Solar photovoltaic (PV) is a crucial renewable energy source that converts sunlight into electricity using silicon-based semiconductor materials. However, due to the non-linear characteristic behavior of the PV module, the module’s output power varies according to the solar radiation and the ambient temperature. To address this challenge, maximum power point tracking (MPPT) techniques are employed to extract the maximum amount of power from the PV modules. This paper offers a comprehensive review of widely used traditional and advanced MPPT approaches in PV systems, along with current developments and future directions in the field. Under uniform insolation, these methods are compared based on their strengths and weaknesses, including sensed parameters, circuitry, tracking speed, implementation complexity, true MPPT, accuracy, and cost. Additionally, MPPT algorithms are evaluated in terms of their performance in reaching maximum power point (MPP) under partial shading condition (PSC). Existing research clearly demonstrates that the advanced techniques exhibit superior efficiency in comparison to traditional methods, although at the cost of increased design complexity and higher expenses. By presenting a detailed review and providing comparison tables of widely used MPPT techniques, this study aims to provide valuable insights for researchers and practitioners in selecting appropriate MPPT approaches for PV applications.

In recent years, the use of solar photovoltaic (PV) energy, which is one of the leading renewable energy sources, has become increasingly widespread around the world due to its numerous advantages. However, PV-based electricity generation necessitates a large amount of land. Agrivoltaic (AV) systems, an innovative approach to combining agricultural and electricity production in the same area through solar modules positioned several meters above the surface of the ground, are growing rapidly in renewable energy and farming communities. This study explores Turkey's solar power generation and agricultural activities, combining crop cultivation and electricity generation for sustainable development on the same land. Furthermore, the AV potential for the most agriculture ten cities in different climate zones in Turkey is investigated using the PVsyst program. A list of the most commonly grown crops in the ten selected cities and the types of AV systems that can be employed with these crops is provided. The results show that AV systems present a great opportunity for the optimal integration of solar power generation with food production, especially for the cities of Konya, Kayseri, and Manisa, with the most ideal conditions for agricultural and solar power production. By combining the solar power potential of the country with the production capacity of arable lands, the increasing energy needs can be met and more efficient agricultural production can be provided. This study is expected to demonstrate that in specific regions of Turkey, AV farming will be suitable for certain crops.

Burning fossil fuels for transportation is a major source of greenhouse gas emissions, which contribute to global warming, air pollution, and health problems. Research estimates that cars alone emit more than 300 million tons of carbon dioxide into the atmosphere each year due to the internal combustion engines that use fossil fuels. In contrast to fossil fuel vehicles, electric vehicles have zero tailpipe emissions. Therefore, countries around the world are making efforts to use electric vehicles instead of fossil fuels. Two of the available alternatives to internal-combustion engines are battery and hydrogen fuel cell electric vehicles. This work investigates the basic functionalities and current advancements of battery and hydrogen fuel cell electric vehicles. A comprehensive comparison of the benefits and drawbacks of each technology is provided, along with future forecasts for transportation.

Photovoltaic (PV) modules are devices that transform photon energy into electrical energy. The output power of the PV modules is influenced by the intensity of solar radiation and the ambient temperature. Non-uniform shading can cause variations in the extent of sunlight absorbed by PV modules, resulting in a decrease in power output. Maximum power point tracking (MPPT) techniques are employed to optimize the power output of PV modules by operating them at their maximum power point (MPP). The main objective of the study is to investigate the performance analysis of Perturb and Observe (P&O) and Particle Swarm Optimization (PSO) MPPT strategies in uniform and partially shaded conditions with equally and unequally different irradiance differences. Simulation studies were conducted on the PV circuit model using Matlab/Simulink, and the results were evaluated. MPPT algorithms are compared based on their tracking efficiency and convergence speed when solar radiation conditions vary. The findings of the simulation indicate that the P&O is unable to determine global MPP and gets trapped in one of the local MPPs. However, the PSO is very effective in tracking MPP under different partial shading patterns with more than 96% tracking efficiency. In the first partial shading configuration where the sunlight intensity of the PV modules is uniformly distributed, the PSO technique has reduced steady-state oscillations around the MPP. However, the P&O technique demonstrates superior response time and convergence speed in comparison to the PSO technique.