Online Monitoring of Wind Turbine Operation Efficiency and Optimization Based on Benchmark Values

Improving the operational efficiency of wind turbines is an important way to enhance the competitiveness of wind power generation among new energy sources. This paper presents a new method for online monitoring and optimization of the operational efficiency of wind turbines. The randomness of the wind speed is analyzed in the form of wind speed variation using historical data, revealing the distribution pattern of wind speed randomness. The fluctuation amplitude of the output power of wind turbines is analyzed in the form of power variation under different wind speed modes. The level of active power is classified by quantiles based on historical data. The sliding window method is adopted to eliminate the jumping fluctuation of the efficiency level caused by the randomness of the wind speed. To identify and explain the reasons for the deviation of the operating efficiency, the benchmark values of operational parameters are obtained from historical operation data by data mining. The low operating efficiency level is adjusted according to the benchmark values of operating parameters. The model has been verified to effectively monitor the operating efficiency of wind turbines and provide operational optimization measures to improve efficiency.