Energy Management: Big Data in Power Load Forecasting

This book introduces the principle of carrying out a medium-term load forecast (MTLF) at power system level,based on the Big Data concept and Convolutional Neural Network (CNNs). It also presents further research directions in the field of Deep Learning techniques and Big Data,as well as how these two concepts are used in power engineering.

Format: Hardback
Length: 82 pages
Publication date: 28 June 2021
Publisher: Taylor & Francis Ltd

This comprehensive book delves into the realm of medium-term load forecasting (MTLF) in power systems, leveraging the power of Big Data and Convolutional Neural Networks (CNNs). It not only provides an in-depth introduction to this critical aspect of power engineering but also explores innovative research directions in the fields of Deep Learning techniques and Big Data. Furthermore, it sheds light on how these two cutting-edge concepts are applied in the realm of power engineering, offering valuable insights and practical applications.

By efficiently processing and analyzing vast amounts of data, the book enables power engineers to generate highly accurate load forecasts. This, in turn, leads to a significant improvement in the consumption pattern of clients, fostering better consumer awareness and enabling the development of new energy services and business lines.

The book is a valuable resource for electrical engineers, power engineers, and professionals in the energy services sector, providing them with a comprehensive understanding of MTLF and the potential it holds for shaping the future of power systems. With its comprehensive coverage, practical examples, and expert insights, this book is essential for anyone seeking to stay at the forefront of this rapidly evolving field.

Weight: 238g
Dimension: 141 x 224 x 12 (mm)
ISBN-13: 9780367706166