This paper proposes an effective approach to solve renewable distributed generators (RDGs) and electric vehicle charging station (EVCS) allocation problems in the distribution system (DS) to reduce power loss (PLoss) and enhance voltage profile. The RDGs considered for this work are solar, wind and fuel cell. The uncertainties related to RDGs are modelled using probability distribution functions (PDF). These sources’ best locations and sizes are identified by the voltage stability index (VSI) and political optimization algorithm (POA). Furthermore, EV charging strategies such as the conventional charging method (CCM) and optimized charging method (OCM) are considered to study the method’s efficacy. The developed approach is studied on Indian 28 bus DS. Different cases are considered, such as a single DG, multiple DGs and a combination of DGs and EVs. This placement of multiple DGs along with EVs, considering proper scheduling patterns, minimizes PLoss and considerably improves the voltage profile. Finally, the proposed method is compared with other algorithms, and simulated results show that the POA method produces better results in all aspects.

The rise of electric vehicles (EVs) has a massive impact on the electricity grid due to the electrification of vehicles in the transportation sector. As a result, various techniques are needed to minimize the effects of charging on the grid. One of these techniques is having intelligent coordination between the various components of the EV charging network. This ensures that the network has enough electricity to support the charging needs of the vehicles. This article provides an overview of the many aspects of the EV industry and its charging infrastructure. It also provides a step-by-step approach for implementing the Vehicle to Grid (V2G) deployment, the utilization of recordings from the data by the EV battery through Artificial Intelligence and the cost-benefit analysis from effective utilization of the V2G method. The paper also explores the various aspects of the EV market and the role of aggregators and consumers. Finally, it assesses the possibility of expansion of the EV charging and grid integration system and outlines its challenges and solutions.

Electric vehicles (EVs) have become a feasible alternative to conventional vehicles due to their technical and environmental benefits. The rapid penetration of EVs might cause a significant impact on the distribution system (DS) due to the adverse effects of charging the EVs and grid integration technologies. In order to compensate for an additional EV load to the existing load demand on the DS, the distributed generators (DGs) are integrated into the grid system. Due to the stochastic nature of the DGs and EV load, the integration of DGs alone with the DS can minimize the power losses and increase the voltage level but not to the extent that might not improve the system stability. Here, the EV that acts as a load in the grid-to-vehicle (G2V) mode during charging can act as an energy source with its bidirectional mode of operation as vehicle-to-grid (V2G) while in the discharging mode. V2G is a novel resource for energy storage and provision of high and low regulations. The article proposes a smart charging model of EVs, estimates the off-load and peak load times over a period of time, and allocates charging and discharging based on the constraints of the state of charge (SoC), power, and intermittent load demand. A standardized IEEE 33-node DS integrated with an EV charging station (EVCS) and DGs is used to reduce the losses and improve the voltage profile of the proposed system. Simulation results are carried out for various possible cases to assess the effective utilization of V2G for stable operation of the DS. The cost–benefit analysis (CBA) is also determined for the G2V and V2G modes of operation for a 24-h horizon.

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