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Renewable energy sources such as solar are becoming increasingly popular worldwide. Mathematical derivation is used to show the structural framework of PV cells and their models with a single-diode configuration. This paper proposed a two-step optimization technique for extracting the unknown parameters of solar PV cells and modules. The implementation of the proposed techniques is to find the unknown parameters of the PV module from Kyocera (KC200GT). First, we configured the single-diode configuration of the PV equation in terms of five unknown parameters (Iph, I0, Vt, Rs, and Rsh) and in terms of two unknown parameters (Rs and Vt). After that, we implemented the proposed two-step optimization techniques for extracting the unknown parameters (Iph, I0, Vt, Rs, and Rsh) of the PV module Kyocera (KC200GT). Also, we used the genetic algorithm (GA) and particle swarm optimization (PSO) techniques to find the unknown parameters (Iph, I0, Vt, Rs, and Rsh) of the PV module from Kyocera (KC200GT). The performance of the proposed two-step optimization techniques was compared with the traditional single-stage optimization techniques: particle swarm optimization (PSO), genetic algorithms (GAs), grey wolf optimization (GWO), Villalva’s method, Accarino’s method, Iterative method, and Silva’s method. The test results and the output P–V waveform indicate that the proposed method is more efficient and has a greater impact than the standard techniques.

Due to global warming and climate change, it is essential to produce power using renewable sources, such as solar, wind, fuel cells, etc. The traditional grid shifts towards the smart grid by infusing digital communication techniques and information technology. As the current power system is shifting towards a smart grid, the utility and prosumers participate in the energy trading process. Due to the distributed nature of the smart grid, providing a fair price among them is becoming a difficult task. The article introduces a model for energy trading in a smart grid by allowing participants to negotiate in multiple stages using a game-theory-based multi-stage Nash Bargaining Solution (NBS). The model’s application of game theory enables the participants to decide on a mutually acceptable price, thereby encouraging the utility, private parties and prosumers (those who are able to generate and consume energy) to participate in the trading process. Since all parties participate in the trading procedure, greenhouse gas emissions are reduced. The proposed model also balances the benefits of consumers and producers in the final agreed fixed price. To demonstrate the efficacy of the proposed work, we compare the analytical results with feed-in-tariff (FiT) techniques in terms of consumers’ energy bills and producers’ revenue. For experimental analysis, 20 participants are considered, where the percentage reduction in the bill of each consumer and the percentage increment of revenue of each producer are compared to FiT. On average, the overall bill of the consumer is reduced by 32.8%, and the producers’ revenue is increased by 64.83% compared to FiT. It has been shown further that the proposed model shows better performance as compared to FiT with an increase in the number of participants. The analysis of carbon emission reduction in the proposed model has been analyzed, where, for 10 participants, the carbon emission reduction is approximately 28.48 kg/kWh, and for 100 participants is 342.397 kg/kWh.

Conventional DC-DC boost converters have played a vital role in electric vehicle (EVs) powertrains by enabling the necessary voltage to increase to meet the needs of electric motors. However, recent developments in high-gain converters have introduced new possibilities with enhanced voltage amplification capabilities and efficiency. This study discusses and evaluates the state-of-the-art high-gain DC-DC converters for EV applications based on the Quadratic Boost Converter (QBC). Research into innovative topologies has increased in response to the increasing demand for efficient and high-performance power electronic converters in the rapidly expanding EV industry. Due to its ability to provide more significant voltage gains than conventional boost converters, the QBC has become a viable option for meeting the unique requirements of EV power systems. This survey focuses on the efficiency, power density, and overall performance parameters of QBC-based high-gain converters. The literature review provides a foundation for comprehending power electronics converters’ trends, challenges, and opportunities. The acquired knowledge can enhance the design and optimization of high-gain converters based on the QBC, thereby fostering more sustainable and efficient power systems for the expanding electric mobility industry. In the future, the report suggests that investigating new high-gain converter design methodologies will reduce component stress and enhance the intact system efficiency.

Electric vehicles (EVs) are universally recognized as an incredibly effective method of lowering gas emissions and dependence on oil for transportation. Electricity, rather than more traditional fuels like gasoline or diesel, is used as the main source of energy to recharge the batteries in EVs. Future oil demand should decline as a result of the predicted rise in the number of EVs on the road. The charging infrastructure is considered as a key element of EV technology where the recent research is mostly focused. A strong charging infrastructure that serves both urban and rural areas, especially those with an unstable or nonexistent electrical supply, is essential in promoting the global adoption of EVs. Followed by different EV structures such as fuel-cell- and battery-integrated EVs, the charging infrastructures are thoroughly reviewed in three modes, specifically—off-grid (standalone), grid-connected, and hybrid modes (capable of both standalone and grid-connected operations). It will be interesting for the readers to understand in detail several energy-source-based charging systems and the usage of charging stations for different power levels. Towards the improvement of the lifetime and efficiency of EVs, charging methods and charging stations in integration with microgrid architectures are thoroughly investigated. EVs are a multi-energy system, which requires effective power management and control to optimize energy utilization. This review article also includes an evaluation of several power management and control strategies followed by the impact assessment of EVs on the utility grid. The findings and the future research directions provided in this review article will be extremely beneficial for EV operators and research engineers.