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Bridging Photovoltaic (PV) energy generation with Electric Vehicle (EV) technology is an essential development in the modern quest for energy sustainability and advanced transportation methods. Consequently, this research focuses on enhancing efficient power utilization in PV-based EVs through the application of a novel Modified Boost-Luo DC-DC converter and a Chaotic Genetic Algorithm -based Maximum Power Point Tracking system. The Modified Boost-Luo converter provides a high voltage conversion ratio by incorporating a Voltage Multiplier Cell (VMC) and Three-Winding Coupled Inductor (3WCL) into its circuit configuration. The augmented PV output from Modified Boost-Luo converter is directed to the Brushless DC (BLDC) motor of the EV through a three-phase Voltage Source Inverter (3ΦVSI). Moreover, speed regulation in the BLDC motor is achieved using a Proportional–Integral (PI) controller. A distinctive feature of the proposed system involves the storage of surplus PV-generated power in a battery, interconnected to the DC-link via a bidirectional converter. In instances of PV power unavailability, the BLDC motor seamlessly taps into the stored energy in the battery for continued operation. The proposed approach is evaluated through both MATLAB simulation and laboratory prototype implementation, showcasing its potential to advance EV technology. [ABSTRACT FROM AUTHOR]

Cultivating negatively photoblastic plants requires, first of all, the provision of a constant supply of electricity, without which it is impossible to cyclically implement the process of watering the plants. Due to the large amounts of heat generated by some plants during their growth cyclic watering is not only necessary to provide water for their growth, but also to cool them down. Lack of power supply and failure to water within a certain period leads to overheating of the plants and their destruction, thus necessitating the disposal of the production batch. Ensuring stable power supply and energy security of the cultivation is possible using an island PV plant, but only integrated with appropriately sized energy storage. This paper presents the results of an analysis of the feasibility of using PV sources to ensure continuous cultivation of Mung bean sprouts. Determination of the energy demand of the sprout-growing plant was made based on the developed transient simulation model of the production line. The level of energy demand was determined for different production scenarios. The availability of solar energy at the location of the production line was analyzed and the size of the PV system integrated with energy storage was determined. For full-scale production, regardless of the period of the year in which it is carried out, the maximum energy demand was determined based on simulation studies at 36 kWh/day. For full-scale production, the size of the PV system should be 96.5 kWp, and the capacity of the energy storage should provide weekly coverage of the production line and be about 252 kWh. [ABSTRACT FROM AUTHOR]

Rapid fluctuations in solar irradiation lead to significant variability in PV power output. Traditional ramp rate control methods use battery energy storage systems to smooth power outputs and provide a more consistent supply to the grid. However, these methods require high initial costs and substantial maintenance. In this study, we propose a novel method for controlling PV power output ramp rates using cooling technology, which is essential to stabilize grid operations and ancillary services. The proposed method adjusts power generation efficiency in real-time by controlling PV panel temperature, leveraging their thermoelectric properties. The effectiveness of our method was validated by simulation based on real-world data, which showed reductions in mean and maximum ramp rates of 43.5% and 76.2%, respectively, compared to traditional battery storage solutions. Notably, these improvements were achieved with a cooling unit having a coefficient of performance of less than 10 and a minimal battery capacity of 20 kWh, highlighting the efficiency of the method and its potential to significantly lower system costs and environmental impacts compared to traditional control strategies. • A ramp rate control method for PV systems is proposed. • PV cooling is used to control PV power generation. • It prevents ramp rate increase without large-capacity batteries, gas turbines, or dump loads. • The proposed method reduces the mean ramp rate by 43.5% compared to the battery-only method. [ABSTRACT FROM AUTHOR]