Smart Energy Management: Data Driven Methods for Energy Service Innovation

This book provides a comprehensive view of data-driven decision-making methods for energy service innovation and energy system optimization, focusing on personalized energy services, energy efficiency improvement, and blockchain-based electricity trading. It introduces various data mining and machine learning methods and their applications in improving energy efficiency and supporting energy service innovation. The intended readership includes researchers, engineers, graduate students, and general interested audiences.

Format: Paperback / softback
Length: 310 pages
Publication date: 06 February 2023
Publisher: Springer Verlag, Singapore

This comprehensive book offers a thorough exploration of data-driven decision-making techniques for energy service innovation and energy system optimization. By delivering personalized energy services and enhancing energy efficiency, it plays a pivotal role in driving the green transformation of the energy system and fostering sustainable societal development. The book presents a novel approach to achieving smart energy management through a diverse range of data mining and machine learning methods, including fuzzy clustering, shape-based clustering, ensemble clustering, deep learning, and reinforcement learning. These methods are applied to improve energy efficiency and support energy service innovation. Furthermore, the book delves into the role of blockchain in facilitating peer-to-peer (P2P) electricity trading innovation, thereby supporting smart energy management.

The book's broad scope encompasses load clustering, load forecasting, price-based demand response, incentive-based demand response, and energy blockchain-based electricity trading. Its intended readership includes researchers and engineers working in related fields, graduate and undergraduate students enrolled in universities, as well as a broader audience with an interest in smart energy management.

Key features of the book include:

Introduction to Various Data-Driven Methods: The book provides an in-depth introduction to a diverse array of data-driven methods, enabling the achievement of various smart energy management tasks.

Investigation of Data-Driven Methods in Supporting Energy Service Innovation: It explores the crucial role of data-driven techniques in fostering energy service innovation, contributing to the development of a more sustainable and efficient energy system.

Exploration of Energy Blockchain in P2P Electricity Trading: The book delves into the application of energy blockchain in P2P electricity trading, supporting smart energy management by enabling secure and transparent transactions.

Overall, this book serves as a valuable resource for researchers, engineers, students, and practitioners seeking to leverage data-driven approaches to optimize energy systems and drive the transition towards a greener and more sustainable future.

Weight: 504g
Dimension: 235 x 155 (mm)
ISBN-13: 9789811693625
Edition number: 1st ed. 2022