Wind turbine generator running state online evaluation method

Abstract

The invention provides a wind turbine generator running state online evaluation method, which comprises the steps of selecting wind turbine generator running parameters and data thereof, and calculating a weight for a fuzzy comprehensive evaluation method based on a factor analysis method; determining a membership degree matrix of the online operation monitoring parameters of the wind turbine generator according to a relative degradation degree calculation method; obtaining a final online evaluation result of the running state of the wind turbine generator through a fuzzy evaluation method; and based on the actual SCADA data and the SPSS software platform, verifying the effectiveness of the online evaluation method for the running state of the wind turbine generator. According to the method, the wind turbine generator parameter weight can be updated in real time, the field operation requirement is better met, the operation state of the wind turbine generator can be objectively and comprehensively evaluated, the evaluation result is closer to the actual operation state, and therefore the advantages and disadvantages of the current operation state of the wind turbine generator are judged, and the operation state of the wind turbine generator is mastered in time; and decision-making assistance is provided for daily operation, maintenance and management.

Description

technical field [0001] The invention belongs to the technical field of evaluating the running state of a wind turbine, and in particular relates to an online evaluation method for the running state of a wind turbine. Background technique [0002] With the increase of wind turbine operation and maintenance costs, in order to operate and maintain wind farms in a healthy manner, keep abreast of the operating status and problems of wind turbines, and improve the operating efficiency and reliability of wind turbines, the most critical link is to operate and maintain wind turbines according to the wind turbines. Various existing online monitoring information, using specific data processing and analysis methods, conduct online evaluation of wind turbine operating performance. [0003] In the prior art, researchers generally use methods such as expert system, fuzzy method, and gray theory variable weight to analyze and evaluate the operating state of the unit. However, the knowledg...

AI Technical Summary

Problems solved by technology

However, the knowledge-based expert system uses historical experience and expert knowledge to form a knowledge base, which is difficult to update and maintain, which limits its practical application to a certain extent and affects the practicability of the method

In the fuzzy evaluation method, the determination of parameter weights depends on the update of the expert knowledge base, and the subjective factors are too strong, resulting in unreliable evaluation results.

According to the variable weight method of gray theory, in the process of multi-layer fuzzy reasoning, the information on the deterioration of some parameters of wind turbines is lost, and the evaluation results are not accurate enough

[0004] The traditional fuzzy evaluation method of wind turbine performance often has the problem that the weight is determined by experts or the parameter information of the weight determination process is not fully utilized. There is a deviation in the evaluation of the operation status of the wind turbine, which may lead to the inability to discover the potential safety hazards of the wind turbine in time, or even serious safety accident

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