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A Game Theory Approach to Multi-Agent Decentralized Energy Management of Autonomous Polygeneration Microgrids

Christos-Spyridon Karavas (), Konstantinos Arvanitis () and George Papadakis ()
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Christos-Spyridon Karavas: Department of Natural Resources Management and Agricultural Engineering, School of Agricultural Production, Infrastructure and Environment, Agricultural University of Athens, 75 Iera Odos Street, Botanikos, 11855 Athens, Greece
Konstantinos Arvanitis: Department of Natural Resources Management and Agricultural Engineering, School of Agricultural Production, Infrastructure and Environment, Agricultural University of Athens, 75 Iera Odos Street, Botanikos, 11855 Athens, Greece
George Papadakis: Department of Natural Resources Management and Agricultural Engineering, School of Agricultural Production, Infrastructure and Environment, Agricultural University of Athens, 75 Iera Odos Street, Botanikos, 11855 Athens, Greece

Energies, 2017, vol. 10, issue 11, 1-22

Abstract: Energy management systems are essential and indispensable for the secure and optimal operation of autonomous polygeneration microgrids which include distributed energy technologies and multiple electrical loads. In this paper, a multi-agent decentralized energy management system was designed. In particular, the devices of the microgrid under study were controlled as interactive agents. The energy management problem was formulated here through the application of game theory, in order to model the set of strategies between two players/agents, as a non-cooperative power control game or a cooperative one, according to the level of the energy produced by the renewable energy sources and the energy stored in the battery bank, for the purpose of accomplishing optimal energy management and control of the microgrid operation. The Nash equilibrium was used to compromise the possible diverging goals of the agents by maximizing their preferences. The proposed energy management system was then compared with a multi-agent decentralized energy management system where all the agents were assumed to be cooperative and employed agent coordination through Fuzzy Cognitive Maps. The results obtained from this comparison, demonstrate that the application of game theory based control, in autonomous polygeneration microgrids, can ensure operational and financial benefits over known energy management approaches incorporating distributed intelligence.

Keywords: microgrids; multiple agents; decentralized energy management system; game theory (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
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