Charging Station Placement for Electric Vehicles: A Case Study of Guwahati City, India

• Published in: IEEE access Vol. 7; pp. 100270 - 100282
• Main Authors: Deb, Sanchari, Tammi, Kari, Kalita, Karuna, Mahanta, Pinakeswar
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Bayes methods; charging station; Charging stations; City; cost; Decision making; Depletion; Economic factors; Electric power grids; electric vehicle; Electric vehicle charging; Electric vehicles; Fossil fuels; Infrastructure; Linear programming; Machine learning; Optimization; Pareto optimum; Placement; Planning; Reliability aspects; Roads; traffic; Urban areas; Voltage stability; India
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2019.2931055

The ever-increasing population of India accompanied by the recent concerns regarding fossil fuel depletion and environmental pollution has made it indispensable to develop alternate mode of transportation. Electric vehicle (EV) market in India is expanding. For acceptance of EVs among the masses, development of charging infrastructure is of paramount importance. This paper formulates and solves the charging infrastructure-planning problem for Guwahati, India, that will develop as a smart city soon. The allocation of charging station problem was framed in a multi-objective framework considering the economic factors, power grid characteristics, such as voltage stability, reliability, power loss, as well as EV user's convenience, and random road traffic. The placement problem was solved by using a Pareto dominance-based hybrid algorithm amalgamating chicken swarm optimization (CSO) and the teaching learning-based optimization (TLBO) algorithm. Finally, the Pareto optimal solutions were compared by fuzzy decision-making.