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Energies 2016, 9(1), 5; doi:10.3390/en9010005

Energy Management Strategy for Microgrids by Using Enhanced Bee Colony Optimization

1
Department of Electrical Engineering, National Sun Yat-Sen University, Kaohsiung 807, Taiwan
2
Department of Electrical Engineering, Cheng-Shiu University, Kaohsiung 833, Taiwan
*
Author to whom correspondence should be addressed.
Academic Editor: Neville Watson
Received: 7 October 2015 / Revised: 13 December 2015 / Accepted: 17 December 2015 / Published: 23 December 2015
View Full-Text   |   Download PDF [3066 KB, uploaded 23 December 2015]   |  

Abstract

This paper presents a microgrid (MG) energy management strategy by considering renewable energy and battery storage systems. Renewable energy, including wind power generation and solar power generation, is integrated into the distribution network, for which is formulated the optimal dispatch model of mixed-power generation by considering the charging/discharging scheduling of battery storage systems. The MG system has an electrical link for power exchange between the MG and the utility during different hours of the day. Based on the time-of-use (TOU) and all technical constraints, an enhanced bee colony optimization (EBCO) is proposed to solve the daily economic dispatch of MG systems. In the EBCO procedure, the self-adaption repulsion factor is embedded in the bee swarm of the BCO in order to improve the behavior patterns of each bee swarm and increase its search efficiency and accuracy in high dimensions. Different modifications in moving patterns of EBCO are proposed to search the feasible space more effectively. EBCO is used for economic energy management of grid-connected and stand-alone scenarios, and the results are compared to those in previous algorithms. In either grid-connected or stand-alone scenarios, an optimal MG scheduling dispatch is achieved using micro-turbines, renewable energy and battery storage systems. Results show that the proposed method is feasible, robust and more effective than many previously-developed algorithms. View Full-Text
Keywords: microgrid; time-of-use; bee colony optimization; renewable energy microgrid; time-of-use; bee colony optimization; renewable energy
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

Lin, W.-M.; Tu, C.-S.; Tsai, M.-T. Energy Management Strategy for Microgrids by Using Enhanced Bee Colony Optimization. Energies 2016, 9, 5.

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