1st Edition
Solar Power Forecasting Using Time Series and Machine Learning
By Natarajan Gautam
Copyright 2026
206 Pages
103 B/W Illustrations
by
CRC Press
206 Pages
103 B/W Illustrations
by
CRC Press
This book takes an approach that leverages methods using time series analysis, machine learning, and stochastic models to effectively forecast solar power. The goal of this book is not only to produce an accurate forecast but also to make it conducive to being used for decision-making.
Solar Power Forecasting: Using Time Series and Machine Learning combines traditional forecasting with recent... Read more
1. Introduction. 2. Forecasting. 3. Short-Term Solar Forecasts. 4. Day-Ahead Solar Forecasts. 5. Day-Ahead Planning. 6. Distributional Forecasts.
Biography
N. Gautam has been a Professor in the Department of Electrical Engineering and Computer Science at Syracuse University, NY, USA, since January 2022. Before that, he was a faculty member at Texas A&M for over 16 years and at Penn State for 8 years. In addition, Dr. Gautam has been an Amazon Scholar since Fall 2019. His research focuses on optimization and control of stochastic systems with applications in computer-communication networks, renewable energy systems, real-time logistics, and smart manufacturing. Dr. Gautam is a Fellow of the Institute for Industrial and Systems Engineers (IISE).
