Although electric vehicles (EVs) play a vital role in realizing remarkable features, however, the integration of a huge number of EVs leads to grid congestion as well. As a result, uncontrolled charging might give rise to undervoltage and complex congestion in the electric grid. The reasons for the uncontrolled charging of EVs have been investigated in the recent past to mitigate the effects thereof. It is very challenging to achieve controlled charging due to different constraints at the customer end; therefore, it is better to take the benefits of power prediction schemes for the charging and discharging of EVs. The power prediction scheme is based on a practical power forecast system that exploits the needs of various patterns, and the current research focuses on considering users’ demands. The primary objective of this study is to develop an effective and efficient coordination system for the charging and discharging of EVs by exploiting a smart algorithm that intelligently tackles the possible difficulties to attain optimum power requirements. In this context, a model is proposed based on stochastic methods for analyzing the impact of vehicle-to-grid (V2G) charging and discharging in the microgrid environment. A Markov model is used to simulate the use of EVs. This method works well with the Markov model because of its ability to adjust to random changes. When considering an EV, its erratic travel patterns suggest a string of events that resemble a stochastic process. The proposed model ensures that high power requirements are met during peak hours in a cost-effective manner. In simpler words, the promising features of the proposed scheme are to meet electricity/power demands, monitoring and the efficient forecasting of power. The outcomes revealed an effective power system, EV scheduling, and power supply without compromising the electric vehicle’s presentation of the EV owner’s tour schedule. In terms of comprehensiveness, the developed algorithm exhibits a significant improvement.

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Electric vehicles (EVs) are becoming more attractive for a variety of reasons. One of the major advantages of EVs is that they emit fewer polluted gases. Other factors that must be addressed include an increase in fuel prices and a decline in energy resources such as fossil fuels. These characteristics have a greater impact on Pakistan’s clean and green image. Electric vehicles are becoming an attractive option for reducing global fossil fuel usage, as well as CO2 emissions, from road transportation. The electricity required to charge an EV’s battery is commonly sourced from the power grid. When EVs are charged by the electrical grid, there are significant power constraints in the system. To promote renewable energy consumption and reduce CO2 emissions, specific solar system-based charging stations should be designed. Other benefits of renewable energy generation include increased grid flexibility and reduced grid congestion. Moreover, the State of Azad Jammu and Kashmir, Pakistan, has a huge potential for solar energy. This article investigates the possibility of designing a solar photovoltaic-based EV charging station for security bikes located in the State of Azad Jammu and Kashmir, Pakistan. Before installing a PV charging station, the charging station’s feasibility must be studied. The proposed study also analyzes the power reliability, energy cost, and CO2 emissions of a PV-powered charging station. The proposed system’s outcomes are compared to grid-based charging stations. In comparison to other existing approaches, there is a significant reduction in greenhouse gas (GHG) emissions, including CO2, CO, SO2, and NOX. The proposed study anticipates the economic and environmental benefits of EV charging stations powered by renewable energy resources.

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The integration of Renewable Energy Resources (RERs) into Power Distribution Networks (PDN) has great significance in addressing power deficiency, economics and environmental concerns. Photovoltaic (PV) technology is one of the most popular RERs, because it is simple to install and has a lot of potential. Moreover, the realization of net metering concepts further attracted consumers to benefit from PVs; however, due to ineffective coordination and control of multiple PV systems, power distribution networks face large voltage deviation. To highlight real-time control, decentralized and distributed control schemes are exploited. In the decentralized scheme, each zone (having multiple PVs) is considered an agent. These agents have zonal control and inter-zonal coordination among them. For the distributed scheme, each PV inverter is viewed as an agent. Each agent coordinates individually with other agents to control the reactive power of the system. Multi-agent actor-critic (MAAC) based framework is used for real-time coordination and control between agents. In the MAAC, an action is created by the actor network, and its value is evaluated by the critic network. The proposed scheme minimizes power losses while controlling the reactive power of PVs. The proposed scheme also maintains the voltage in a certain range of ±5%. MAAC framework is applied to the PV integrated IEEE-33 test bus system. Results are examined in light of seasonal variation in PV output and time-changing loads. The results clearly indicate that a controllable voltage ratio of 0.6850 and 0.6508 is achieved for the decentralized and distributed control schemes, respectively. As a result, voltage out of control ratio is reduced to 0.0275 for the decentralized scheme and 0.0523 for the distributed control scheme.