Performance evaluation of metaheuristic techniques for optimal sizing of a stand-alone hybrid PV/wind/battery system

Dalila Fares, Mohamed Fathi and Saad Mekhilef

Applied Energy, 2022, vol. 305, issue C, No S0306261921011521

Abstract: This study presents a performance evaluation of ten metaheuristics optimization techniques that are applied to solve the sizing problem for a stand-alone hybrid renewable energy system including a photovoltaic module, wind turbine, and a battery (PV/WT/Battery). The algorithms include genetic algorithm (GA), cuckoo search (CS), simulated annealing (SA), harmony search (HS), Jaya algorithm, firefly optimization algorithm (FA), flower pollination algorithm (FPA), moth flame optimization (MFO), brainstorm optimization in objective space (BSO-OS), and the simplified squirrel search algorithm (S-SSA). The optimization process aims to minimize the total net present cost (TNPC) of the system while maintaining the acceptable deficiency of power supply probability (DPSP). The levelized energy cost and the relative excess power generated criteria are also considered. The studied algorithms have been simulated for four DPSP values (0%, 0.3%, 1%, and 5%), each for 50 independent runs. Based on the simulation results, FPA and SA demonstrated high robustness and accuracy with zero standard deviation and a 0% increase in the TNPC values compared to the optimal solutions. The FAO showed the best performance in terms of execution time with an average of 6.32 s, followed by BSO-OS (6.36 s) and SA (7.84 s). The SA has the best compromise between robustness, accuracy, and rapidity, and is found to be the best option to solve the sizing problem. The FPA is the most advantageous in case the execution time is not crucial for the optimization. Our findings will be a good reference for researchers to select the best technique for the sizing problem.

Keywords: Optimal sizing; Metaheuristic techniques; Hybrid renewable energy system; PV/wind/battery (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261921011521
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:appene:v:305:y:2022:i:c:s0306261921011521

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic

DOI: 10.1016/j.apenergy.2021.117823

Access Statistics for this article

Applied Energy is currently edited by J. Yan

More articles in Applied Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().