Abstract
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
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Code is made available online for verifying the results - https://bit.ly/EVCS-Paper
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Rao, P.U., Sodhi, B. Hybrid quantum-classical solution for electric vehicle charger placement problem. Soft Comput 27, 13347–13363 (2023). https://doi.org/10.1007/s00500-022-07478-x
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DOI: https://doi.org/10.1007/s00500-022-07478-x