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Go to Editorial ManagerSolar panels are constantly evolving, with changes occurring in the materials used, panel shapes, and the method used to attach solar cells to the panels. Solar radiation consists of two components: photovoltaic energy, which is used to generate electricity via photovoltaic panels, and thermal energy, which, on the other hand, can reduce the efficiency of photovoltaic panels. Thermal photovoltaic panels are a recent breakthrough in the industry as they use light to generate energy and heat to reheat cryogenic liquid for a variety of purposes. One subtype that is gaining popularity is hybrid photovoltaic thermal panels, which are designed to enhance heat use by adding a heat storage medium, with phase change materials being a noteworthy example. Despite their numerous benefits, these materials have limited heat conductivity, necessitating substantial research efforts to improve this attribute. However, most research focus solely on enhancing conductivity without applying the findings to PV panels in a comprehensive manner. This study fills this gap by reviewing the phase change materials accessible locally, picking Iraqi wax, researching additions, selecting micro- particles of aluminum oxide (Al2O3), investigating the mixing procedure, and calculating the ideal mixing ratio (6% additive to wax). The combination is then placed to a normal solar panel, resulting in a hybrid photovoltaic panel with a complicated phase transition material reinforced with aluminum oxide.
The sun is an inexhaustible source of clean energy. For a long time, humans perceived the sun as a source of heat and light, without thinking of using it fully for their purposes. The worldwide solar photovoltaic (PV) market has been growing rapidly, with significant investments leading to increased capacity. Mathematical models are used to calculate solar radiation, taking into account various meteorological factors to predict solar energy generation. The construction of P-V curves helps understand the output of PV systems, crucial for optimizing energy conversion efficiency. The photovoltaic effect allows solar cells to convert light into electrical energy, highlighting the importance of understanding the relationship between current and voltage in solar panels. In this work, the mathematical model of PV is presented and the equations that describe the relation between PV and environment are presented. Finally, a complete model is designed in Matlab and the results are presented.
Hydrogen fuel is a good alternative to fossil fuels. It can be produced using a clean energy without contaminated emissions. This work is concerned with experimental study on hydrogen production via solar energy. Hybrid photovoltaic thermal system (PV/T) is used to convert solar radiation to electrical and thermal energy. The electrical energy is used to analyze water into hydrogen and oxygen by using alkaline water electrolyzer with stainless steel electrodes. The absorbed thermal energy is used to heat circulating water inside the copper serpentine pipe fixed on the back surface of the PV panel. A perforated pipe connected on the upper edge of PV panel is used to spray a thin layer of water on the PV panel surface for auxiliary cooling and improve the generated electrical power. The hydrogen production system is tested at different temperature of electrolysis water (40, 45, 50, 55, 60)?C. The experimental results show that the PV module electrical efficiency is improved by (14.31)%. while the power generated was enhanced by (3.94 to 15.40)%. The maximum hydrogen production rate is 153.3 ml/min, the efficiency of the system is 20.88% and the total amount of hydrogen produced in one day is 220.752 liter.
Photovoltaic (PV) systems have gained importance as one of the major renewable energy technologies because of its clean and sustainable characteristics; however, PV nonlinear current-voltage and power-voltage characteristics are a significant factor in limiting the maximum available power determined by the amount of available power under different environmental and load conditions. Maximum Power Point Tracking (MPPT) algorithms are one of the most important performance enhancements to help make PV energy conversion systems more efficient and reliable. Conventional MPPT techniques such as Perturb and Observe (P&O) have been widely used due to their simple and easy implementation in terms of control strategies, however, they exhibit steady-state oscillations, slow convergence, and poor dynamic performance under fast changing conditions of irradiation and load. To overcome these limitations, validation of intelligent and bio-inspired optimization and MPPT algorithms have attracted a great deal of interest. This paper includes a comprehensive comparative analysis of three MPPT techniques that are: conventional P&O algorithm, Grey Wolf Optimization algorithm (GWO), and Teaching-Learning-Based Optimization algorithm (TLBO). A detailed model of PV system coupled with dc-dc boost converter is built in Matlab/Simulink and the algorithms are tested with a constant irradiation and variable load and with simultaneous irradiation and load variation. Performance criteria like tracking performance, speed of convergence, steady state oscillations and robustness under dynamic conditions are analyzed. Based on the simulation results it is proven that both GWO and TLBO clearly outperforms the conventional P&O algorithm. Amongst all the optimization-based approaches, TLBO provides good performance with near-instantaneous convergence, minimum oscillations and consistent tracking efficiency is close to 100% for all the tested scenarios. The results prove that TLBO-based MPPT offers solid and computationally efficient solution for real world applications of PV systems especially in those with frequent and random operating condition variation environment.
The partial shading conditions have a significant effect on the performance of Photovoltaic system and the ability of delivering energy. In this study, the impact of different partial shading on the mono crystalline (88W) PV module performance was investigated in this study. Horizontal string, vertical string, and single cell shading at different percentage of shading area have been studied. It is found that the horizontal string shading is more severe on the efficiency of the PV panel. In contrast, the efficiency of PV panel with cellular and vertical cell shading was less during the tests. The experimental results showed that the power losses were 99.8%, 66% and 56.8 % for horizontal, cellular and vertical shading respectively via applied non transparent material as shading element by 100% of shading area at 500 W/m2. Moreover, transparent material used to shade whole module horizontally, different shading area and different radiation level applied to find electrical characteristics of the module under these conditions. The results show that at 800W/m2 of irradiation levels and no shading condition the power was 68.6W, by increase shading area by 20% in each step, the power reducing by 44.94, 47.58, 49.42, 50.57 and 52.4% in compared with their initial value at no shading condition.
This paper displays the improvement of Graphical User Interface programming for sizing principle segment in Stand-Alone PV system and PV- Diesel hybrid power system based on Iraq conditions. The solar system software is a tool depends on the input data by the user to give correct results on the basis of what has been introduced. Therefore, this software tool Includes products (PV modules, charge controller, inverter, battery and diesel generator) which can be obtained from the market with their detail. This software presents a guideline for photovoltaic system integrator to match the load requirement to design the effective size of components and system configuration, in hybrid PV–Diesel system. The ratio of photovoltaic solar energy to diesel generators is introduced by considering the contribution of hybrid system energy.
Maximum Power Point Tracking (MPPT) techniques are essential for maximizing energy extraction from photovoltaic (PV) systems under diverse environmental conditions. This paper reviews three widely used MPPT methods Perturb and Observe (P&O), Fuzzy Logic Control (FLC), and Artificial Neural Networks (ANN) highlighting their effectiveness in addressing challenges such as temperature fluctuations, varying irradiance, and shading. The P&O method is noted for its simplicity and low computational requirements, but it suffers from oscillations around the maximum power point under rapidly changing conditions. FLC offers enhanced adaptability and robustness by mimicking human decision-making, performing well in dynamic environments with moderate complexity. ANN-based methods demonstrate superior tracking efficiency and fast convergence, particularly under complex and highly variable conditions, due to their ability to learn and generalize from data. These findings underscore the importance of continued development of MPPT techniques, especially intelligent and hybrid approaches, to meet the growing demand for sustainable energy. Thus, solar energy remains a highly viable solution for modern energy needs.
The efficiency of the solar PV panel decreases significantly as the PV panel’s operating temperature increases. There are many cooling techniques might be suitably deal with this problem to enhance the solar panel efficiency. The presented cooling technique used for solving the PV panel’s temperature elevation is an active close loop cooling system, accomplished using two water glazing chambers made from acrylic glass placed at the PV panel surfaces (rear and front). These champers are utilized for cooling down the PV cell’s temperature, as well as filtering the useful sunlight spectrum. The results show that the PV cell’s temperature reduction by 50.06% with using the cooling system, this leads to an average increase in the maximum output power and consequently electrical efficiency of the PV panel by about 12.69% and 14.2%, respectively.