A networked fault warning system for wind turbines based on the Internet of Things

Abstract

This application discloses a networked fault warning system for wind turbines based on the Internet of Things (IoT), relating to the technical field of power generation fault warning. The method includes: an abnormality judgment module that collects operating information from the wind turbine and determines whether the wind turbine is abnormal; an equipment judgment module that determines whether the wind turbine is abnormal and obtains an equipment judgment result; a benefit evaluation module that obtains a real-time control plan and evaluates positive and negative benefits if the wind turbine is not abnormal; a first judgment module that determines whether the control is faulty; a second judgment module that obtains control information and determines whether the control is faulty if the wind turbine is not abnormal; a fault severity module that extracts fault information and evaluates the fault severity; and a fault warning module that generates a fault warning plan and implements the fault warning plan. This application improves the comprehensiveness of networked fault warning for wind turbines based on the IoT.

Description

Technical Field

[0001] The present application relates to the technical field of power generation fault early warning, and in particular to a networked fault early warning system for wind power generation groups based on the Internet of Things. Background Art

[0002] The networked fault warning system for wind turbines is a fault prediction system based on modern information technology. It aims to enable real-time online monitoring of wind turbine operating status, health diagnosis, fault warning, and scientific maintenance through remote internet technology. The networked fault warning system for wind turbines can be applied to wind farms and wind turbines of all sizes. By monitoring and analyzing the operating status of wind turbines in real time, the system can promptly detect and warn of various faults and anomalies, such as generator failures, gearbox failures, and blade failures. The system also provides maintenance recommendations and overhaul plans, helping operators better manage and maintain wind turbines. However, most wind turbines currently utilize semi-automatic or fully automatic control. Conventional wind turbine fault warning systems typically only provide warnings for wind turbine equipment, without considering other types of faults. Consequently, these warnings are incomplete and inaccurate. Summary of the Invention

[0003] The purpose of the present invention is to provide a networked fault warning system for wind turbines based on the Internet of Things to solve the problems raised in the above background technology.

[0004] This application provides a networked fault warning system for wind turbines based on the Internet of Things, which adopts the following technical solutions:

[0005] The abnormality judgment module collects the operating information of the wind power generation group through the arranged sensors and judges whether the wind power generation group is abnormal based on the operating information;

[0006] The equipment judgment module determines whether the wind power generation group is abnormal based on the operation information and obtains the equipment judgment result;

[0007] The benefit evaluation module obtains the real-time control plan if the fault is not a wind turbine equipment failure, and evaluates the positive and negative benefits of the real-time control plan;

[0008] The first judgment module judges whether the control of the wind turbine generator set is faulty based on the positive benefits and negative benefits, and obtains a control judgment result;

[0009] The second judgment module obtains control information of the wind power generation group if there is no abnormality in the wind power generation group, judges whether the control of the wind power generation group is faulty based on the control information, and obtains a control judgment result;

[0010] The fault degree module extracts fault information based on the equipment judgment results and the control judgment results, and obtains the fault degree based on the fault information evaluation;

[0011] The fault warning module generates a fault warning plan based on the fault severity and fault information, implements the fault warning plan through the wind turbine network, and reminds users of wind turbine faults.

[0012] Preferably, if the wind power generation group is abnormal, the step of determining whether it is an equipment failure of the wind power generation group according to the operation information and obtaining the equipment determination result is specifically:

[0013] Extracting the operating parameters of the wind turbine generator set equipment based on the operating information and recording them as real-time operating parameters;

[0014] Obtain historical fault parameters of wind turbine equipment and extract complete fault parameter range based on the historical fault parameters;

[0015] Determine whether the real-time operating parameters are within the complete fault parameter range. If the real-time operating parameters are within the complete fault parameter range, determine that the device is faulty.

[0016] If the real-time operating parameters are not within the complete fault parameter range, the historical operating parameters of the wind turbine generator set are collected, and the frequency of the real-time operating parameters within the historical operating parameters is extracted and recorded as the operating frequency;

[0017] Count the frequency of real-time operating parameters within historical fault parameters and record it as historical frequency;

[0018] The failure probability within the non-complete failure parameter range is obtained by combining the operating frequency and historical frequency evaluation;

[0019] It is determined whether the fault probability reaches a preset fault probability threshold. If so, it is determined that the equipment is faulty; otherwise, it is determined that the equipment of the wind turbine generator set is not faulty.

[0020] Preferably, if the fault is not an equipment failure of the wind turbine generator set, the steps of obtaining a real-time control solution and evaluating the positive and negative benefits of the real-time control solution are specifically as follows:

[0021] Obtain a real-time control plan for the wind turbine generator set, extract the power operation status before the real-time control plan is implemented and record it as the original power status;

[0022] Obtain the power operation status after the real-time control plan is implemented and record it as the real-time power status;

[0023] Compare the original power situation with the real-time power situation, extract the problems solved by the real-time control solution and record them as solved problems, and extract the problems generated by the real-time control solution and record them as generated problems;

[0024] The problem benefits of solving problems and generating problems are evaluated separately, and the positive and negative benefits are calculated based on the problem benefits.

[0025] Preferably, the steps of respectively evaluating the problem benefits of solving the problem and the problem benefits of generating the problem, and calculating the positive benefits and negative benefits based on the problem benefits, are specifically as follows:

[0026] Determine whether the problem is completely solved. If not, count the duration of solving the problem and record it as the resolution time.

[0027] Count the number of electricity users covered by the problem solution and confirm the diversity value of the problem solution;

[0028] Set the proportional coefficients of the solution time, the number of electricity users, and the diversity value respectively, and calculate the problem benefit of solving the problem based on the proportional coefficients;

[0029] If the problem is completely solved, the difficulty of solving the problem is evaluated, and the benefit of solving the problem is obtained by combining the number and diversity of electricity users;

[0030] Count all the benefits of solving problems and get the positive benefits;

[0031] Obtain the duration of the problem, the number of electricity users covered, and the diversity value, obtain the problem benefit of the problem, count the problem benefits of all problems, and obtain the negative benefit.

[0032] Preferably, the steps of counting the number of electricity users covered by the problem solution and determining the diversity value of the problem solution are specifically as follows:

[0033] Classify the problems in the wind power generation group into categories to obtain multiple problem categories;

[0034] Divide problem solving into categories and count the number of categories to which the problem solving belongs;

[0035] Collect factors affecting the wind turbine generator set that affect the problem, and count the number of factors as the number of factors;

[0036] Extract the source causes of problem solving, count the number of source causes and record it as the number of causes;

[0037] The weight ratios of the number of types, the number of factors, and the number of causes are set respectively, and the diversity value of problem solving is calculated based on the weight ratios.

[0038] Preferably, the step of determining whether the control of the wind turbine generator set is faulty by combining the positive benefits and the negative benefits to obtain the control determination result is specifically as follows:

[0039] Determine whether the positive benefits outweigh the negative benefits. If not, determine the severity of the problem to be solved and determine whether to resolve it based on the severity.

[0040] If the problem is solved, it is determined whether negative benefits are incurred; if not, it is determined that a fault has occurred in the control of the wind turbine generator set;

[0041] If negative benefits are incurred, determine whether there is a replacement plan. If there is no replacement plan, determine that there is no fault in the wind turbine control.

[0042] If there is a replacement plan, compare the real-time control plan with the replacement plan to confirm whether the wind turbine control fails;

[0043] If the problem is not solved, it is determined that a fault has occurred in the control of the wind turbine generator set.

[0044] Preferably, the steps of obtaining the severity of the problem to be solved and determining whether to solve the problem according to the severity are specifically:

[0045] Obtain historical processing records, count the frequency of problem resolution and record it as the processing frequency;

[0046] Collect the consequences of not solving the problem, and extract the impact scope of solving the problem based on the consequences;

[0047] Combine the problem benefit, treatment frequency and impact scope of the problem to get the severity of the problem;

[0048] Count the severity of all problems solved and use it as the problem degree of the problem solved;

[0049] Determine whether the severity of the problem has reached a preset severity threshold. If so, determine to resolve the problem; otherwise, determine not to resolve the problem.

[0050] Preferably, if there is a replacement solution, the step of comparing the real-time control solution with the replacement solution to confirm whether the wind turbine control fails is specifically as follows:

[0051] Superimpose the positive and negative benefits of the real-time control scheme to obtain the real-time benefits of the real-time control scheme;

[0052] Obtain the positive and negative benefits of the replacement plan and calculate the replacement benefit of the replacement plan;

[0053] Compare the real-time benefits and the replacement benefits, and determine whether the replacement benefits of the replacement plan are greater than the real-time benefits;

[0054] If the replacement benefit is greater than the real-time benefit, it is determined that a fault occurs in the control of the wind power generation group; otherwise, it is determined that there is no fault in the control of the wind power generation group.

[0055] Preferably, if the wind power generation group has no abnormality, the step of obtaining control information of the wind power generation group, judging whether the control of the wind power generation group has a fault according to the control information, and obtaining a control judgment result is specifically as follows:

[0056] If there is no abnormality in the wind turbine generator set, real-time control information of the wind turbine generator set is obtained, and the control reaction time and control reaction steps are extracted;

[0057] Obtain historical control information, and calculate the average response time of the control response based on the historical control information;

[0058] Standard steps for obtaining control responses based on historical control information;

[0059] According to the standard steps, it is judged whether the control reaction step meets the standard. If it meets the standard, the time difference between the control reaction time and the average reaction time is calculated;

[0060] A difference range is pre-set to determine whether the time difference is within the difference range. If so, it is determined that there is no control failure; otherwise, it is determined that a control failure occurs.

[0061] If the control reaction step does not meet the standard, it is judged that the control has failed.

[0062] Preferably, the steps of extracting fault information based on the device judgment result and the control judgment result, and evaluating the fault degree based on the fault information, are specifically as follows:

[0063] If the device fails, the device failure information is obtained, and the degree of the device failure is obtained according to the device failure condition evaluation as the failure degree;

[0064] If there is a control failure, control failure information is obtained, and the control failure degree is obtained according to the control failure situation evaluation as the failure degree.

[0065] In summary, this application includes at least one of the following beneficial technical effects:

[0066] 1. Based on the wind turbine operating information collected by sensors, determine whether the wind turbine is experiencing anomalies. Based on the anomaly results, determine whether the wind turbine's equipment or control is faulty. Generate a fault warning plan based on the fault information and judgment results, providing a more comprehensive assessment of whether automatic control failures have occurred, thus improving the comprehensiveness of IoT-based wind turbine network fault warnings.

[0067] 2. Based on the positive and negative benefits of the real-time control solution, combined with the judgment results such as whether the problem has been resolved and whether negative benefits have been incurred, a comprehensive analysis is conducted to determine whether there is a problem with the control of the wind turbine group, and the judgment results of the control failure are obtained more accurately, thereby improving the accuracy of the networked fault warning of the wind turbine group based on the Internet of Things.

[0068] 3. The problem diversity value is determined by summing the source, influencing factors, and the number of problem types. The problem benefit is then determined by combining parameters such as the problem resolution time, difficulty, and the number of electricity users affected by the problem. Establishing the problem benefit helps confirm whether the control solution is faulty and determines whether the control is faulty based on the actual benefit. This is more realistic and improves the practicality of IoT-based networked fault warning for wind turbines. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 The present invention is a schematic diagram of module connections of an embodiment of a networked fault warning system for wind power generation groups based on the Internet of Things. DETAILED DESCRIPTION

[0070] Below is a combination of the embodiments and Figure 1 The present invention will be described in further detail, but the embodiments of the present invention are not limited thereto.

[0071] The present invention discloses a networked fault early warning system for wind power generation groups based on the Internet of Things, which specifically includes:

[0072] The abnormality judgment module collects the operating information of the wind power generation group through the arranged sensors, and judges whether the wind power generation group is abnormal based on the operating information.

[0073] Different sensors can collect different information. For example, temperature sensors can collect temperature information of wind turbine equipment, and vibration sensors can collect vibration information of wind turbine equipment. The arranged sensors can collect operating information of wind turbines.

[0074] The equipment judgment module determines whether the wind power generation group is abnormal based on the operation information and obtains the equipment judgment result.

[0075] The benefit evaluation module obtains a real-time control plan if the fault is not in the wind turbine generator set, and evaluates the positive and negative benefits of the real-time control plan.

[0076] The first judgment module judges whether the control of the wind power generation group is faulty by combining the positive benefits and the negative benefits, and obtains a control judgment result.

[0077] The second judgment module obtains control information of the wind power generation group if there is no abnormality in the wind power generation group, judges whether the control of the wind power generation group is faulty according to the control information, and obtains a control judgment result.

[0078] The fault degree module extracts fault information based on the equipment judgment results and the control judgment results, and obtains the fault degree based on the fault information evaluation.

[0079] The fault warning module generates a fault warning plan based on the fault severity and fault information, implements the fault warning plan through the wind turbine network, and reminds users of wind turbine faults.

[0080] In practice, different fault severity levels require different fault warning schemes. For example, different warning sounds can be set to indicate faults of varying severity. Implementing different warning schemes for different faults helps users immediately understand the severity of the fault, allowing for timely repairs and mitigating losses. Fault information is synchronized with the user, allowing them to promptly develop appropriate repair plans based on the fault information.

[0081] If the wind turbine generator set is abnormal, the steps of determining whether it is an equipment failure of the wind turbine generator set according to the operation information and obtaining the equipment judgment result are as follows:

[0082] The operating parameters of the wind turbine equipment are extracted based on the operating information and recorded as real-time operating parameters.

[0083] Wind turbine equipment has corresponding parameters during operation, such as rated power, wind speed, etc.

[0084] Obtain historical fault parameters of wind turbine equipment and extract the complete fault parameter range based on the historical fault parameters.

[0085] Historical fault parameters are extracted from the wind turbine's data repository. The complete fault range indicates that the equipment is definitely faulty. For example, if the generator's vibration amplitude exceeds a specified threshold, or the vibration acceleration exceeds 0.1g (gravity), this may indicate bearing damage, imbalance, or installation problems. In this case, the generator is considered to be faulty. Therefore, a vibration acceleration greater than 0.1g is considered within the complete fault range.

[0086] It is determined whether the real-time operating parameters are within the complete failure parameter range. If the real-time operating parameters are within the complete failure parameter range, it is determined that the device is faulty.

[0087] If the real-time operating parameter is not within the complete fault parameter range, the historical operating parameters of the wind turbine generator set are collected, and the frequency of the real-time operating parameter within the historical operating parameters is extracted and recorded as the operating frequency.

[0088] The frequency of real-time operating parameters within historical fault parameters is counted and recorded as historical frequency.

[0089] The frequency of historical fault parameters within the range of non-complete fault parameters is counted and recorded as the historical frequency.

[0090] The failure probability within the non-complete failure parameter range is evaluated by combining the operating frequency and historical frequency.

[0091] Set the weight ratio of the operating frequency and historical frequency separately, and calculate the failure probability based on the weight ratio. When the operating frequency is higher, it means that more devices are operating within the parameter range, and the failure probability is lower. On the other hand, when the historical frequency is higher, it means that the probability of failure of devices within the parameter range in historical failures is greater, and therefore the failure probability is higher.

[0092] It is determined whether the fault probability reaches a preset fault probability threshold. If so, it is determined that the equipment is faulty; otherwise, it is determined that the equipment of the wind turbine generator set is not faulty.

[0093] In actual operation, when a wind turbine generator system experiences an anomaly, it could be caused by either the equipment or the control. First, determine whether it's an equipment failure based on the equipment's operating parameters. Generally, control won't cause a failure; it's simply a slight deviation in the operating parameters. Therefore, if the equipment's operating parameters indicate a definite equipment failure, the fault is confirmed. If the operating parameters don't indicate a definite equipment failure, the judgment is based on the actual failure probability, reducing the possibility of fault warning errors.

[0094] If the wind turbine generator system is not faulty, the steps for obtaining a real-time control solution and evaluating the positive and negative benefits of the real-time control solution are as follows:

[0095] A real-time control plan for the wind turbine generator set is obtained, and the power operation status before the real-time control plan is implemented is extracted and recorded as the original power status.

[0096] The power situation includes but is not limited to the user's power demand, the stability of the power grid, the power dispatch, etc., which are collected through the control system of the wind power generation group to obtain a real-time control plan.

[0097] The power operation status after the real-time control plan is implemented is obtained and recorded as the real-time power status.

[0098] Comparing the original power situation with the real-time power situation, the problems solved by the real-time control solution are recorded as solved problems, and the problems generated by the real-time control solution are recorded as generated problems.

[0099] Controlling wind turbines is always intended to solve a problem. For example, when user electricity demand is unmet, wind turbines can be dispatched to provide more power to meet the user's needs. While the problem being solved is unmet user demand, the implementation of some control schemes can also have negative effects and create new problems. While satisfying user demand, this can also increase grid instability, creating a problem.

[0100] The problem benefits of solving problems and generating problems are evaluated separately, and the positive and negative benefits are calculated based on the problem benefits.

[0101] In practice, when selecting a control solution for a wind turbine, we tend to choose one with greater benefits and fewer drawbacks. Therefore, semi-automatic and fully automatic control also reflect this control strategy. Evaluating the positive and negative benefits of a control solution helps identify control failures. For example, if a control solution has no positive benefits but significant negative benefits, this clearly indicates a control error and a failure. Based on the positive and negative benefits, we can more accurately determine whether a control failure has occurred, thereby reducing the chances of control failures being overlooked.

[0102] The steps to evaluate the problem benefits of solving problems and those of causing problems respectively, and to calculate the positive and negative benefits based on the problem benefits are as follows:

[0103] Determine whether the problem is completely solved. If not, count the duration of solving the problem and record it as the resolution time.

[0104] In wind power generation, not all problems can be completely solved. For example, if a wind turbine fails to start, it may be possible to completely solve the problem by restarting it, while unstable wind energy can only be temporarily solved through a temporary adjustment solution.

[0105] Count the number of electricity users covered by the problem solution and confirm the diversity value of the problem solution.

[0106] The proportional coefficients of solution time, number of electricity users and diversity value are set respectively, and the problem benefit of solving the problem is calculated according to the proportional coefficients.

[0107] A longer resolution time indicates a better solution and greater benefits. The greater the number of electricity users covered, the wider the scope of the solution and the greater the benefits, for example, meeting the electricity needs of more people. A higher problem diversity value indicates a greater benefit from resolving the problem, as it addresses more aspects of the problem and generates greater benefits.

[0108] If the problem is completely solved, the difficulty of solving the problem is evaluated, and the benefit of solving the problem is obtained based on the number and diversity of electricity users.

[0109] The problem benefit is calculated based on the weighted ratios for difficulty, number of electricity users, and diversity. The difficulty of solving a problem can be assessed by users. The greater the difficulty, the greater the benefit.

[0110] Count all the benefits of solving problems and get the positive benefits.

[0111] Sometimes a control solution does not solve a single problem, but may solve multiple problems. Therefore, the positive benefits generated by the control solution are the sum of the benefits of all the problems solved.

[0112] Obtain the duration of the problem, the number of electricity users covered, and the diversity value, obtain the problem benefit of the problem, count the problem benefits of all problems, and obtain the negative benefit.

[0113] In practice, the problem benefit of generating problems is evaluated in the same way as the problem benefit of solving problems, except that the problem benefit of generating problems is negative. Weights are set for the duration of the problem, the number of electricity users affected, and the diversity value, and the problem benefit is calculated based on the weighted ratios. The problem benefit of generating problems is always negative; that is, the greater the problem benefit of generating problems, the greater the negative benefit. The greater the number of electricity users affected by the problem, the greater the problem benefit, but the negative problem benefit is greater. In other words, the problem benefit of solving problems is always positive, while the problem benefit of generating problems is always negative. Similarly, the diversity value of generating problems is obtained in the same way as the diversity value of solving problems.

[0114] The steps to count the number of electricity users covered by the problem solution and confirm the diversity value of the problem solution are as follows:

[0115] Problems in the wind turbine generator set are classified into different categories to obtain multiple problem categories.

[0116] There are various types of problems in wind turbines, whether they cause problems or solve problems, and the types of problems include but are not limited to technical, economic, environmental, social, etc.

[0117] Divide the problem solving into categories according to the problem, and count the number of categories to which the problem solving belongs.

[0118] Some problems do not belong to a single type. They can be classified into technology or environment. In this case, the number of types to which the problem belongs is 2.

[0119] The factors affecting the wind turbine generator set that affect the problem are collected and the number of factors is counted and recorded as the number of factors.

[0120] The factors affecting wind turbines in problem solving are also different, including but not limited to wind turbine equipment, power grid, wind farm, etc. The more factors that affect the problem solving, the more changes will be brought about by handling the problem.

[0121] Extract the source causes of problem solving, count the number of source causes and record it as the number of causes.

[0122] The source of the problem to be solved varies. For example, there are many reasons for grid instability, such as load changes, reactive power imbalance, etc. The source of the problem can be extracted based on historical fault information.

[0123] The weight ratios of the number of types, the number of factors, and the number of causes are set respectively, and the diversity value of problem solving is calculated based on the weight ratios.

[0124] In practice, the greater the number of problem types, the more diverse the problem will be. Once the problem is solved, its impact will be felt across multiple levels, resulting in a higher diversity value. When more factors affect a wind turbine, the impact is more widespread, thus increasing the diversity of the problem. Similarly, the greater the number of source causes, the greater the likelihood of a problem arising, reflecting its diversity. The diversity value for the generated problem is derived using the same method described above: substituting the word "generated problem" for the word "solved problem" to obtain the resulting value.

[0125] The steps of judging whether the control of the wind turbine generator set is faulty by combining the positive benefits and the negative benefits and obtaining the control judgment result are as follows:

[0126] Determine whether the positive benefits outweigh the negative benefits. If the positive benefits do not outweigh the negative benefits, obtain the severity of the problem to be solved and determine whether to solve the problem based on the severity.

[0127] If the positive benefits do not outweigh the negative benefits, then the control scheme may be faulty. This is because when making control decisions, the control scheme with positive benefits outweighs negative benefits is often chosen. Otherwise, controlling the wind turbine may negatively impact the wind turbine. If the positive benefits do not outweigh the negative benefits, this does not necessarily indicate a control fault; further analysis is required based on the actual situation.

[0128] If the problem is solved, it is determined whether negative benefits are incurred; if not, it is determined that a fault occurs in the control of the wind turbine generator set.

[0129] If the problem is extremely serious, it must be addressed. In this case, addressing the problem comes at a cost. It's then necessary to determine whether the cost is affordable—in other words, whether the negative impacts are manageable. For example, if user electricity demand cannot be met, timely dispatch of wind turbines is necessary, but this would cause extreme grid instability. In this case, the stability level is acceptable. To determine whether the negative impacts are manageable, the maximum negative impact of all control schemes is extracted based on historical data. If the real-time negative impact is greater than the maximum negative impact, the negative impact is considered negligible. Otherwise, the negative impact is considered manageable.

[0130] If negative benefits are incurred, it is determined whether there is an alternative solution. If there is no alternative solution, it is determined that there is no fault in the control of the wind turbine generator set.

[0131] If negative consequences are acceptable, the system then searches historical data for alternative control solutions based on the actual situation. All other solutions that solve the same problem are considered as alternatives. If no other solutions are available, the problem must be solved, and the cost is acceptable, then the wind turbine control system has made the optimal control choice.

[0132] If there is a replacement plan, compare the real-time control plan with the replacement plan to confirm whether the wind turbine control fails.

[0133] If the problem is not solved, it is determined that a fault has occurred in the control of the wind turbine generator set.

[0134] In actual application, if the problem is not so serious and does not need to be dealt with and resolved, but the control of the wind turbine still chooses a control scheme in which the positive benefits are not greater than the negative benefits, it means that a fault has occurred in the control of the wind turbine. Because the implementation of the control scheme has not brought any benefits, the control scheme is inaccurate, reflecting a control error.

[0135] Get the severity of the problem to be solved and decide whether to solve it based on the severity. The steps are as follows:

[0136] Obtain historical processing records, count the frequency of problem resolution, and record it as the processing frequency.

[0137] The frequency of problem solving refers to the ratio of the number of times the problem is solved to the total number of times the problem exists, which is recorded as the processing frequency.

[0138] Collect the consequences of not solving the problem, and extract the impact scope of solving the problem based on the consequences of the problem.

[0139] The consequences of not addressing the problem are extracted based on historical data. The scope of impact includes the number of people and the area affected. The weight ratios of the number of people and the affected area are set respectively, and the scope of impact of solving the problem is calculated based on the weight ratio.

[0140] The severity of the problem to be solved is obtained by combining the problem benefit, processing frequency and impact scope of the problem to be solved.

[0141] Scale factors are set for the problem benefit, frequency of action, and scope of impact. The severity of the problem is calculated based on these scale factors. A greater benefit indicates greater negative consequences if the problem is not addressed, thus making the problem more serious. A higher frequency of action indicates that the problem should be addressed, thus reflecting a greater severity. A larger scope of impact directly indicates a greater severity because it affects more people.

[0142] The sum of the severity of all problems solved is counted as the problem degree of the problem solved.

[0143] Determine whether the severity of the problem has reached a preset severity threshold. If so, determine to resolve the problem; otherwise, determine not to resolve the problem.

[0144] In practice, because a control solution doesn't solve a single problem, the sum of the severity levels of all the problems solved is calculated as the severity level of all the problems, i.e., the severity level of the problem solved by the control solution. If the severity level is greater than the severity threshold, it indicates that the problem is serious and requires prompt resolution. If not, it is considered unnecessary.

[0145] If there is a replacement plan, the steps to compare the real-time control plan with the replacement plan to confirm whether the wind turbine control has failed are as follows:

[0146] The positive benefits and negative benefits of the real-time control scheme are superimposed to obtain the real-time benefits of the real-time control scheme.

[0147] Obtain the positive and negative benefits of the substitution plan and calculate the substitution benefit of the substitution plan.

[0148] The positive and negative benefits of the substitution plan are evaluated in the same way as the positive and negative benefits of the control plan, that is, they are also evaluated by solving problems and generating problems.

[0149] Compare the real-time benefits and the replacement benefits to determine whether the replacement benefits of any replacement plan are greater than the real-time benefits.

[0150] If the replacement benefit is greater than the real-time benefit, it is determined that a fault occurs in the control of the wind power generation group; otherwise, it is determined that there is no fault in the control of the wind power generation group.

[0151] In actual operation, if there are alternatives, the optimal control solution must be selected. The benefits of the real-time control solution and the alternative are compared to determine which one offers the highest benefits. If the wind turbine control system does not select the optimal solution, it indicates a control error. If the control system selects the optimal solution among multiple options, it indicates that the wind turbine has made the correct selection and the control is not faulty.

[0152] If the wind turbine generator set is normal, the steps of obtaining control information of the wind turbine generator set, determining whether the control of the wind turbine generator set is faulty based on the control information, and obtaining a control determination result are as follows:

[0153] If the wind turbine generator set has no abnormality, real-time control information of the wind turbine generator set is obtained, and the control reaction time and control reaction steps are extracted.

[0154] Sometimes the control solution may not be the optimal one, but its implementation will not affect the wind turbine, and the wind turbine can operate normally. At this time, it is difficult to find out whether the control is faulty. Real-time control information can be used to extract the control response time and control response steps in the control process.

[0155] Obtain historical control information, and calculate the average response time of the control response based on the historical control information.

[0156] The standard steps for obtaining control responses are extracted based on historical control information.

[0157] According to the standard steps, it is judged whether the control reaction step meets the standards. If it meets the standards, the time difference between the control reaction time and the average reaction time is calculated.

[0158] A difference range is set in advance to determine whether the time difference is within the difference range. If so, it is determined that there is no control failure; otherwise, it is determined that a control failure occurs.

[0159] If the control reaction step does not meet the standard, it is judged that the control has failed.

[0160] In actual operation, if the control strategy's execution steps are not standard, it means that a step may have been omitted or the execution steps may have been misplaced. This indicates that the control strategy has failed. Although the selected solution did not have a significant impact, it is not the optimal solution. If the control steps meet the standards, the control strategy's response time is determined to be within the allowed error. If it is not within the allowed error, it indicates a sluggish response and a problem within the control system, resulting in a control failure in the wind turbine.

[0161] The steps of extracting fault information based on the equipment judgment results and the control judgment results and evaluating the fault extent based on the fault information are as follows:

[0162] If the device fails, device failure information is obtained, and the degree of the device failure is obtained according to the device failure condition evaluation as the failure degree.

[0163] If there is a control failure, control failure information is obtained, and the control failure degree is obtained according to the control failure situation evaluation as the failure degree.

[0164] In actual operation, equipment failure conditions include operating parameters and lifespan. Based on existing equipment failure conditions, the severity of the failure is assessed using the device's light level. If the device is not faulty, the system determines whether it is a control failure. If so, the optimal control solution is extracted based on the control failure condition. The severity of the failure is then assessed based on the similarity between the real-time control solution and the optimal control solution. The lower the similarity, the greater the severity of the failure. Based on the actual fault type, the corresponding fault severity is determined and, combined with the fault information, transmitted to the user as a fault warning, effectively minimizing the damage caused by the fault to the wind turbine.

[0165] The above are all preferred embodiments of the present application, and are not intended to limit the scope of protection of the present application. Therefore, any equivalent changes made based on the structure, shape, and principle of the present application should be included in the scope of protection of the present application.

Claims

1. A networked fault warning system for wind turbines based on the Internet of Things, characterized in that: include: The abnormality judgment module collects the operating information of the wind power generation group through the arranged sensors and judges whether the wind power generation group is abnormal based on the operating information; The equipment judgment module determines whether the wind power generation group is abnormal based on the operation information and obtains the equipment judgment result; The benefit evaluation module obtains the real-time control plan if the fault is not a wind turbine equipment failure, and evaluates the positive and negative benefits of the real-time control plan; The first judgment module judges whether the control of the wind turbine generator set is faulty based on the positive benefits and negative benefits, and obtains a control judgment result; The second judgment module obtains control information of the wind power generation group if there is no abnormality in the wind power generation group, judges whether the control of the wind power generation group is faulty based on the control information, and obtains a control judgment result; The fault degree module extracts fault information based on the equipment judgment results and the control judgment results, and obtains the fault degree based on the fault information evaluation; The fault warning module generates a fault warning plan based on the fault severity and fault information, implements the fault warning plan through the wind turbine network, and reminds users of wind turbine faults; If the wind power generation group is abnormal, the step of determining whether it is an equipment failure of the wind power generation group according to the operation information and obtaining the equipment judgment result is specifically as follows: Extracting the operating parameters of the wind turbine generator set equipment based on the operating information and recording them as real-time operating parameters; Obtain historical fault parameters of wind turbine equipment and extract complete fault parameter range based on the historical fault parameters; Determine whether the real-time operating parameters are within the complete fault parameter range. If the real-time operating parameters are within the complete fault parameter range, determine that the device is faulty. If the real-time operating parameters are not within the complete fault parameter range, the historical operating parameters of the wind turbine generator set are collected, and the frequency of the real-time operating parameters within the historical operating parameters is extracted and recorded as the operating frequency; Count the frequency of real-time operating parameters within historical fault parameters and record it as historical frequency; The failure probability within the non-complete failure parameter range is obtained by combining the operating frequency and historical frequency evaluation; Determine whether the fault probability reaches a preset fault probability threshold. If so, determine that the equipment is faulty; otherwise, determine that the equipment of the wind turbine generator set is not faulty. If the wind turbine generator system is not faulty, the steps of obtaining a real-time control solution and evaluating the positive and negative benefits of the real-time control solution are as follows: Obtain a real-time control plan for the wind turbine generator set, extract the power operation status before the real-time control plan is implemented and record it as the original power status; Obtain the power operation status after the real-time control plan is implemented and record it as the real-time power status; Compare the original power situation with the real-time power situation, extract the problems solved by the real-time control solution and record them as solved problems, and extract the problems generated by the real-time control solution and record them as generated problems; Evaluate the problem benefits of solving problems and generating problems respectively, and calculate the positive and negative benefits based on the problem benefits; The step of determining whether the control of the wind turbine generator set is faulty by combining the positive benefits and the negative benefits to obtain the control determination result is specifically as follows: Determine whether the positive benefits outweigh the negative benefits. If not, determine the severity of the problem to be solved and determine whether to resolve it based on the severity. If the problem is solved, it is determined whether negative benefits are incurred; if not, it is determined that a fault has occurred in the control of the wind turbine generator set; If negative benefits are incurred, determine whether there is a replacement plan. If there is no replacement plan, determine that there is no fault in the wind turbine control. If there is a replacement plan, compare the real-time control plan with the replacement plan to confirm whether the wind turbine control fails; If the problem is not solved, it is determined that a fault has occurred in the control of the wind turbine generator set.

2. The networked fault warning system for wind turbine generators based on the Internet of Things according to claim 1 is characterized in that: The steps of respectively evaluating the problem benefits of solving problems and generating problems, and calculating the positive benefits and negative benefits based on the problem benefits are as follows: Determine whether the problem is completely solved. If not, count the duration of solving the problem and record it as the resolution time. Count the number of electricity users covered by the problem solution and confirm the diversity value of the problem solution; Set the proportional coefficients of solution time, number of electricity users and diversity value respectively, and calculate the problem benefit of solving the problem based on the proportional coefficients; If the problem is completely solved, the difficulty of solving the problem is evaluated, and the benefit of solving the problem is obtained by combining the number and diversity of electricity users; Count all the benefits of solving problems and get the positive benefits; Obtain the duration of the problem, the number of electricity users covered, and the diversity value, obtain the problem benefit of the problem, count the problem benefits of all problems, and obtain the negative benefit.

3. The networked fault warning system for wind turbine generators based on the Internet of Things according to claim 2 is characterized in that: The steps of counting the number of electricity users covered by the problem solution and confirming the diversity value of the problem solution are specifically as follows: Classify the problems in the wind power generation group into categories to obtain multiple problem categories; Divide problem solving into categories and count the number of categories to which the problem solving belongs; Collect factors affecting the wind turbine generator set that affect the problem, and count the number of factors as the number of factors; Extract the source causes of problem solving, count the number of source causes and record it as the number of causes; The weight ratios of the number of types, the number of factors, and the number of causes are set respectively, and the diversity value of problem solving is calculated based on the weight ratios.

4. The networked fault warning system for wind turbine generators based on the Internet of Things according to claim 1 is characterized in that: The steps of obtaining the severity of the problem to be solved and determining whether to solve the problem according to the severity are specifically as follows: Obtain historical processing records, count the frequency of problem resolution and record it as the processing frequency; Collect the consequences of not solving the problem, and extract the impact scope of solving the problem based on the consequences; Combine the problem benefit, treatment frequency and impact scope of the problem to get the severity of the problem; Count the severity of all problems solved and use it as the problem degree of the problem solved; Determine whether the severity of the problem has reached a preset severity threshold. If so, determine to resolve the problem; otherwise, determine not to resolve the problem.

5. The networked fault warning system for wind turbine generators based on the Internet of Things according to claim 4 is characterized in that: If there is a replacement plan, the steps of comparing the real-time control plan with the replacement plan to confirm whether the wind turbine control has a fault are as follows: Superimpose the positive and negative benefits of the real-time control scheme to obtain the real-time benefits of the real-time control scheme; Obtain the positive and negative benefits of the replacement plan and calculate the replacement benefit of the replacement plan; Compare the real-time benefits and the replacement benefits, and determine whether the replacement benefits of the replacement plan are greater than the real-time benefits; If the replacement benefit is greater than the real-time benefit, it is determined that a fault occurs in the control of the wind power generation group; otherwise, it is determined that there is no fault in the control of the wind power generation group.

6. The networked fault warning system for wind turbine generators based on the Internet of Things according to claim 1 is characterized in that: If the wind power generation group is normal, the steps of obtaining control information of the wind power generation group, determining whether the control of the wind power generation group is faulty according to the control information, and obtaining a control determination result are specifically as follows: If there is no abnormality in the wind turbine generator set, real-time control information of the wind turbine generator set is obtained, and the control reaction time and control reaction steps are extracted; Obtain historical control information, and calculate the average response time of the control response based on the historical control information; Standard steps for obtaining control responses based on historical control information; According to the standard steps, it is judged whether the control reaction step meets the standard. If it meets the standard, the time difference between the control reaction time and the average reaction time is calculated; A difference range is pre-set to determine whether the time difference is within the difference range. If so, it is determined that there is no control failure; otherwise, it is determined that a control failure occurs. If the control reaction step does not meet the standard, it is judged that the control has failed.

7. The networked fault warning system for wind turbine generators based on the Internet of Things according to claim 1 is characterized in that: The steps of extracting fault information based on the device judgment result and the control judgment result, and evaluating the fault degree based on the fault information are specifically as follows: If the device fails, the device failure information is obtained, and the degree of the device failure is obtained according to the device failure condition evaluation as the failure degree; If there is a control failure, control failure information is obtained, and the control failure degree is obtained according to the control failure situation evaluation as the failure degree.

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