Despite the Korean government’s keen interest in wind power generation, wind farm construction continues to be ad hoc in terms of both selection of location and utilization wind resources in the country. In this study, an artificial neural network (...
Despite the Korean government’s keen interest in wind power generation, wind farm construction continues to be ad hoc in terms of both selection of location and utilization wind resources in the country. In this study, an artificial neural network (ANN) model was developed to predict the economics of wind power generation using wind vector characteristics, grid linkage, and geographical characteristics. A regional wind power resource distribution map was constructed considering economic feasibility. An optimization method was established to optimize the size of the wind power complex, grid connection, and type of wind turbine to secure maximum economic benefits for promising wind power locations. The optimization method used could quantify various key factors and support economic analysis through a sensitivity analysis between the various impact factors of wind power projects. The optimization method led to identifying locations for onshore and offshore wind farms with high economic potential in the Southwest Sea and near Jeju Island.