£83.99

Academic Press Local Electricity Markets

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Description

Product Description Local Electricity Markets introduces the fundamental characteristics, needs, and constraints shaping the design and implementation of local electricity markets. It addresses current proposed local market models and lessons from their limited practical implementation. The work discusses relevant decision and informatics tools considered important in the implementation of local electricity markets. It also includes a review on management and trading platforms, including commercially available tools. Aspects of local electricity market infrastructure are identified and discussed, including physical and software infrastructure. It discusses the current regulatory frameworks available for local electricity market development internationally. The work concludes with a discussion of barriers and opportunities for local electricity markets in the future. Review Explores challenges and opportunities surrounding the practical design and implementation of local electricity markets, including proposed models and practical barriers About the Author Tiago Pinto (Lecturer, BISITE research group, University of Salamanca, Spain) works in the application of AI techniques to the study of electricity markets, specifically in the decision support of negotiating agents. He has been involved in several research projects involving the development and use of: Multi-Agent systems, Machine Learning algorithms, Knowledge-Based systems, Game Theory, Neural Networks, Genetic Algorithms, Particle Swarm Intelligence, and Data Mining. He is particularly interested in electricity markets, addressing the decision-support for market participants, negotiation strategies, machine learning and agent-based market simulation. He is also interested in smart grids, accommodating an intensive use of Renewable Energy Sources, Distributed Energy Resources (DER) and Distributed Generation (DG), addressing the management of energy resources and the negotiation of DER in electricity markets. He has authored over 150 publications in international journals and conferences. He has co-edited several books and special issues in journals related to power and energy systems and artificial intelligence. Zita Vale (GECAD research group, Polytechnic of Porto, Portugal) is Professor at the School of Engineering (ISEP) of the Polytechnic of Porto (IPP) and Director of GECAD – Research Group on Intelligent Engineering and Computing for Advanced Innovation and Developments. Her main interests regard the application of Artificial Intelligence Techniques to Power systems, including Knowledge based systems, Multi-agent systems, Neural Networks, Meta-heuristics, Optimization, Machine Learning, and Knowledge Discovery Techniques. She has been involved in more than 40 R&D projects from which she coordinated more than 20 projects. She is principally interested in Smart Grids, with an intensive use of Renewable Energy Sources, Distributed Energy Resources and Distributed Generation, addressing the management of energy resources, the negotiation of DER in electricity markets, demand response, and electric vehicles. She is also interested in electricity markets, addressing prices and tariffs, decision-support for market participants, ancillary services, derivatives market, pricing and market simulation. Steve Widergren (Principal Engineer, Pacific Northwest National Laboratory, USA) is interested in the application of information technology to power engineering problems including simulation, control, and system integration. He was the founding Administrator for the GridWise Architecture Council – a group formed to enable interoperability of automated systems related to the electric system. Prior to joining the Laboratory, Mr. Widergren was a corporate engineer at ESCA, now GE, an electricity control center supplier. Prior to that, he worked at American Electric Power and interned at Pacific Gas and Electric. In these positions, he engineered and m

Product Specifications

Format
Paperback
Domain
Amazon UK
Release Date
12 July 2021
Listed Since
01 October 2019

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