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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.

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Over these years, dependency of electric generation on renewables is increasing steadily. The renewable energy sources are usually connected to the electric grid on the distribution networks. Energy supply from prominent renewable sources like wind and solar are restricted due to the high level of unpredictability and intermittency associated with them. This leads to the inefficient and less reliable output from these sources. Thus proper generation prediction, sizing and intermittency mitigation of renewable energy sources such as wind and solar photovoltaic (PV) is necessary while placing them on the feeder. As these sources are distributed energy sources, the loss minimization can be one of the opportunities in addition to their generation support. This paper deals with the optimal sizing of solar PV and battery combination in a grid connected system. Solar PV generation is seen as the future generation source and battery storage with its matured technology can support it to become more reliable source in a power system. Here an analytical method for sizing of solar PV and battery is proposed. The line losses and intermittency minimization is the prime consideration for the sizing and placement of the solar PV and battery. To tackle with the variability of the solar PV generation, it is predicted by probability density function and supported by battery energy storage. The battery energy storage is properly sized to satisfy the state of charge limitations. The location and sizing methodology is applied to a 13-bus test system using MATLAB. With the proposed optimal sizing methodology the losses can be reduced up to 83 % during the solar PV generation period and a small amount of battery support can help to get constant power supply to the grid from the solar PV.

Decarburization of electrical systems encourage high wind power into electric power systems and the electrification of transport sectors through electric vehicles (EVs). The increasing penetration of uncertain wind power generation and transportation networks via EV charging stations has introduced challenges for system operators to manage power systems and market operations. In this context, this paper presents a stochastic AC security-constrained unit commitment (SCUC) model to clear day-ahead energy and reserve markets considering transportationelectricity networks through EV charging stations in the presence of uncertain wind power and generator contingency. Pre-contingency ranking is a common strategy for reducing the time of the SCUC problem, but it provides high-impact outages. To address this issue, generator outages ranked first are identified using the postcontingency generator response ranking approach. The main contribution of this