Energy Management Strategy for Microgrids by Using Enhanced Bee Colony Optimization
Whei-Min Lin,
Chia-Sheng Tu and
Ming-Tang Tsai
Additional contact information
Whei-Min Lin: Department of Electrical Engineering, National Sun Yat-Sen University, Kaohsiung 807, Taiwan
Chia-Sheng Tu: Department of Electrical Engineering, National Sun Yat-Sen University, Kaohsiung 807, Taiwan
Ming-Tang Tsai: Department of Electrical Engineering, Cheng-Shiu University, Kaohsiung 833, Taiwan
Energies, 2015, vol. 9, issue 1, 1-16
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.
Keywords: microgrid; time-of-use; bee colony optimization; renewable energy (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 (8)
Downloads: (external link)
https://www.mdpi.com/1996-1073/9/1/5/pdf (application/pdf)
https://www.mdpi.com/1996-1073/9/1/5/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:9:y:2015:i:1:p:5-:d:61109
Access Statistics for this article
Energies is currently edited by Ms. Agatha Cao
More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().