Prediction Techniques for Renewable Energy Generation and Load Demand Forecasting

The book "Prediction Techniques for Renewable Energy Generation and Load Demand Forecasting" offers a comprehensive introduction to forecasting methods for renewable energy sources integrated into existing power grids. It is divided into two main sections: the first section focuses on forecasting methods for energy generation, while the second section addresses various approaches to load forecasting. The work includes modern techniques such as artificial intelligence, machine learning, and hybrid methods that are relevant for predicting renewable energies and loads. Furthermore, the book reflects the current state of the art regarding distributed generation systems and future microgrids. It covers both theoretical concepts and practical applications, including algorithms, simulations, and case studies. This book is a valuable resource for students and researchers engaged in renewable energies and their integration into existing power distribution networks.