Multi-agent System Based Energy Management of Microgrid on Day-ahead Market Transaction

This article focuses on the multi-agent system-based energy management issue of an autonomous microgrid (MG) and proposes a novel approach that a distributed generation unit as a rational agent participates in energy scheduling and profit allocation under a day-ahead market environment. First, a bi-...

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Bibliographic Details
Published in:Electric power components and systems 2016-07, Vol.44 (12), p.1330-1344
Main Authors: Dou, Chun-Xia, Jia, Xing-Bei, Li, Heng, Lv, Meng-Fei
Format: Article
Language:English
Subjects:
Allocations
bi-level multi-agent system
cooperative game
day-ahead market transaction
Distributed generation
Economic models
Electric utilities
Electricity distribution
Energy management
equilibrium problem with equilibrium constraints
Game theory
Markets
Mathematical models
microgrid
Multiagent systems
Nash equilibrium
non-cooperative game
Optimization
optimization problem
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Summary:This article focuses on the multi-agent system-based energy management issue of an autonomous microgrid (MG) and proposes a novel approach that a distributed generation unit as a rational agent participates in energy scheduling and profit allocation under a day-ahead market environment. First, a bi-level multi-agent system is structured, and a bi-level day-ahead bidding model is formulated for the bidding optimization of distributed generation. Subsequently, the bi-level bidding model is transformed into a mixed-integer linear program from a mathematical program with equilibrium constraints with binary expansion of quantity price bids. Then formulation of an equilibrium problem with equilibrium constraints is processed for all distributed generation units to obtain the Nash equilibrium solution based on game theory. An auxiliary optimization problem is also formulated to find the unique Nash equilibrium for the bidding game in consideration of maximizing the transaction price. Both non-cooperative and cooperative bidding games are finally addressed by the means of the proposed energy management approach in the designed bi-level multi-agent system market.
ISSN:1532-5008
1532-5016
DOI:10.1080/15325008.2016.1158216