Multi-Agent System-Based Microgrid Operation Strategy for Demand Response

Hee-Jun Cha, Dong-Jun Won, Sang-Hyuk Kim, Il-Yop Chung and Byung-Moon Han
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Hee-Jun Cha: Department of Electrical Engineering, Inha University, 100, Inha-ro, Nam-gu, Incheon 402-751, Korea
Dong-Jun Won: Department of Electrical Engineering, Inha University, 100, Inha-ro, Nam-gu, Incheon 402-751, Korea
Sang-Hyuk Kim: School of Electrical Engineering, Kookmin University, Jeongneung-ro, Seongbuk-gu, Seoul 136-702, Korea
Il-Yop Chung: School of Electrical Engineering, Kookmin University, Jeongneung-ro, Seongbuk-gu, Seoul 136-702, Korea
Byung-Moon Han: Department of Electrical Engineering, Myongji University, 116, Myongji-ro, Cheoin-gu, Yongin-si, Gyeonggi-do 449-728, Korea

Energies, 2015, vol. 8, issue 12, 1-15

Abstract: The microgrid and demand response (DR) are important technologies for future power grids. Among the variety of microgrid operations, the multi-agent system (MAS) has attracted considerable attention. In a microgrid with MAS, the agents installed on the microgrid components operate optimally by communicating with each other. This paper proposes an operation algorithm for the individual agents of a test microgrid that consists of a battery energy storage system (BESS) and an intelligent load. A microgrid central controller to manage the microgrid can exchange information with each agent. The BESS agent performs scheduling for maximum benefit in response to the electricity price and BESS state of charge (SOC) through a fuzzy system. The intelligent load agent assumes that the industrial load performs scheduling for maximum benefit by calculating the hourly production cost. The agent operation algorithm includes a scheduling algorithm using day-ahead pricing in the DR program and a real-time operation algorithm for emergency situations using emergency demand response (EDR). The proposed algorithm and operation strategy were implemented both by a hardware-in-the-loop simulation test using OPAL-RT and an actual hardware test by connecting a new distribution simulator.

Keywords: microgrid; demand response; multi-agent system; battery energy storage system; intelligent load; fuzzy system; hardware-in-the-loop simulation (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: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (16)

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