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Go to Editorial ManagerThis 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.
Due to the Kurdistan regional government-KRG district mission potential towards huge solar energy power generation plant investments by global investors, a genuine study is required to explore the impact of PV-panels installation angles on power generation gain within all seasons duration as the KRG located in four season area which, affect the annual total power gain due to daylight duration effect in each season. The proposed study was conducted within a duration of “513” days utilizing three PV tilt installation angle tests of “ 30⁰, 35⁰, and 40⁰ ” with “ 545 watts single side PV plates” selecting the Erbil district area gaining a crucial role in maximizing energy output for comparison, Results presented a significant variation in power gain due to deviations in annual effective daylight duration effectively mostly a reduction in cold seasons within 25%-37.7% drops compared to the hot season, while the sunset and sunrise duration presented a significant influence of 5%-10% drops in power generated. The season change shows a significant influence of weather variation in each calendar on power gain annually. The installation orientation angle impact presented divergence in production within the cold season only. Process output can potentially unlock a novelty awareness of the investors toward innovative yield project optimization in the area as it will affect the annual power purchasing influence and production divergence with interest.
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.