Smart Grid Economics and Management

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· Lecture Notes in Energy Buku 51 · Springer Nature
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This book focuses on market/regulatory issues concerning smart grid applications, business cases and use cases. It covers the most relevant aspects of the smart grid—design considerations, economics, legal aspects and system management—and includes exercises at the end of each chapter. Since renewable energy generation is weather-dependent, it is more volatile, which affects market prices and the need for flexibility options including demand side management. In order to balance supply and demand in a sustainable manner also with high shares of renewables, energy systems need to be enhanced by smart grid technologies. This co-evolutionary transformation of the energy system, economic, societal, political and regulatory domains is challenging and calls for an integrated and interdisciplinary approach. This book provides an essential basis to prepare lecturers and students for engaging in the new energy world.

Perihal pengarang

Clemens van Dinther is Professor for Information Systems/Business Analytics at ESB Business School at Reutlingen University and Privatdozent at the Karlsruhe Institute of Technology (KIT). After his studies of business engineering and management at the former Universität Karlsruhe (TH) he worked as researcher at KIT and the FZI Forschungszentrum Informatik Karlsruhe (a research center for computer science) with research interests in smart grids, information systems, market engineering and agent-based computational economics. He received his Dr.-degree from Universität Karlsruhe (TH) in 2006 and his venia legendi in Business Administration from KIT in 2010. Clemens is member of the working group “Internet of Energy” of the German federal industry association (BDI Bundesverband der deutschen Industrie). He held positions in energy companies and is currently CEO of VIVAVIS, a German enterprise that delivers software and hardware solutions for power grid and metering systems

Christoph M. Flath is a chaired Professor of Information Systems and Business Analytics at the University of Würzburg. He holds a diploma degree in Industrial Engineering and Management and a doctoral degree in Information Systems from Karlsruhe Institute of Technology, Germany. His research interests include management and analysis of cyber-physical systems in energy, industry and transportation with a focus on business analytics and optimization. His research has been published in various international academic journals and proceedings including Production and Operations Management, Journal of Operations Management, Journal of Information Technology, Transportation Science, European Journal of Operational Research and Energy Policy.

Reinhard Madlener is a Full Professor for Energy Economics and Management at RWTH Aachen University and an Adjunct Professor with the Department of Industrial Economics and Technology Management, Norwegian University of Science and Technology (NTNU). Since 2007, he is one of the Directors of the E.ON Energy Research Center at RWTH Aachen University, and as such Head of the Institute for Future Energy Consumer Needs and Behavior (FCN). Before taking up the position at RWTH Aachen, he was a Senior Researcher with DIW Berlin (2007), Assistant Professor at the Centre for Energy Policy and Economics (CEPE) at ETH Zurich (2001-2007), and the Managing Director of the Institute for Advanced Studies Carinthia (1999-2000). He is a Senior Editor of the Energy Policy journal and a member of numerous editorial and scientific advisory boards. His teaching activities include Energy Economics, Smart Grid Economics and Information Management, Environmental Economics, Economics of Technical Change, Economics of Technological Diffusion, and Behavioral and Experimental Economics, among others. The main research interests are in energy economics, management and (public) policy; investment & financing under uncertainty; behavioral & experimental energy research; the adoption & diffusion of technological innovation; and risk management & portfolio optimization.


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