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Energies 2015, 8(12), 14272-14286; doi:10.3390/en81212430

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

1
Department of Electrical Engineering, Inha University, 100, Inha-ro, Nam-gu, Incheon 402-751, Korea
2
School of Electrical Engineering, Kookmin University, Jeongneung-ro, Seongbuk-gu, Seoul 136-702, Korea
3
Department of Electrical Engineering, Myongji University, 116, Myongji-ro, Cheoin-gu, Yongin-si, Gyeonggi-do 449-728, Korea
*
Author to whom correspondence should be addressed.
Academic Editor: Neville R. Watson
Received: 14 September 2015 / Revised: 10 December 2015 / Accepted: 14 December 2015 / Published: 18 December 2015
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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. View Full-Text
Keywords: microgrid; demand response; multi-agent system; battery energy storage system; intelligent load; fuzzy system; hardware-in-the-loop simulation microgrid; demand response; multi-agent system; battery energy storage system; intelligent load; fuzzy system; hardware-in-the-loop simulation
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Cha, H.-J.; Won, D.-J.; Kim, S.-H.; Chung, I.-Y.; Han, B.-M. Multi-Agent System-Based Microgrid Operation Strategy for Demand Response. Energies 2015, 8, 14272-14286.

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