Emissions from the Internal Combustion Engine (ICE) Vehicles are one of the primary cause of air pollution and climate change. In recent years, Electric Vehicles (EVs) are becoming a more sensible alternative to these ICE vehicles. With the recent breakthroughs in battery technology and large scale production, EVs are becoming cheaper. In the near future, mass deployment of EVs will put severe stress on the existing Electrical Power System (EPS). Optimal scheduling of EV can reduce the stress on the existing network while accommodating large scale integration of EV. Integration of these EVs can provide several economic benefits to different players in the energy market. In this paper, recent works related to the integration of EV with electrical power system are classified based on their relevance to different players in the electricity market. This classification considers four players-Generation Company (GENCO), Distribution System Operator (DSO), EV Aggregator and End User. Further classification is done based on scheduling or charging strategies used for the grid integration of EVs. This paper provides a comprehensive review of technical challenges in grid integration of EVs along with their solution based on optimal scheduling and controlled charging strategies.

Summary With the recent breakthroughs in battery technology and large scale production, electric vehicles (EVs) are becoming cheaper. In a few years, mass deployment of EVs will put severe stress on the electricity network. Charging of EV during peak hours may overload the distribution grid transformer, and EV owners may have to pay more money for electricity during peak hours. To address these issues, a coordinated scheduling model is proposed in this paper. A mathematical model is formulated to minimise the charging cost of each EV while satisfying the constraints. In this work, time of use (ToU) tariff from the utility and actual power demand from household and EVs are used to conduct simulation for one week in summer and winter season with different levels of EV penetration. The results demonstrate that the proposed scheduling model can significantly reduce the charging cost for the EV owner and power peaks in the distribution network.