Applications of Machine Learning: Energy Systems

This chapter focuses on machine learning applications in electrical energy systems. The first application is load forecasting, followed by fault/anomaly analysis, including fault detection, classification, and partial discharge detection. Then, the future trend of solar photovoltaic installed capacity and wind power output is predicted using machine learning. Finally, this chapter discusses a machine learning-based approach to reactive power control and power factor correction. By the end of this chapter, the readers will know about the multifaceted applications of machine learning in energy systems; especially electrical engineering students, researchers, and professionals will find it very useful in their practical lives.