Energy Availability Analysis of Offshore Wind Farms Considering the Correlation between Wind Speed Cloud Model and Parameters

Abstract

With the development of smart wind turbines, more comprehensive data and information for reliability assessment of wind turbines are provided. The reliability assessment can be carried out by statistically analyzing the failure and outage time of wind farm units, using simulation mathematical methods. However, for large-scale offshore wind farms, there is often the problem of a lack of wind farm data. Moreover, compared to wind farms, offshore wind farms operating in complex environments, harsh operating conditions for wind turbines, uncertain parameters, and complex coupling relationships among various uncertain parameters, which improve the energy reliability of offshore wind farms. Accordingly, in this paper, the offshore wind farm reliability assessment method takes into account the complex coupling effects of uncertain factors and parameters. In general, it mainly considers wind speed, ocean waves, own failure rate, and maintenance resource allocation plan method among climatic factors are mainly considered in this paper. For the main influencing parameters, the method of the cloud model is used to change the numerical state of multiple parameters, and the method of artificial neural network (ANN) and multiple linear regression is used to analyze the correlation between multiple parameters to explore the power-generation capacity of offshore wind farms. The degree of influence of the parameters of various uncertain factors. The proposed method is exemplified via an illustrative example of an offshore wind farm system and the influence and relationship between the power-generation capacity of the offshore wind farm by multiple parameters can be revealed clearly.