Chapter 6. Artificial Intelligence in Wind Energy

Despite the increasing development of wind energy (WE) which has notably become the leading renewable energy now, there are still persistent barriers to wider implementation related to technology, cost, and environmental and social impacts, e.g., super large-scale (≥10 megawatt) wind turbine (WT) technology, WT deployment at low wind speed and/or residential-closed areas, and offshore wind farm under severe wind-wave conditions. As one of the emerging technologies, artificial intelligence (AI) could take some of these challenges and assist in achieving the goal of further lowering the levelized cost of energy from wind. Recently AI has been tremendously investigated in an extremely wide range from financial data analytics and industrial production design to novel biometric and forensic applications and various renewable energy development. This chapter provides the fundamental introduction of four categories of state-of-the-art AI methods including (i) neural learning methods, (ii) statistical learning methods, (iii) evolutionary learning methods, and (iv) hybrid learning methods in a lucid way, then carry out a comprehensive survey of various AI methods used in WE including (i) wind speed prediction, (ii) wind power estimation, (iii) WT design and optimization, and (iv) WT condition monitoring.