Power generation equipment risk condition assessment method, device, equipment, medium and product

Abstract

The invention provides a power generation equipment risk condition assessment method and device, equipment, a medium and a product, and the method comprises the steps: obtaining the related data of a station, and the related data comprises the environment data of the station, the operation state data of each target equipment in the station, the communication data of each target equipment, and the output power of each target equipment; screening out abnormal data from the operation state data and the communication data, and analyzing the abnormal data to obtain a reliability index of each target device; determining the power utilization rate of each business stage according to the environmental data of the station, the output power of each power generation device and the output power of each energy transmission device; and performing interface display on the reliability index and the power utilization rate. According to the method, human errors caused by manual processing are effectively avoided, the accuracy of data analysis is ensured, and the data processing mode does not interfere with the efficient operation of the power generation equipment, so that the continuity and stability of energy production are ensured.

Description

Technical Field

[0001] The present application relates to the field of energy technology, and in particular to a method, device, equipment, medium and product for evaluating the risk status of power generation equipment. Background Art

[0002] With the advancement of energy technology and changes in market demand, emerging industries such as wind power and solar energy are experiencing a period of rapid development. These emerging industries not only promote the transformation of energy structure, but also bring a large amount of data information. In order to more effectively manage and maintain the increasingly large energy sites, the centralized control center management model came into being.

[0003] In the prior art, the centralized control center receives relevant data information from the power generation equipment in the station through the communication network, and then the operators of the centralized control center perform statistical analysis on the data information, and then the operators arrange fault maintenance work for the power generation equipment according to the analysis results.

[0004] However, the centralized control center relies on manual analysis and troubleshooting of relevant data information of power generation equipment in the station, which may lead to long processing time and introduce human errors, affecting the efficient operation of power generation equipment. Summary of the invention

[0005] The present application provides a method, device, equipment, medium and product for evaluating the risk status of power generation equipment to solve the problem in the prior art that the centralized control center relies on manual analysis and fault handling of relevant data information of power generation equipment in the station, resulting in long processing time and introduction of human errors, and also affecting the efficient operation of the power generation equipment.

[0006] In a first aspect, the present application provides a method for assessing the risk status of power generation equipment, which is applied to computer equipment, comprising:

[0007] Acquire relevant data of the site, the relevant data including: environmental data of the site, operating status data of each target device in the site, communication data of each target device and output power of each target device, each target device including at least one power generation device and at least one energy transmission device, and the environmental data is related to the type of each power generation device;

[0008] Filtering abnormal data from the operating status data and the communication data, and analyzing the abnormal data to obtain reliability indicators of each target device;

[0009] Determine the power utilization rate of each business stage according to the environmental data of the site, the output power of each power generation device, and the output power of each energy transmission device, wherein the business stage includes: an energy conversion stage and an energy transmission stage;

[0010] The reliability index and the power utilization rate are displayed on an interface.

[0011] In one possible design, the power utilization rate of each business stage is determined based on the environmental data of the site, the output power of each power generation equipment, and the output power of each energy transmission equipment, including: calculating the input power of each power generation equipment based on the environmental data; determining the power utilization rate in the energy conversion stage based on the input power of each power generation equipment and the output power of each power generation equipment; determining the power utilization rate in the energy transmission stage based on the output power of each power generation equipment and the output power of each energy transmission equipment.

[0012] In a possible design, abnormal data is screened out from the operating status data and the communication data, and the abnormal data is analyzed to obtain the reliability index of each target device, including: cleaning and formatting the operating status data and the communication data to obtain processed operating status data and processed communication data, the cleaning is used to delete invalid data, and the formatting is used to convert data into a unified format; if any processed operating status data is greater than or equal to an operating status data threshold, then any processed operating status data is determined to be abnormal data; if any processed communication data is greater than or equal to a communication data threshold, then any processed communication data is determined to be abnormal data; extracting characteristic values ​​of the abnormal data; inputting the characteristic values ​​into a corresponding safety prediction model to output the reliability index of the target device corresponding to the abnormal data.

[0013] In a possible design, the reliability index and the power utilization rate are displayed in an interface, including: determining the power loss rate of each energy transmission device according to the power utilization rate in the energy transmission stage, and determining the power loss of each energy transmission device per unit time according to the power loss rate; the reliability index of each target device in each site, the power utilization rate of each business stage and the power loss of each energy transmission device per unit time are statistically analyzed according to different dimensions to obtain the reliability index and the power utilization rate of different dimensions, and the different dimensions include: the target device, site, region and affiliated party; the reliability index, the power utilization rate and the power loss are displayed in the form of a list according to the different dimensions, and the dimensions of the reliability index with abnormalities are prompted.

[0014] In a possible design, the reliability index, the power utilization rate and the power loss are displayed in the form of a list according to the different dimensions, and after prompting the dimension where the reliability index is abnormal, it also includes: for any dimension, the curves of the reliability index, the power utilization rate and the power loss in any dimension changing with time are displayed separately.

[0015] In one possible design, the method also includes: performing statistical analysis on the environmental data of the station to obtain environmental resource indicators of the station, the environmental data including at least one of the following: real-time wind speed data and real-time light data, and the environmental resource indicators including at least one of the following: average wind speed, wind frequency graph, wind rose graph, average light intensity, total light intensity, peak sunshine duration, equivalent peak sunshine duration; arranging and displaying the environmental resource indicators in a preset order.

[0016] In a second aspect, the present application provides a device for assessing the risk status of power generation equipment, which is applied to computer equipment, including:

[0017] An acquisition module is used to acquire relevant data of a station, wherein the relevant data includes: environmental data of the station, operating status data of each target device in the station, communication data of each target device, and output power of each target device, wherein each target device includes at least one power generation device and at least one energy transmission device, and the environmental data is related to the type of each power generation device;

[0018] Analysis module: used for filtering abnormal data from the operation status data and the communication data, and analyzing the abnormal data to obtain the reliability index of each target device;

[0019] A determination module: used to determine the power utilization rate of each business stage according to the environmental data of the site, the output power of each power generation equipment, and the output power of each energy transmission equipment, wherein the business stage includes: an energy conversion stage and an energy transmission stage;

[0020] Display module: used to display the reliability index and the power utilization rate on an interface.

[0021] Wherein, the power utilization rate of each business stage is determined according to the environmental data of the site, the output power of each power generation equipment, and the output power of each energy transmission equipment, including: calculating the input power of each power generation equipment according to the environmental data; determining the power utilization rate in the energy conversion stage according to the input power of each power generation equipment and the output power of each power generation equipment; determining the power utilization rate in the energy transmission stage according to the output power of each power generation equipment and the output power of each energy transmission equipment.

[0022] Among them, abnormal data is screened out from the operating status data and the communication data, and the abnormal data is analyzed to obtain the reliability index of each target device, including: cleaning and formatting the operating status data and the communication data to obtain processed operating status data and processed communication data, the cleaning is used to delete invalid data, and the formatting is used to convert data into a unified format; if any processed operating status data is greater than or equal to an operating status data threshold, then any processed operating status data is determined to be abnormal data; if any processed communication data is greater than or equal to a communication data threshold, then any processed communication data is determined to be abnormal data; extracting characteristic values ​​of the abnormal data; inputting the characteristic values ​​into a corresponding safety prediction model to output the reliability index of the target device corresponding to the abnormal data.

[0023] Among them, the reliability index and the power utilization rate are displayed in an interface, including: determining the power loss rate of each energy transmission device according to the power utilization rate in the energy transmission stage, and determining the power loss of each energy transmission device per unit time according to the power loss rate; the reliability index of each target device in each station, the power utilization rate of each business stage and the power loss of each energy transmission device per unit time are statistically analyzed according to different dimensions to obtain the reliability index and the power utilization rate of different dimensions, and the different dimensions include: the target device, station, region and affiliated party; the reliability index, the power utilization rate and the power loss are displayed in the form of a list according to the different dimensions, and the dimensions of the reliability index with abnormalities are prompted.

[0024] Among them, the reliability index, the power utilization rate and the lost electricity are displayed in the form of a list according to the different dimensions, and after prompting the dimension where the reliability index is abnormal, it also includes: for any dimension, the curves of the reliability index, the power utilization rate and the lost electricity of any dimension changing with time are displayed respectively.

[0025] The method further includes: performing statistical analysis on the environmental data of the station to obtain environmental resource indicators of the station, the environmental data including at least one of the following: real-time wind speed data and real-time light data, and the environmental resource indicators including at least one of the following: average wind speed, wind frequency graph, wind rose graph, average light intensity, total light intensity, peak sunshine duration, equivalent peak sunshine duration; arranging and displaying the environmental resource indicators in a preset order.

[0026] In a third aspect, the present application provides a computer device, comprising: at least one processor and a memory;

[0027] The memory stores computer-executable instructions;

[0028] The at least one processor executes the computer-executable instructions stored in the memory, so that the at least one processor performs the method for assessing the risk status of the power generation equipment as described in the first aspect and various possible designs of the first aspect.

[0029] In a fourth aspect, the present application provides a computer storage medium storing computer execution instructions. When a processor executes the computer execution instructions, the method for evaluating the risk status of power generation equipment as described in the first aspect and various possible designs of the first aspect is implemented.

[0030] In a fifth aspect, the present application provides a computer program product, including a computer program. When the computer program is executed by a processor, it implements the method for evaluating the risk status of power generation equipment as described in the first aspect and various possible designs of the first aspect.

[0031] The method, device, equipment, medium and product for assessing the risk status of power generation equipment provided by this application first collect relevant data in the site, then use these data to identify abnormal conditions and analyze data to assess the reliability index of each target equipment; then combine environmental data and the output power of the equipment to calculate the power utilization rate in different business stages, such as the energy conversion stage and the energy transmission stage; finally, the reliability index and power utilization rate are displayed on the interface. It effectively avoids human errors caused by manual processing and ensures the accuracy of data analysis. In addition, this data processing method will not interfere with the efficient operation of power generation equipment, thereby ensuring the continuity and stability of energy production. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0033] Figure 1 A schematic diagram of an application scenario for assessing the risk status of power generation equipment provided by an embodiment of the present invention;

[0034] Figure 2 A schematic flow chart of a method for assessing the risk status of power generation equipment provided in one embodiment of the present application;

[0035] Figure 3An evaluation device for the risk status of power generation equipment provided in an embodiment of the present application;

[0036] Figure 4 A schematic diagram of the hardware structure of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are 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.

[0038] With the rapid development of energy technology and the growing global demand for clean energy, renewable energy industries such as wind power and solar energy are rising rapidly. These emerging energy industries are not only driving the transformation of traditional energy structures towards a greener and more sustainable direction, but also generating a large amount of data information, which is essential for optimizing energy production and management. In order to more effectively manage and maintain the increasingly large energy sites, the centralized control center management model came into being. This model integrates advanced information technology and communication technology to achieve centralized monitoring and management of energy generation equipment scattered in different locations. In the prior art, the centralized control center receives relevant data information from the power generation equipment in the site through the communication network, and then the operators of the centralized control center perform statistical analysis on the data information, and then the operators arrange the fault maintenance work of the power generation equipment according to the analysis results. However, in the prior art, the centralized control center relies on manual analysis and fault handling of the relevant data information of the power generation equipment in the site, which may lead to excessive processing time and introduce human errors, thereby affecting the efficient operation of the power generation equipment.

[0039] In order to solve the above technical problems, the embodiments of the present application propose the following technical concepts: The inventors think that in order to effectively manage power generation and energy transmission equipment, it is necessary to comprehensively consider the equipment operating status, output power and related environmental conditions. By collecting these data in real time, screening and identifying abnormal information, and further analyzing the reliability indicators of the equipment. At the same time, combined with the output power and environmental data of the equipment, the power utilization rate can be calculated at different stages of energy conversion and transmission, thereby evaluating the energy efficiency of the entire site. Finally, the reliability index and power utilization rate are displayed in an interface. The following is a detailed description using a detailed embodiment.

[0040] Figure 1 Schematic diagram of application scenario of risk status assessment of power generation equipment provided by an embodiment of the present invention. Figure 1As shown, the scene includes: a station 10, computer equipment 20 and a centralized control center 30.

[0041] Wherein, the station 10 provides relevant data to the computer device 20;

[0042] The computer device 20 processes and analyzes the data obtained from the site 20 to obtain reliability indicators and power utilization.

[0043] The centralized control center 30 is used to display the data obtained from the computer device 20 .

[0044] based on Figure 1 In the application scenario, this embodiment provides a method for assessing the risk status of power generation equipment, and the execution subject can be Figure 1 The computer device shown is not particularly limited in this embodiment. Figure 2 A flow chart of a method for assessing the risk status of power generation equipment provided in one embodiment of the present application is shown in FIG. Figure 2 As shown, the method includes:

[0045] S201: Acquire relevant data of the site, the relevant data including: environmental data of the site, operating status data of each target device in the site, communication data of each target device and output power of each target device, each target device includes at least one power generation device and at least one energy transmission device, and the environmental data is related to the type of each power generation device.

[0046] Among them, the station refers to the new energy station, which is a facility that uses renewable resources such as wind and solar energy to generate electricity. Such stations usually include multiple key equipment, such as power generation equipment and energy transmission equipment, which work together to generate and transmit electricity.

[0047] Among them, the relevant data of the station can be obtained through four methods: telemetry, telepulse, remote control and telesignaling, and the relevant data of the station can also be obtained from the centralized control center.

[0048] Among them, environmental data is data used to describe the environment in which the station is located. The collected environmental data is associated with the type of power generation equipment and is usually data that affects the operation of this type of power generation equipment. If the power generation equipment is a solar power generation equipment, the corresponding station environmental data may be: light intensity, light duration and temperature, etc.; if the power generation equipment is a wind power generation equipment, the corresponding station environmental data may be: wind speed, duration and wind direction, etc.

[0049] The operating status data of the power generation equipment is data used to describe the operating status of the power generation equipment. The operating status data of the power generation equipment may include: temperature or vibration; the operating status data of the energy transmission equipment may include: voltage, current or load rate.

[0050] The communication data may include telephone dispatch, data signals, system operation status image information, number of devices or number of communication interruptions, and other communication contents.

[0051] It should also be noted that the communication data can be analyzed to obtain the communication status of each target device; wherein the communication status includes: maintaining communication and interrupting communication.

[0052] Among them, output power is an important indicator to measure the performance of electrical or mechanical equipment, which is directly related to the energy conversion efficiency and load capacity of the equipment.

[0053] The power generation equipment may include: solar power generation equipment and / or wind power generation equipment; the energy transmission equipment may include: inverters, transformers and / or cables.

[0054] S202: Filter out abnormal data from the operating status data and the communication data, and analyze the abnormal data to obtain reliability indicators of each target device.

[0055] Reliability indicators are a series of quantitative parameters used to measure the ability of equipment or systems to complete a given function under specified conditions and within a specified time. Reliability indicators may include: failure frequency, mean trouble-free operation time, mean troubleshooting time, mean maintenance interval time, mean maintenance time, power generation time of the power station, downtime, communication interruption time, inverter output power dispersion and / or string current dispersion rate and other key indicators.

[0056] Among them, S202 specifically includes:

[0057] S2021: Clean and format the operation status data and the communication data to obtain processed operation status data and processed communication data, wherein the cleaning is used to delete invalid data and the formatting is used to convert the data into a unified format.

[0058] S2022: If any processed running status data is greater than or equal to the running status data threshold, then determine that any processed running status data is abnormal data.

[0059] S2023: If any processed communication data is greater than or equal to the communication data threshold, then determine that any processed communication data is abnormal data.

[0060] S2024: Extract characteristic values ​​of abnormal data.

[0061] The feature value refers to the numerical value or parameter extracted from the abnormal data, which can represent or summarize the specific attributes or behavior patterns of the abnormal data.

[0062] S2025: Input the characteristic value into the corresponding safety prediction model to output the reliability index of the target device corresponding to the abnormal data.

[0063] Among them, the safety prediction model is a computational model that uses data analysis and machine learning techniques to output the reliability index of the target device.

[0064] In one possible example, different priorities can be assigned to each target device based on its reliability index, and the intensity of daily maintenance can be adjusted according to the corresponding priority. For example, if the failure frequency of a certain device is relatively high, a higher priority is set for the device, and the intensity of daily maintenance can be improved by increasing the inspection frequency, the frequency of collecting operating status data, and other operations.

[0065] S203: Determine the power utilization rate of each business stage according to the environmental data of the site, the output power of each power generation equipment, and the output power of each energy transmission equipment. The business stage includes: an energy conversion stage and an energy transmission stage.

[0066] Among them, power utilization refers to the ratio of the output power of the equipment to the input power. In the process of wind and / or solar energy conversion and transmission, power utilization is a key indicator to measure efficiency. It directly reflects the effective utilization of energy in the process from wind power generation and / or solar power generation to power transmission.

[0067] Among them, the energy conversion stage is to convert the original energy (such as wind energy or solar energy) into electrical energy, and the energy transmission stage is to transmit the electrical energy to the electrical equipment.

[0068] Among them, S203 specifically includes:

[0069] S2031: Calculate the input power of each power generation equipment according to the environmental data.

[0070] For example, if the power generation equipment is a solar power generation equipment, the light intensity of the current environment can be measured by a light intensity sensor, and the input power of the solar power generation equipment can be obtained by multiplying the measured light intensity by the area and efficiency of the solar panel.

[0071] Exemplarily, if the power generation equipment is a wind power generation equipment, an anemometer is used to measure the wind speed in the current environment, wherein the wind power generation equipment usually has a specific power curve, which describes the output power under different wind speeds. The input power of the wind power generation equipment can be obtained based on the measured wind speed and the power curve of the wind power generation equipment.

[0072] S2032: Determine the power utilization rate in the energy conversion stage according to the input power of each power generation device and the output power of each power generation device.

[0073] Among them, for a power generation device, the power utilization rate of the power generation device in the energy conversion stage can be the ratio of the output power of the power generation device to the input power of the power generation device, which can be specifically calculated by referring to the following calculation formula:

[0074]

[0075] S2033: Determine the power utilization rate in the energy transmission stage according to the output power of each power generation device and the output power of each energy transmission device.

[0076] Among them, for an energy transmission device, the power utilization rate of the energy transmission device in the energy transmission stage can be the ratio of the output power of the energy transmission device to the output power of the power generation device, which can be specifically calculated by referring to the following calculation formula:

[0077]

[0078] S204: The reliability index and the power utilization rate are displayed on an interface.

[0079] Among them, it can be displayed on the display screen of the centralized control center, or on any other display device.

[0080] In summary, we first collect relevant data within the site, then use these data to identify abnormal situations and analyze data to evaluate the reliability index of each target device; then combine environmental data and the output power of the equipment to calculate the power utilization rate in different business stages, such as the energy conversion stage and the energy transmission stage; finally, the reliability index and power utilization rate are displayed on the interface. This effectively avoids human errors caused by manual processing and ensures the accuracy of data analysis. In addition, this data processing method will not interfere with the efficient operation of power generation equipment, thereby ensuring the continuity and stability of energy production.

[0081] Based on the above embodiment, this embodiment further describes a process of displaying different data in different dimensions, which is described in detail as follows:

[0082] S301: Determine the power loss rate of each energy transmission device according to the power utilization rate in the energy transmission stage, and determine the power loss of each energy transmission device per unit time according to the power loss rate.

[0083] The power loss rate refers to the percentage of energy lost during energy transmission to the original energy. This loss is usually caused by physical phenomena such as resistance, friction, and heat exchange.

[0084] Among them, for an energy transmission device, the power loss rate of the energy transmission device in the energy transmission stage can be specifically calculated by referring to the following formula:

[0085] Power loss rate = (1-power utilization rate in energy transmission phase) * 100% (3)

[0086] Among them, for an energy transmission device, the power loss per unit time of the energy transmission device during the energy transmission stage can be the product of the power loss rate of the energy transmission device and the input power of the energy transmission device. For details, please refer to the following calculation formula:

[0087] The amount of power lost per unit time = the power consumption rate of the energy transmission device * the power of the energy transmission device (4)

[0088] Among them, the power loss of each energy transmission device per unit time can help us understand the amount of electrical energy lost due to low transmission efficiency within a certain time period, thereby making a more accurate assessment of the performance and maintenance needs of the equipment.

[0089] S302: The reliability index of each target device in each site, the power utilization rate of each business stage and the power loss of each energy transmission device per unit time are counted according to different dimensions to obtain the reliability index and power utilization rate of different dimensions. The different dimensions include: target device, site, region and owner.

[0090] The above data can also be counted horizontally and vertically. Horizontal analysis refers to the data statistics of the above data at the same time point; vertical analysis refers to the data statistics of a certain data in different time periods.

[0091] Furthermore, a comparative analysis model can be established to analyze the impact of management plans or equipment anomalies on reliability indicators, power utilization, and power loss, so that operation and maintenance personnel can find out the causes that affect reliability indicators, power utilization, and power loss. Among them, management plans include production plans, operation and maintenance plans, power grid dispatching, etc., and equipment anomalies include equipment failures, equipment communication interruptions, etc. For example, for data at the same time point, analyze the commonalities of management plans or equipment anomalies at that time point to analyze the specific causes; for a certain data, analyze the commonalities of management plans or equipment anomalies in different time periods to analyze the specific causes.

[0092] Specifically, first, according to the analysis needs, the data is appropriately transformed, such as standardization, normalization, etc. Secondly, the data is grouped and further classified or segmented as needed. For example, data groups in different time periods can be dynamically compared, and data groups at the same time point can be statically compared. Then, comparative analysis is performed, including descriptive statistics, comparative analysis, and visual analysis. Descriptive statistical analysis, such as mean, median, standard deviation, etc., is performed on each comparison group to understand the basic situation of each group. Statistical methods, such as analysis of variance, chi-square test, etc., are used to compare whether the differences between different groups are significant. The differences and trends between groups are intuitively displayed through charts, such as bar charts, line charts, box plots, etc. Finally, based on the results of the comparative analysis, the differences between the groups and their possible reasons are explained.

[0093] S303: Reliability indicators, power utilization and power loss are displayed in a list according to different dimensions, and the dimensions of the reliability indicators with abnormalities are prompted.

[0094] Among them, it can also be displayed in a combination of numbers, lists and visual charts.

[0095] Among them, a red background can be used to highlight the dimensions of the reliability indicators that have abnormalities.

[0096] S304: For any dimension, the reliability index, power utilization rate and power loss curves of any dimension changing with time are respectively displayed.

[0097] S305: Statistically analyzing the environmental data of the station to obtain environmental resource indicators of the station, where the environmental data includes at least one of the following: real-time wind speed data and real-time light data, and the environmental resource indicators include at least one of the following: average wind speed, wind frequency diagram, wind rose diagram, average light intensity, total light intensity, peak sunshine duration, and equivalent peak sunshine duration;

[0098] Among them, the wind frequency diagram, also known as the wind direction rose diagram or wind frequency and wind speed rose diagram, is a meteorological statistical diagram. Its main purpose is to show the frequency and wind speed of wind in different directions in a region within a specific time.

[0099] Among them, the average light intensity refers to the average value of the luminous flux received per unit area within a certain period of time.

[0100] The total light intensity refers to the total light energy received by an area within a specific time period.

[0101] Among them, peak sunshine duration refers to the time when the solar radiation intensity reaches its highest value in a day.

[0102] Among them, the equivalent peak sunshine duration is an indicator that equates the actual sunshine duration to the theoretical peak sunshine duration. It evaluates its power generation capacity relative to the peak period by converting the actual sunshine duration in different time periods.

[0103] S306: Arrange and display the environmental resource indicators in a preset order.

[0104] The preset order may include: sorting according to the importance of environmental resource indicators, wherein the importance is preset.

[0105] In summary, we first analyze the power utilization rate in the energy transmission stage to determine the power loss rate of the equipment, and then calculate the power loss per unit time. Next, the reliability indicators and power utilization rates of different dimensions (such as equipment, stations, regions, and owners) are counted and displayed in a list form, and any abnormal reliability indicators are specially prompted. In addition, a curve chart showing the change of each indicator over time will be displayed, as well as statistical analysis of the environmental data of the station, such as wind speed and light data, to obtain the corresponding environmental resource indicators, which will be arranged and displayed according to the preset order. Through comprehensive performance analysis and data visualization of energy equipment, energy management can be optimized, equipment maintenance can be more efficient, and energy output and overall reliability can be improved.

[0106] It should also be noted that all the data obtained above can be imported into a database, and can be imported, exported, queried and / or modified regularly.

[0107] Figure 3 The present invention provides a device for evaluating the risk status of power generation equipment. Figure 3 As shown, the device for evaluating the risk status of power generation equipment is applied to a computer device, and includes: an acquisition module 401 , an analysis module 402 , a determination module 403 and a display module 404 .

[0108] Acquisition module 401: used to acquire relevant data of the site, the relevant data including: environmental data of the site, operating status data of each target device in the site, communication data of each target device and output power of each target device, each target device includes at least one power generation device and at least one energy transmission device, and the environmental data is related to the type of each power generation device.

[0109] Analysis module 402: used to filter out abnormal data from the operation status data and communication data, and analyze the abnormal data to obtain the reliability index of each target device.

[0110] Determination module 403: used to determine the power utilization rate of each business stage according to the environmental data of the site, the output power of each power generation equipment, and the output power of each energy transmission equipment. The business stage includes: energy conversion stage and energy transmission stage.

[0111] Display module 404: used to display the reliability index and power utilization rate on the interface.

[0112] In one possible design, the determination module 403 is specifically used to calculate the input power of each power generation device based on environmental data; determine the power utilization rate in the energy conversion stage based on the input power of each power generation device and the output power of each power generation device; determine the power utilization rate in the energy transmission stage based on the output power of each power generation device and the output power of each energy transmission device.

[0113] In one possible design, the analysis module 402 is specifically used to clean and format the operating status data and the communication data to obtain processed operating status data and processed communication data, wherein the cleaning is used to delete invalid data, and the formatting is used to convert the data into a unified format; if any processed operating status data is greater than or equal to an operating status data threshold, then any processed operating status data is determined to be abnormal data; if any processed communication data is greater than or equal to a communication data threshold, then any processed communication data is determined to be abnormal data; extract characteristic values ​​of the abnormal data; input the characteristic values ​​into a corresponding safety prediction model to output a reliability index of a target device corresponding to the abnormal data.

[0114] In one possible design, the display module 404 is specifically used to determine the power loss rate of each energy transmission device according to the power utilization rate in the energy transmission stage, and determine the power loss of each energy transmission device per unit time according to the power loss rate; the reliability index of each target device in each site, the power utilization rate of each business stage and the power loss of each energy transmission device per unit time are counted according to different dimensions to obtain reliability index and power utilization rate of different dimensions, and the different dimensions include: target device, site, region and owner; the reliability index, power utilization rate and power loss are displayed in the form of a list according to different dimensions, and the dimensions of the reliability index with abnormalities are prompted.

[0115] Among them, for any dimension, the curves of the reliability index, power utilization and power loss of any dimension changing with time are displayed respectively.

[0116] Among them, the environmental data of the station are statistically analyzed to obtain the environmental resource indicators of the station, the environmental data include at least one of the following: real-time wind speed data and real-time light data, the environmental resource indicators include at least one of the following: average wind speed, wind frequency diagram, wind rose diagram, average light intensity, total light intensity, peak sunshine duration, equivalent peak sunshine duration; the environmental resource indicators are arranged and displayed in a preset order.

[0117] The device provided in this embodiment can be used to execute the technical solution of the above method embodiment. Its implementation principle and technical effect are similar, and this embodiment will not be repeated here.

[0118] Figure 4 Schematic diagram of the hardware structure of the computer device provided in the embodiment of the present application. Figure 4 As shown, the computer device includes: at least one processor 501 and a memory 502; the memory stores computer execution instructions; at least one processor executes the computer execution instructions stored in the memory, so that at least one processor executes the above-mentioned method for assessing the risk status of power generation equipment.

[0119] Optionally, the memory 502 may be independent or integrated with the processor 501 .

[0120] When the memory 502 is independently provided, the computer device further includes a bus 503 for connecting the memory 502 and the processor 501 .

[0121] The embodiment of the present application also provides a computer storage medium, in which computer execution instructions are stored. When a processor executes the computer execution instructions, the above-mentioned method for assessing the risk status of power generation equipment is implemented.

[0122] An embodiment of the present application also provides a computer program product, including a computer program, which, when executed by a processor, implements the above-mentioned method for assessing the risk status of power generation equipment.

[0123] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the above modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or modules, which can be electrical, mechanical or other forms.

[0124] The modules described above as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to implement the solution of this embodiment.

[0125] In addition, each functional module in each embodiment of the present application can be integrated into one processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit. The above-mentioned module-composed unit can be implemented in the form of hardware or in the form of hardware plus software functional units.

[0126] The above-mentioned integrated module implemented in the form of a software function module can be stored in a computer-readable storage medium. The above-mentioned software function module is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to perform some steps of the above-mentioned method in each embodiment of the present application.

[0127] It should be understood that the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the invention may be directly implemented as being executed by a hardware processor, or may be implemented by a combination of hardware and software modules in the processor.

[0128] The memory may include a high-speed RAM memory, and may also include a non-volatile storage NVM, such as at least one disk memory, and may also be a USB flash drive, a mobile hard disk, a read-only memory, a magnetic disk or an optical disk, etc.

[0129] The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the bus in the drawings of the present application is not limited to only one bus or one type of bus.

[0130] The above storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), electrically erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The storage medium can be any available medium that can be accessed by a general or special computer.

[0131] An exemplary storage medium is coupled to a processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an application specific integrated circuit (ASIC). Of course, the processor and the storage medium can also exist as discrete components in an electronic device or a main control device.

[0132] Those skilled in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, disk or optical disk and other media that can store program codes.

[0133] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for assessing the risk status of power generation equipment, characterized in that: include: Acquire relevant data of the site, the relevant data including: environmental data of the site, operating status data of each target device in the site, communication data of each target device and output power of each target device, each target device including at least one power generation device and at least one energy transmission device, and the environmental data is related to the type of each power generation device; Filtering abnormal data from the operating status data and the communication data, and analyzing the abnormal data to obtain reliability indicators of each target device; Determine the power utilization rate of each business stage according to the environmental data of the site, the output power of each power generation device, and the output power of each energy transmission device, wherein the business stage includes: an energy conversion stage and an energy transmission stage; The reliability index and the power utilization rate are displayed on an interface.

2. The method according to claim 1, characterized in that Determining the power utilization rate of each business stage according to the environmental data of the site, the output power of each power generation device, and the output power of each energy transmission device includes: Calculate the input power of each power generation device according to the environmental data; Determining the power utilization rate in the energy conversion stage according to the input power of each power generation device and the output power of each power generation device; The power utilization rate in the energy transmission stage is determined according to the output power of each power generation device and the output power of each energy transmission device.

3. The method according to claim 1, characterized in that: The step of filtering out abnormal data from the operation status data and the communication data, and analyzing the abnormal data to obtain the reliability index of each target device includes: Cleaning and formatting the operation status data and the communication data to obtain processed operation status data and processed communication data, wherein the cleaning is used to delete invalid data and the formatting is used to convert the data into a unified format; If any processed running status data is greater than or equal to the running status data threshold, determining that any processed running status data is abnormal data; If any processed communication data is greater than or equal to the communication data threshold, determining that any processed communication data is abnormal data; Extracting characteristic values ​​of the abnormal data; The characteristic value is input into a corresponding safety prediction model to output a reliability index of a target device corresponding to the abnormal data.

4. The method according to any one of claims 1 to 3, characterized in that The interface displaying the reliability index and the power utilization rate includes: Determine the power loss rate of each energy transmission device according to the power utilization rate in the energy transmission stage, and determine the power loss of each energy transmission device per unit time according to the power loss rate; The reliability index of each target device in each station, the power utilization rate of each service stage and the power loss of each energy transmission device per unit time are statistically analyzed according to different dimensions to obtain the reliability index and the power utilization rate of different dimensions, wherein the different dimensions include: the target device, station, region and owner; The reliability index, the power utilization rate and the power loss are displayed in a list according to the different dimensions, and the dimension of the reliability index with abnormality is prompted.

5. The method according to claim 4, characterized in that After displaying the reliability index, the power utilization rate and the power loss in the form of a list according to the different dimensions and prompting the dimension where the reliability index is abnormal, the method further includes: For any dimension, the curves showing changes of the reliability index, the power utilization rate and the power loss over time in any dimension are respectively displayed.

6. The method according to claim 2, characterized in that The method further comprises: Performing statistical analysis on the environmental data of the station to obtain environmental resource indicators of the station, the environmental data including at least one of the following: real-time wind speed data and real-time light data, and the environmental resource indicators including at least one of the following: average wind speed, wind frequency diagram, wind rose diagram, average light intensity, total light intensity, peak sunshine duration, equivalent peak sunshine duration; The environmental resource indicators are arranged and displayed in a preset order.

7. A device for assessing the risk status of power generation equipment, characterized in that: include: Acquisition module: acquires relevant data of the site, the relevant data including: environmental data of the site, operation status data of each target device in the site, communication data of each target device and output power of each target device, each target device includes at least one power generation device and at least one energy transmission device, and the environmental data is related to the type of each power generation device; Analysis module: Screening out abnormal data from the operation status data and the communication data, and analyzing the abnormal data to obtain reliability indicators of each target device; Determination module: Determine the power utilization rate of each business stage according to the environmental data of the site, the output power of each power generation equipment, and the output power of each energy transmission equipment, wherein the business stage includes: energy conversion stage and energy transmission stage; Display module: display the reliability index and the power utilization rate on an interface.

8. A computer device, characterized in that: include: at least one processor and memory; The memory stores computer-executable instructions; The at least one processor executes the computer-executable instructions stored in the memory, so that the at least one processor performs the method for assessing the risk status of power generation equipment according to any one of claims 1 to 6.

9. A computer storage medium, characterized in that: The computer storage medium stores computer executable instructions, and when the processor executes the computer executable instructions, the method for assessing the risk status of power generation equipment according to any one of claims 1 to 6 is implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the method for assessing the risk status of power generation equipment according to any one of claims 1 to 6 is implemented.

Images