 Modified teaching-learning-based optimization by orthogonal learning for optimal design of an electric vehicle charging stationDitao Duan and Roza Poursoleiman Utilities Policy, 2021, vol. 72, issue C Abstract: The provision of a safe environment has led to the growth of electric vehicles (EVs), whose propagation in the market depends on features such as price, battery technology, economy, and improvement of charging stations. This paper proposes a charging station for plug-in electric vehicles (PEVs) connected to the distribution system, along with the energy storage system's batteries, diesel generator, and photovoltaic panels. The charging facilities are also designed and optimized at three levels of fast, medium, and slow speeds. Since this model integrates many decision variables and cannot be accurately solved by traditional mathematical methods, a new modified optimization algorithm is presented. The modified teaching-learning-based optimization (TLBO) based on orthogonal learning (OL), or OLTLBO, is proposed to solve the optimization problem. The results confirm that the model successfully uses all the available options to design the EVCS. Keywords: Electric vehicle charging station; TLBO algorithm; Renewable energy resources; Probabilistic models; Optimization (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:juipol:v:72:y:2021:i:c:s0957178721000874 DOI: 10.1016/j.jup.2021.101253 Access Statistics for this article Utilities Policy is currently edited by Beecher, Janice More articles in Utilities Policy from Elsevier |
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