ABSTRACT
Integrated advancements in sustainable energy are inspiring more usage of eco-friendly, reliable, non-harmful renewable energy generation resources. Due to the increase in power supply and demand, renewable energy sources are used as an energy boost. The rate of pollution by renewable energy is much lesser than other energy sources. The solar energy system depends on solar irradiance and the wind energy system also depends on the speed of the wind. Using artificial intelligence (AI)-based algorithms it is easy to predict and detect the timing of solar radiation, wind farms energy generation, etc. Power supply and demand, energy sources, and decision-making situations are autonomously controlled by AI and machine learning (ML) algorithms. In recent days developments in AI and ML models are helpful for controllability, optimization of energy efficiency, control of predictive maintenance, operational performance, monitoring, feature selection, extraction, production, infrastructure, etc. The most common algorithm for the development of energy management is AI (artificial neural network), swarm intelligence, (FLC) fuzzy logic systems, genetic algorithms, expert systems, etc. In this chapter, we will discuss those algorithms which are related to solar and wind energy systems. In energy management systems, predicting power generation and monitoring the condition of wind/solar/etc energy systems is helpful for controlling the supply chain. An analysis of recent advances in the various applications of AI and ML with renewable energy, wind power systems, solar farms, etc., will be helpful to others.
