Operational cost minimization of a microgrid with optimum battery energy storage system and plug-in-hybrid electric vehicle charging impact using slime mould algorithm
Amit Chakraborty and
Saheli Ray
Energy, 2023, vol. 278, issue PA
Abstract:
Microgrid (MG) with battery energy storage system (BESS) is the best for distribution system automation and hosting renewable energies. The proliferation of plug-in hybrid electric vehicles (PHEV) in distribution networks without energy management (EM) puts additional pressure on the utility and creates challenges for MG. This research article proposes a stochastic expert method to minimize the total operational cost through proper EM of a grid-connected low-voltage MG by considering the charging impact of PHEVs with the optimal size of BESS. Three strategies are used to control the PHEV charging demand. Economically improved performance of MG is obtained as compared to previous research without considering the daily cost of the BESS (fBESS) and operation and maintenance cost of different distributed generation sources (OMcost). Then, the study is extended by incorporating these two parameters into the objective function of operational cost. Finally, this article analyzes to what extent the fBESS and OMcost factors raise the microgrid's operational cost. Due to non-linear optimization issues, the slime mould algorithm (SMA) is proposed, which performed better EM with a lower operational cost of MG than other methods.
Keywords: Microgrid; Plug-in-hybrid electric vehicles; Energy management; Distribution generation; Cost optimization (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544223012367
Full text for ScienceDirect subscribers only
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:eee:energy:v:278:y:2023:i:pa:s0360544223012367
DOI: 10.1016/j.energy.2023.127842
Access Statistics for this article
Energy is currently edited by Henrik Lund and Mark J. Kaiser
More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().