Application of machine learning for wind energy from design to energy-Water nexus: A Survey

Abstract

The world’s dependency on fossil fuels is decreasing swiftly, and countries rely more on renewable energies. Among renewable energies, wind energy has become one of the most significant ones. Increasing its production and reducing energy and water costs has attracted many attentions. Moreover, due to the uncertainty of wind speed, power generation of wind farms is facing high volatility, which is affecting the electricity markets. Thus, in light of the rapid growth of wind energy technologies, new approaches based on advanced analytic are required. This paper presents a comprehensive review of artificial intelligence employed in wind energy systems, surveying the studies most applied in various applications and resulting from artificial neural networks (ANN) could be a sustainable approach instead of conventional methods in many cases. A large number of research studies associated with this topic are published since 2015, and based on the application could be categorized in five main groups: wind speed prediction, design optimization, fault detection, optimal control and maintenance planning. A statistical analysis of ANN application in these fields is carried out for the present time and future trends.

Keywords

• Renewable energy
• Wind energy
• Artificial neural network
• Artificial intelligence