INTRODUCTION TO AI TECHNIQUES FOR RENEWABLE ENERGY SYSTEM (HB 2021) Hardcover

Artificial Intelligence (AI) methods are becoming vital for understanding, analyzing, and predicting how renewable energy systems perform and how they can be controlled. Traditional methods for modeling, controlling, and predicting the behavior of these energy systems often involve complex equations, significant computing power, and lengthy processing times. Instead of relying on intricate rules and mathematical formulas, AI can learn crucial patterns from large amounts of data. Designing, controlling, and operating renewable energy systems often requires extensive historical weather data like solar radiation, temperature, or wind speed. However, this long-term data is frequently unavailable for many locations of interest, or if it exists, it might be of poor quality or not cover a sufficiently long period. This book highlights how AI techniques can help overcome these data limitations. It provides an overview of commonly used AI methods in renewable energy, with a specific focus on neural networks, fuzzy logic, and genetic algorithms. It also presents selected examples of AI applications in this field. In particular, it discusses how AI can be used to predict and model solar radiation, and to analyze, predict the performance of, and control solar photovoltaic (PV) systems.