Abstract
Electric vehicle (EV) market is growing rapidly in India with support of the government which aims to fulfill its commitment for carbon neutrality. The government of India has launched a scheme named Fast Adaptation and Manufacturing of Electric Vehicles to adapt to this emerging technology. EV charging infrastructure is a critical step for tapping the full potential for electrification of urban transport sector through EVs. Development of EV charging infrastructure will give a boom to EVs in the automobile industry. Therefore charging infrastructure needs to cope up with this growing market. This increase will lead to excessive loading on the distribution network. Conventional EV chargers have a significant impact on the distribution grid. Microgrids along with renewable energy generations have the potential to lessen the impacts of EV charging on the distribution network. This research explores the potential of renewable and conventional sources to formulate a smart charging strategy for EV charging. A standalone/self-governing hybrid charging scheme is formulated to minimize the dependence on grid for power. Scheduling of individual components of the EV charging system is done by formulating a smart algorithm which helps in controlling power flow among different system components. Optimal sizing of different components is done keeping in mind the reliability of the system. Number of photovoltaic panel pairs, wind turbines, autonomy days of battery, and diesel generator units are optimized using computational intelligence tools to fulfill the EV load for a year. Optimal location of the charging stations within and beyond the urban limits is identified using analytical study. Several case studies are performed for EVs used for intracity and intercity commuting in the identified optimal charging station locations. For intercity travel analysis of the EVs, rest areas on Lucknow–Agra Expressway are explored. Extensive experimental studies result in accurate sizing of charging station components while maintaining the overall reliability of the system and enhancing the share of renewable energy sources within the given system constraints. The obtained results indicate the feasibility of a smart self-governing hybrid EV charging system subject to appropriate modeling and availability of data which can be instrumental in coping up with the increasing EV charging infrastructure demand.
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