Please use this identifier to cite or link to this item: http://dspace.iitrpr.ac.in:8080/xmlui/handle/123456789/4614
Title: Hybrid quantum-classical solution for electric vehicle charger placement problem
Authors: Rao, P.U.
Sodhi, B.
Keywords: Quantum computing
·Electric vehicle charging station placement
Quantum unconstrained binary optimization
Variational quantum circuits
Quantum machine learning
Issue Date: 20-Jun-2024
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
URI: http://dspace.iitrpr.ac.in:8080/xmlui/handle/123456789/4614
Appears in Collections:Year-2023

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