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.

Photovoltaic (PV) modules have emerged as a promising technology in the realm of sustainable energy solutions, specifically in the harnessing of solar energy. Photovoltaic modules, which use solar energy to generate electricity, are often used on terrestrial platforms. In recent years, there has been an increasing inclination towards the installation of photovoltaic (PV) modules over water surfaces, including lakes, reservoirs, and even oceans. The novel methodology introduces distinct benefits and complexities, specifically pertaining to the thermal characteristics of the modules. In order to accomplish this objective, a photovoltaic (PV) module system with a capacity of 1 MW was developed as a scenario in the PVsyst Program. The scenario simulation was conducted on the Mamasın Dam, situated in the Gökçe village within the Aksaray province. To conduct the efficiency analysis, a comparative evaluation was conducted between bifacial and monofacial modules, which were installed from above the water at 1 m. The comparison was made considering two different types of modules. Additionally, the albedo effect, water saving amount, and CO₂ emissions of the system were also investigated. Albedo measurements were made in summer when the PV power plant will operate most efficiently. As a result of the simulations, it was found that bifacial modules produce 12.4% more energy annually than monofacial modules due to the albedo effect. It is estimated that PV power plant installation will save 19,562.695 and 17,253.475 tons of CO₂ emissions in bifacial and monofacial systems, respectively.

This study shows the dust effect on solar panel efficiency based on experimental measurements. Sieve analysis has been performed to investigate the effect on the efficiency of the panel. Dust particles have been divided into different sizes such as (-75), (+75/-105), (+105/-250), (+250/-450). In addition, each piece weighed 20 g, uniformly sprinkled onto a 40-Watt SUNNY polycrystalline panel. In order to obtain the output voltages of the PV panel used a data acquisition card. Additionally, a photodiode sensor has been used in order to obtain the light reflection data from the panel to the outside while there had covered different diameters of dust particles on the panel. The data set consisting of electrical parameters have been used to compered both experimental study and Artificial Neural Network (ANN) output. There were 5 different data sets with the clean PV panel in this study (randomly selected data from it used as %40 training - %60 test) and the clean panel data have been used twice in the training and test part of the ANN. In this study, it has been observed that the ANN method can be used to estimate panel efficiency due to the linearity (The R-value was gotten nearly equal to 1 and it shows that there is a linear relationship between outputs and targets.) if the appropriate transfer function is selected. Also, this study shows that as the particle diameter covering the panel gets smaller, the output voltage of the panel decreases linearly.

This paper describes a newly developed system for harvesting thermoelectric energy from photovoltaic panels. This system helps to power monitoring systems for photovoltaic panels (PVs) in locations where there is no energy source using waste thermal energy from PVs exposed to the sun’s rays. In the study described here, the thermal energy from a PV panel was captured and transferred to a thermoelectric generator (TEG). A temperature gradient was created by reducing the temperature using an aluminium heat sink in ambient weather conditions. This temperature gradient was used to generate electricity via two TEGs. In field tests carried out in April, in Aksaray province in central Turkey, the maximum temperature gradient due to solar radiation was measured as 21.08 °C. The harvested energy was increased to a usable level of 4.1 V using a DC-to-DC converter and stored in a li-ion rechargeable battery. The maximum charge current level of the battery was 147 µA. The maximum harvested energy was 458.64 mW, and a stable level of around 350 mW was achieved. The experimental operation of the prototype system was carried out in stable weather conditions; however, weather and climatic conditions greatly affect levels of energy harvested as a result of changing temperature gradients. The energy obtained with the prototype may reduce the battery maintenance costs of PV monitoring systems and lead to the development of new such systems which cannot presently be used due to a lack of energy.