Issue |
E3S Web Conf.
Volume 472, 2024
International Conference on Renewable Energy, Green Computing and Sustainable Development (ICREGCSD 2023)
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Article Number | 01015 | |
Number of page(s) | 11 | |
Section | Smart and Energy Efficient Systems | |
DOI | https://doi.org/10.1051/e3sconf/202447201015 | |
Published online | 05 January 2024 |
Minimizing electric vehicle charging costs in the microgrid using the BFGS Quasi-Newton Method
1 Vignan’s Lara Institute of Technology and science, Vadlamudi, Guntur, India
2 Vignan’s NIRULA institute of technology and science for women’s, Peddapalakaluru, Guntur
3 YSR Engineering college of Yogi Vemana University, Proddatur, India
4 JNTUN, Narasaraopet, India
* Corresponding author: jayababu.badugu@gmail.com
Electric vehicles (EVs) offer a compelling solution for mitigating pollution, addressing environmental alterations, and enhancing energy security. This research presents a methodology employing the Broyden Fletcher Gold- farb Shanno quasi-Newton technique to streamline the charging costs associated with plug-in electric vehicles (PEVs). The initial step involves formulating an objective function directed at minimizing the expenses tied to PEV charging. This function takes into account crucial constraints pertaining to charger specifications, state of charge limitations, and voltage levels. Subsequently, we de- tail the application of the BFGS Quasi-Newton algorithm in computing node topology voltages within a microgrid featuring distributed energy resources (DERs). The findings demonstrate that the BFGS-enabled method outperforms alternative approaches in minimizing the cost of charging PEVs
© The Authors, published by EDP Sciences, 2024
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