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Energy Sustainability through Retail Electricity Markets


Menge:  Stück  
Produktinformationen
cover
cover
Artikel-Nr.:
     5667A-9783031397066
Hersteller:
     Springer Verlag
Herst.-Nr.:
     9783031397066
EAN/GTIN:
     9783031397066
Suchbegriffe:
Bücher zu Sozialwissenschaften allg...
Bücher über Sozialwissenschaften al...
Bücher über Wirtschaft
Wirtschaftsbücher
The world is moving away from demand-driven electricity markets supplied by centralized generation and distribution of fossil-fuel-produced electricity. Increasing reliance on weather-dependent renewable sources will require a shift toward a supply-driven paradigm, while beneficial electrification, including widespread adoption of electric vehicles, heat pumps, and batteries will offer considerable but widely distributed demand flexibility that can be used to compensate for supply variability. The open-source Power Trading Agent Competition (Power TAC) platform simulates a decentralized future, modeling the high complexity of future retail electricity markets.  This book describes a variety of approaches to profitable trading in realistic wholesale and retail electricity markets. It presents actionable insights from extensive exploration of policies and business models for retail electricity markets gained from a decade of Power TAC tournaments, and from research inspired by the Power TAC experience. Featuring contributions from tournament designers, competitors, and scientists combining best practices from computer science and economics and management science, this book is of benefit to academics, researchers, practitioners and policy makers in sustainable energy and wholesale and retail electricity markets.
Weitere Informationen:
Author:
John Collins; Wolfgang Ketter; Andreas L. Symeonidis
Verlag:
Springer International Publishing
Sprache:
eng
Weitere Suchbegriffe: Wirtschaftsbücher - englischsprachig, allgemeine Sozialwissenschaftsbücher - englischsprachig, bücher zu sozialwissenschaften allgemein, Sustainable Energy; Statistical modeling; Machine Learning; Intelligent agents; Energy System Modeling; Virtual power plants; Competitive simulation, Power Trading Agent Competition (Power TAC), retail electricity markets, Sustainable energy, statistical modeling, Machine Learning, Intelligent agents, Energy System modeling, Virtual power plants, Competitive simulation
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