Multi-objective optimisation method of electric vehicle charging station based on non-dominated sorting genetic algorithm
Jia Liu,
Jin Huang and
Jinzhi Hu
International Journal of Global Energy Issues, 2022, vol. 44, issue 5/6, 413-426
Abstract:
There are some problems in the existing objective optimisation planning methods of electric vehicle charging station, such as low accuracy and long optimisation time. By calculating the input cost, combined closure flow and minimum node voltage of the charging station through the objective function, the optimisation objective was determined. According to the determined optimisation objective, the multi-objective comprehensive planning model of the electric vehicle charging station is constructed. After the initial solution setting, coding, decoding and other iterative operations, the multi-objective comprehensive planning model of the electric vehicle charging station is solved and the optimisation result is obtained. The multi-objective optimisation of electric vehicle charging station is realised. The results show that the highest accuracy is about 95%.
Keywords: non-dominated sorting genetic algorithm; electric vehicle charging station; multi-objective optimisation; decoding. (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations: View citations in EconPapers (6)
Downloads: (external link)
http://www.inderscience.com/link.php?id=125413 (text/html)
Access to full text is restricted to subscribers.
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:ids:ijgeni:v:44:y:2022:i:5/6:p:413-426
Access Statistics for this article
More articles in International Journal of Global Energy Issues from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().