Genetic Algorithm Based Whole Life Cycle Cost Prediction Model for Wind Farms

Under the trend of increasingly mature wind power generation technology in China, the power generation capacity of wind turbines is getting larger and larger. In this paper, we will study the cost composition of wind power from the perspective of the whole life cycle to help promote cost reduction and efficiency; at the same time, by calculating the LCOE to evaluate the economics of wind farms, and by taking into account the impact of the wake flow between wind turbines, the power generation capacity of wind farms, and the cost of the whole life cycle of the wind power project, we propose a genetic algorithm based on the optimal design of the unit scheduling scheme of wind farms.