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Summary Rapid growth of electric vehicles (EVs) has necessitated the devolvement of sustainable and easily accessible charging stations. Transport sector electrification and increased popularity of EVs make researcher to search for charging stations. In this paper, a new methodology regarding electric vehicle charging spot is proposed. In the study, allocation of the parking lot and capacitor is suggested for congestion management along with reactive power compensation. To this end, sensitivity analysis is performed by evaluating the inverse Jacobian matrix from the power flow studies. In order to optimally determine the size of parking lot, biogeography‐based optimization (BBO) technique is adopted. The effectiveness of the anticipated technique is tested on adapted IEEE 34‐bus distribution network. The outcome attained by BBO technique is equated with particle swarm optimization.

Electrification of transport sector is gaining popularity and congested cities are taking bold steps in this direction, hence the mushrooming of metros, electric trams, BRT corridors with EVs and promotion of EV adoption in general in several countries. Hence charging stations are expected to be increased among residential area in future.In this paper, optimum location for charging of electric vehicles (EVs) and it's charging strategy in an IEEE-34 distribution system is proposed. To find the optimum location, a 24 hour load demand is varied at given junction nodes and the corresponding sensitivity indexes are determined. These indexes are derived from the inverse Jacobian matrix from the Newton-Raphson power flow analysis and aid in selecting suitable location for charging. Next, in the study, a methodology that depicts the size of charging station is discussed. Charging of EVs at selected node is discussed based on real time price data. The peak period gets shifted to valley period wherein real time price is low.

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