LAPSE

LAPSE:2018.0744
Published Article
LAPSE:2018.0744
Energy Management Strategy for Microgrids by Using Enhanced Bee Colony Optimization
Whei-Min Lin, Chia-Sheng Tu, Ming-Tang Tsai
October 22, 2018
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.
Keywords
bee colony optimization, microgrid, Renewable and Sustainable Energy, time-of-use
Suggested Citation
Lin WM, Tu CS, Tsai MT. Energy Management Strategy for Microgrids by Using Enhanced Bee Colony Optimization. (2018). LAPSE:2018.0744
Author Affiliations
Lin WM: Department of Electrical Engineering, National Sun Yat-Sen University, Kaohsiung 807, Taiwan
Tu CS: Department of Electrical Engineering, National Sun Yat-Sen University, Kaohsiung 807, Taiwan
Tsai MT: Department of Electrical Engineering, Cheng-Shiu University, Kaohsiung 833, Taiwan
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Journal Name
Energies
Volume
9
Issue
1
Article Number
E5
Year
2015
Publication Date
2015-12-23
Published Version
ISSN
1996-1073
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Original Submission
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PII: en9010005, Publication Type: Journal Article
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LAPSE:2018.0744
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doi:10.3390/en9010005
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Oct 22, 2018
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CC BY 4.0
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[v1] (Original Submission)
Oct 22, 2018
 
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Oct 22, 2018
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http://psecommunity.org/LAPSE:2018.0744
 
Original Submitter
Calvin Tsay
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