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Energies 2013, 6(10), 4956-4979; doi:10.3390/en6104956

Intelligent Control of Battery Energy Storage for Multi-Agent Based Microgrid Energy Management

1
School of Electrical Engineering, Kookmin University, 861-1, Jeongneung-dong, Seongbuk-gu, Seoul 136-702, Korea
2
Korea Electric Power Research Institute, 105 Munji-Ro, Yuseong-Gu, Daejeon 305-760, Korea
*
Author to whom correspondence should be addressed.
Received: 12 August 2013 / Revised: 16 September 2013 / Accepted: 16 September 2013 / Published: 25 September 2013
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Abstract

Microgrids can be considered as controllable units from the utility point of view because the entities of microgrids such as distributed energy resources and controllable loads can effectively control the amount of power consumption or generation. Therefore, microgrids can make various contracts with utility companies such as demand response program or ancillary services. Another advantage of microgrids is to integrate renewable energy resources to low-voltage distribution networks. Battery energy storage systems (BESSs) can effectively compensate the intermittent output of renewable energy resources. This paper presents intelligent control schemes for BESSs and autonomous energy management schemes of microgrids based on the concept of multi-agent systems. The proposed control scheme consists of two layers of decision-making procedures. In the bottom layer, intelligent agents decide the optimal operation strategies of individual microgrid entities such as BESSs, backup generators and loads. In the upper layer, the central microgrid coordinator (MGCC) coordinates multiple agents so that the overall microgrid can match the load reduction requested by the grid operator. The proposed control scheme is applied to Korea Power Exchange’s Intelligent Demand Response Program. View Full-Text
Keywords: battery energy storage; microgrid; multi-agent system; energy management system; emergency demand response; state machine battery energy storage; microgrid; multi-agent system; energy management system; emergency demand response; state machine
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Yoo, C.-H.; Chung, I.-Y.; Lee, H.-J.; Hong, S.-S. Intelligent Control of Battery Energy Storage for Multi-Agent Based Microgrid Energy Management. Energies 2013, 6, 4956-4979.

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