A Multi-Agent-Based Optimization Model for Microgrid Operation Using Dynamic Guiding Chaotic Search Particle Swarm Optimization

Jicheng Liu, Fangqiu Xu, Shuaishuai Lin, Hua Cai and Suli Yan
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Jicheng Liu: School of Economics and Management, North China Electric Power University, Beijing 102206, China
Fangqiu Xu: School of Economics and Management, North China Electric Power University, Beijing 102206, China
Shuaishuai Lin: School of Economics and Management, North China Electric Power University, Beijing 102206, China
Hua Cai: Industrial Engineering, Purdue University, West Lafayette, IN 47907, USA
Suli Yan: School of Economics and Management, North China Electric Power University, Beijing 102206, China

Energies, 2018, vol. 11, issue 12, 1-22

Abstract: The optimal operation of microgrids is a comprehensive and complex energy utilization and management problem. In order to guarantee the efficient and economic operation of microgrids, a three-layer multi-agent system including distributed management system agent, microgrid central control agent and microgrid control element agent is proposed considering energy storage units and demand response. Then, based on this multi-agent system and with the objective of cost minimization, an operation optimization model for microgrids is constructed from three aspects: operation cost, environmental impact and security. To solve this model, dynamic guiding chaotic search particle swarm optimization is adopted and three scenarios including basic scenario, energy storage participation and demand response participation are simulated and analyzed. The results show that both energy storage unit and demand response can effectively reduce the cost of microgrid, improve the operation and management level and ensure the safety and stability of power supply and utilization.

Keywords: multi-agent system; demand response; microgrid optimization; particle swarm optimization; energy storage (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: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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