Hybrid quantum-classical solution for electric vehicle charger placement problem

被引:0
作者
Poojith U. Rao
Balwinder Sodhi
机构
[1] IIT Ropar,Department of Computer Science
来源
Soft Computing | 2023年 / 27卷
关键词
Quantum computing; Electric vehicle charging station placement; Quantum unconstrained binary optimization; Variational quantum circuits; Quantum machine learning;
D O I
暂无
中图分类号
学科分类号
摘要
Building a dependable network of electric vehicle charging stations (EVCSs) requires satisfying the demands and constraints of EV owners, energy grids, and the entities that will own and operate the EVCSs. Thus, determining the optimal spatial placement of EVCS becomes essential for the success of EVs in a market. Time taken by classical computers to solve such combinatorial optimization problems increases exponentially with the size of the area, making them non-scalable. We propose a novel quantum-classical solution to solve this problem. A crucial idea of our approach is to move the more complex combinatorial optimization portion of the problem into a quantum algorithm. We show that our solution gives more than 500% improvement in speed compared to the state-of-the-art classical methods, thus making it well suited for scalability scenarios. For allowing independent verification of our results, we have shared all our software artefacts here: https://bit.ly/EVCS-Paper
引用
收藏
页码:13347 / 13363
页数:16
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