Fr. 198.00

Economically Enabled Energy Management - Interplay Between Control Engineering and Economics

English · Hardback

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Description

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This book gathers contributions from a multidisciplinary research team comprised of control engineering and economics researchers and formed to address a central interdisciplinary social issue, namely economically enabled energy management. The book's primary focus is on achieving optimal energy management that is viable from both an engineering and economic standpoint. In addition to the theoretical results and techniques presented, several chapters highlight experimental case studies, which will benefit academic researchers and practitioners alike.   
The first three chapters present comprehensive overviews of respective social contexts, underscore the pressing need for economically efficient energy management systems and academic work on this emerging research topic, and identify fundamental differences between approaches in control engineering and economics. In turn, the next three chapters (Chapters 4-6) provide economics-oriented approaches to the subject. The following five chapters (Chapters 7-11) address optimal energy market design, integrating both physical and economic models. The book's last three chapters (Chapters 12-14) mainly focus on the engineering aspects of next-generation energy management, though economic factors are also shown to play important roles.

List of contents

Economically-enabled Energy Management: Overview and Research Opportunities.- Supply and Demand Balance Control Based on Balancing Power Market.- Resolving Discrepancies in Problem Formulations for Electricity Pricing by Control Engineers and Economists.- E ectiveness of Feed-In Tari and Renewable Portfolio Standard under Strategic Pricing in Network Access.- The Welfare E ects of Environmental Taxation and Subsidization on Renewable Energy Sources in an Oligopolistic Electricity Market.- Behavioral Study of Demand Response: Web-Based Survey, Field Experiment, and Laboratory Experiment.- Economic Impact and Market Power of Strategic Aggregators in Energy Demand Networks.- Incentive-Based Economic and Physical Integration for Dynamic Power Networks.- Distributed Dynamic Pricing in Electricity Market with Information Privacy.- Real-Time Pricing for Electric Power Systems by Nonlinear Model Predictive Control.- Distributed Multi-Agent Optimization Protocol over Energy Management Networks.- A Passivity-Based Design of Cyber-Physical Building HVAC Energy Management Integrating Optimization and Physical Dynamics.

About the author










Takeshi Hatanaka received his B.Eng. degree in informatics and mathematical science, and his M.Inf. and Ph.D. degrees in applied mathematics and physics, from Kyoto University, Japan, in 2002, 2004 and 2007, respectively. He joined Tokyo Institute of Technology in 2007, where he held positions as an assistant and associate professor. In 2016, he spent an eight-month sabbatical at the School of Engineering and Applied Sciences, Harvard University. Since April 2018, he has been an Associate Professor at Osaka University. His research interests include energy management systems and networked robotics. He received the Outstanding Paper Award (2009, 2015), Pioneer Award (2014), Outstanding Book Award (2016), Kimura Award (2017), and Control Division Conference Award (2018), all from the SICE. He is an associate editor for the journals IEEE TSCT and SICE JCMSI, and a member of the Conference Editorial Board of IEEE CSS. He is the coauthor of Passivity-Based Control and Estimation in Networked Robotics (Springer, 2015).   

Yasuaki Wasa is currently an assistant professor of Electrical Engineering and Bioscience, Waseda University, Japan, since April 2019. He received his B.Eng. degree in control and systems engineering, and his M.Eng. and Ph.D. degrees in mechanical and control engineering, from Tokyo Institute of Technology, Japan in 2011, 2013 and 2016, respectively. He was a research fellow of the Japan Society for the Promotion of Science from 2014 to 2017, and a junior researcher at Waseda University from 2017 to 2019. His research interests include dynamic incentive design in energy management systems, and game theoretic distributed learning and optimization for cyber-physical & human systems. He received the Hatakeyama Award (2012) and Miura Award (2014) from the JSME, the Outstanding Paper Award (2015) and the Young Author Award (2019) from the SICE. He was also a recipient of Asian Control Conference 2019 Best Paper Award Finalist. 

Kenko Uchida graduated from Waseda University, Tokyo, Japan, in 1971, and obtained his M.S. and Dr.Eng. degrees from Waseda University in 1973 and 1976, respectively. He is currently a Senior Research Professor of Research Institute for Science and Engineering at Waseda University. He was an Alexander von Humboldt research fellow at the Technical University of Munich from 1982 to 1983. His main research interests are in the information structure of optimal control and dynamic games, and control problems in energy management systems and biomedical systems. He has served as an associate editor for the journals Automatica and Asian Journal of Control. He received the Outstanding Paper Award in 2010 from the SICE. He is a fellow member of the SICE, and was a vice president of the Asian Control Association from 2012 to 2013 and an associate member of the Science Council of Japan from 2008 to 2017.


Product details

Assisted by Takeshi Hatanaka (Editor), Kenko Uchida (Editor), Yasuak Wasa (Editor), Yasuaki Wasa (Editor)
Publisher Springer, Berlin
 
Languages English
Product format Hardback
Released 01.07.2020
 
EAN 9789811535758
ISBN 978-981-1535-75-8
No. of pages 341
Dimensions 157 mm x 24 mm x 239 mm
Weight 678 g
Illustrations X, 341 p. 140 illus., 114 illus. in color.
Subjects Natural sciences, medicine, IT, technology > Technology > Heat, energy and power station engineering

Volkswirtschaftslehre, BUSINESS & ECONOMICS / Economics / General, TECHNOLOGY & ENGINEERING / Automation, BUSINESS & ECONOMICS / Industries / Energy, Business / Economics / Finance

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