle, compare the obtained load division value of each power generation equipment in the next operating cycle with the rated power generation load of the corresponding power generation equipment, if there is a power generation equipment whose load division value is greater than the rated power generation load of the corresponding power generation equipment, then set the actual load of the corresponding power generation equipment to the rated power generation load of the corresponding power generation equipment, and after removing the corresponding power generation equipment, the remaining power generation load is again introduced into the load division value calculation formula of the next operating cycle to calculate the load division value of each power generation equipment in the next operating cycle; This setting prevents the load division value from being greater than the rated power generation load of the corresponding power generation equipment, which may cause damage to the power generation equipment; What needs to be specifically explained in this embodiment is that the value-taking method of the proportion coefficient of the operating data of the j-th power generation equipment and the proportion of the equipment abnormality assessment coefficient in the time period is as follows: obtain at least five thousand sets of operating data of the power generation equipment, the power generation load data and the power generation quality data in the operating cycle, extract and judge the fault condition after the equipment runs under load in the next cycle, substitute the operating data of the power generation equipment in the historical operation process, the power generation load data and the power generation quality data in the operating cycle into the load division value calculation formula of the next operating cycle to calculate the load division value of the next operating cycle, import the calculated load division value and fault judgment result of the next operating cycle into the fitting software, and output the value of the proportion coefficient of the operating data of the j-th power generation equipment and the proportion of the equipment abnormality assessment coefficient in the time period; It should be noted here that the advantages of this embodiment over the prior art are: obtaining the operating data of the power generation equipment in the power grid operating cycle, the power generation load data and the power generation quality data within the operating cycle, building an operation abnormality assessment model, importing the obtained operating data of the power generation equipment in the operating cycle into the operation abnormality assessment model to perform an operation abnormality assessment, building a power generation proportion assessment model, importing the obtained power generation load data and power generation quality data within the operating cycle into the power generation proportion assessment model to perform power generation proportion assessment, importing the obtained operation abnormality assessment results and the power generation proportion assessment results into the load division strategy for the next operating cycle to perform load division for the next operating cycle, the power generation equipment outputs the load according to the load division of the next operating cycle, and performing a comprehensive load distribution analysis based on the power generation assessment data and the operation abnormality assessment data of the power generation equipment, thereby improving the load distribution output distribution efficiency and the safety of the load distribution output.

[0019] Example 2

[0020] like Figure 3 As shown, the power grid data acquisition system based on data identification is implemented based on the above-mentioned power grid data acquisition method based on data identification, which specifically includes: a data acquisition module, which is used to obtain the operation data of the power generation equipment in the power grid operation cycle, the power generation load data and the power generation quality data within the operation cycle; An operation abnormality assessment model building module is used to build an operation abnormality assessment model, and import the operation data of the power generation equipment in the acquired operation cycle into the operation abnormality assessment model to perform operation abnormality assessment; A power generation proportion assessment model construction module is used to construct a power generation proportion assessment model, and import the power generation load data and power generation quality data acquired during the operation cycle into the power generation proportion assessment model to perform power generation proportion assessment; A load division module is used to import the obtained operation abnormality assessment results and power generation proportion assessment results into the load division strategy for the next operation cycle to perform load division for the next operation cycle; Load output module, used for power generation equipment to output load according to the load division of the next operation cycle; The control module is used to control the operation of the data acquisition module, the operation abnormality assessment model construction module, the power generation proportion assessment model construction module, the load division module and the load output module.

[0021] Example 3

[0022] This embodiment provides an electronic device, including: a processor and a memory, wherein the memory stores a computer program that can be called by the processor; The processor executes the above-mentioned power grid data collection method based on data identification by calling the computer program stored in the memory.

[0023] The electronic device may have relatively large differences due to different configurations or performances, and may include one or more processors (Central Processing Units, CPU) and one or more memories, wherein the memory stores at least one computer program, which is loaded and executed by the processor to implement the power grid data collection method based on data identification provided by the above method embodiment.

[0024] Example 4

[0025] This embodiment provides a computer-readable storage medium having a rewritable computer program stored thereon; When the computer program runs on a computer device, the computer device is enabled to execute the above-mentioned power grid data collection method based on data identification.

[0026] For example, the computer readable storage medium can be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, etc.

Claims

1. A power grid data collection method based on data identification, characterized in that: It includes the following specific steps: Obtain the operating data of power generation equipment during the power grid operation cycle, the power generation load data and power generation quality data during the operation cycle; Constructing an operation abnormality assessment model, and importing the acquired operation data of the power generation equipment in the operation cycle into the operation abnormality assessment model to conduct operation abnormality assessment; Construct a power generation ratio assessment model, and import the power generation load data and power generation quality data obtained during the operation cycle into the power generation ratio assessment model to conduct power generation ratio assessment; The obtained operation abnormality assessment results and power generation ratio assessment results are introduced into the load division strategy for the next operation cycle to perform load division for the next operation cycle; The power generation equipment outputs the load according to the load division of the next operating cycle.

2. The power grid data collection method based on data identification according to claim 1, characterized in that: The acquisition of the operation data of the power generation equipment during the operation period of the power grid, the power generation load data and the power generation quality data during the operation period comprises the following specific steps: S11, collecting the operating data of each power generation device during the power grid operation cycle through the power generation device data collection terminal, wherein the operating data of the power generation device includes temperature data, vibration amplitude, vibration frequency and oil pressure data of the power generation device, and storing the acquired operating data of each power generation device in a first storage component; S12. Collect the power generation load data and power generation quality data of each power generation equipment during the operation cycle of the power grid through the power generation data collection terminal, wherein the power generation load data is the power generation data during the operation cycle, and the power generation quality data is the average proportion of the power generation voltage to the rated power generation voltage, and store the acquired power generation load data and power generation quality data of each power generation equipment in the second storage component.

3. The power grid data collection method based on data identification according to claim 2, characterized in that: The construction of the operation abnormality assessment model and importing the acquired operation data of the power generation equipment in the operation cycle into the operation abnormality assessment model for operation abnormality assessment include the following specific contents: S21, obtaining the operation data of each power generation equipment at a set time interval from the beginning to the end of the operation cycle; S22, extracting the operation data of each power generation equipment at the start set time interval within the operation cycle and the operation data of each power generation equipment at the end set time interval within the operation cycle, and respectively substituting them into the time period equipment abnormality evaluation coefficient calculation formula to calculate the time period equipment abnormality evaluation coefficient of the start set time interval and the time period equipment abnormality evaluation coefficient of the end set time interval, wherein the time period equipment abnormality evaluation coefficient calculation formula is: , where st is the equipment abnormality assessment coefficient for the time period, m is the number of types of operating data of the power generation equipment, and S is the length of the set time period. is the proportion coefficient of the operating data of the j-th power generation equipment, is the specific value of the operating data of the j-th power generation equipment at time t, is the median value of the safe range of operating data of the j-th power generation equipment, is the maximum value of the safe range of the operating data of the j-th power generation equipment, is the minimum value of the safe range of the operating data of the jth power generation equipment, dt is the time integral, where, ; S23, obtaining the calculated equipment abnormality assessment coefficients for the time period of the starting set time interval and the equipment abnormality assessment coefficients for the time period of the ending set time interval, and substituting them into the equipment abnormality assessment coefficient change calculation formula for the operation cycle to calculate the equipment abnormality assessment coefficient change, wherein the equipment abnormality assessment coefficient change calculation formula for the operation cycle is: ,in, The change in the equipment abnormality assessment coefficient for the running cycle, Set the equipment abnormality assessment coefficient for the time interval at the end of the operating cycle. Set the time interval for the start of the operation cycle to evaluate the equipment abnormality.

4. The power grid data collection method based on data identification according to claim 3, characterized in that: The construction of the operation abnormality assessment model and importing the acquired operation data of the power generation equipment in the operation cycle into the operation abnormality assessment model for operation abnormality assessment also includes the following specific contents: S24, substituting the operation data of each power generation equipment in all time periods of the operation cycle into the time period equipment abnormality evaluation coefficient calculation formula to calculate the time period equipment abnormality evaluation coefficient of the operation cycle ; S25. The calculated equipment abnormality assessment coefficient for the time period of the operating cycle is Substitute the change in the equipment abnormality assessment coefficient during the operation cycle into the calculation formula of the abnormal operation assessment value of the power generation equipment to calculate the abnormal operation assessment value of the power generation equipment, where the calculation formula of the abnormal operation assessment value of the i-th power generation equipment is: ,in, is the proportion of equipment abnormality assessment coefficient in the time period, is the equipment abnormality assessment coefficient of the time period of the operating cycle of the i-th power generation equipment, is the change in the equipment abnormality assessment coefficient during the operation cycle of the i-th power generation equipment.

5. The power grid data collection method based on data identification according to claim 4, characterized in that: The construction of the power generation proportion assessment model, importing the acquired power generation load data and power generation quality data within the operation cycle into the power generation proportion assessment model to perform power generation proportion assessment includes the following specific steps: S31, obtaining power generation load data and power generation quality data of each power generation equipment in the last operation cycle; S32, importing the power generation load data and power generation quality data of each power generation equipment into the power generation proportion evaluation value formula to calculate the power generation proportion evaluation value, wherein the power generation proportion evaluation value calculation formula of the i-th power generation equipment is: ,in, is the power generation quality data of the i-th power generation equipment in the last operation cycle, is the power generation load data of the ith power generation equipment in the last operating cycle, and N is the number of power generation equipment in operation in the last operating cycle.

6. The power grid data collection method based on data identification according to claim 5, characterized in that: The step of importing the obtained operation abnormality assessment result and power generation proportion assessment result into the load division strategy for the next operation cycle to perform load division for the next operation cycle includes the following specific steps: Obtain the calculated operation abnormality assessment value and power generation proportion assessment value of each power generation equipment, import the calculated operation abnormality assessment value and power generation proportion assessment value of each power generation equipment into the load partition value calculation formula of the next operation cycle to calculate the load partition value of each power generation equipment in the next operation cycle, wherein the load partition value calculation formula of the i-th power generation equipment in the next operation cycle is: , where Q is the total load required to be output in the next operating cycle, is the rated load of the i-th generating equipment.

7. The power grid data collection method based on data identification according to claim 6, characterized in that: The specific steps of the power generation equipment outputting the load according to the load division of the next operation cycle are as follows: Obtain the calculated load division value of each power generation equipment in the next operating cycle, compare the obtained load division value of each power generation equipment in the next operating cycle with the rated power generation load of the corresponding power generation equipment, if there is a power generation equipment whose load division value is greater than the rated power generation load of the corresponding power generation equipment, then set the actual load of the corresponding power generation equipment to the rated power generation load of the corresponding power generation equipment, and after removing the corresponding power generation equipment, the remaining power generation load is again introduced into the load division value calculation formula of the next operating cycle to calculate the load division value of each power generation equipment in the next operating cycle.

8. A power grid data acquisition system based on data identification, which is implemented based on the power grid data acquisition method based on data identification according to any one of claims 1 to 7, characterized in that: Specifically include: A data acquisition module is used to obtain the operating data of power generation equipment during the power grid operation cycle, the power generation load data within the operation cycle, and the power generation quality data; An operation abnormality assessment model building module is used to build an operation abnormality assessment model, and import the operation data of the power generation equipment in the acquired operation cycle into the operation abnormality assessment model to perform operation abnormality assessment; A power generation proportion assessment model construction module is used to construct a power generation proportion assessment model, and import the power generation load data and power generation quality data acquired during the operation cycle into the power generation proportion assessment model to perform power generation proportion assessment; A load division module is used to import the obtained operation abnormality assessment results and power generation proportion assessment results into the load division strategy for the next operation cycle to perform load division for the next operation cycle; Load output module, used for power generation equipment to output load according to the load division of the next operation cycle; The control module is used to control the operation of the data acquisition module, the operation abnormality assessment model construction module, the power generation proportion assessment model construction module, the load division module and the load output module.

9. An electronic device, comprising: A processor and a memory, wherein the memory stores a computer program that can be called by the processor; It is characterized in that the processor executes the power grid data collection method based on data identification as described in any one of claims 1 to 7 by calling the computer program stored in the memory.

10. A computer-readable storage medium, characterized in that: Instructions are stored, and when the instructions are executed on a computer, the computer is caused to execute the power grid data collection method based on data identification as described in any one of claims 1 to 7.

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