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Go to Editorial ManagerMaximum 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.
In the present work the effect of Corrosion & Scale Inhibitor was evaluated by using of the commercial product (Kurita S2050) that mainly containing of (Na2HPO4) sodium phosphate as corrosion inhibitor and (C6H11NaO7) sodium glocunate as scale inhibitor & dispersant. The dosing rate of this chemical was controlled according to the treatment system depend mainly on the monitoring of LI & RI indexes for (30) days treatment in the cooling tower unit of Al-Dora Oil refinery-Baghdad. The corrosion rate and the corrosion inhibitors efficiency were calculated by measurement of weight loss in standard test coupon (AISI 1010). After 30 day of the Field Test, the result show that the treatment program performance was effective in the corrosion & scale inhibition through an acceptable corrosion rate less than 0.018 in gmd. Also the result of corrosion rate was analyzed statistically by using of (ANN) to formulate a prediction equation to corrosion rate identification.
The oil industry has a direct impact on the economic feasibility of other sectors and is considered to be the most important energy source used to turn the wheels of other industries. Therefore, it was necessary to pay attention and continuously develop this industry, to find the best modern techniques for designing, pre-commissioning and controlling process, to improve efficiency, preserve energy and achieve the highest production of costly components with the highest purity of the product. This study aims to provide a literary analysis of the stages of development and progress of the dynamics and control of the petroleum industry, in particular the distillation column, because it is multivariable with high interaction between control cycles, nonlinear behaviour and large gains. Control processes have undergone many developments and modernizations to achieve the best results. Various control methods have been used, ranging from simple proportional-integral-derivative controller (PID) to advanced control strategies such as model predictive control (MPC), multivariate model predictive control (MMPC), fuzzy logic control (FLC), quadratic dynamic matrix control (QDMC), artificial neural network control (ANN) and other advanced control techniques. The authors concluded from the review that the advanced control strategies superior than the conventional methods.