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Since the beginning of the war in Syria, most of the electricity infrastructure has been destroyed, leaving millions with unreliable energy. Syrians have encountered high electricity production costs and environmental damage costs resulting from the utilization of fossil fuels. Similarly, Syria has abundant solar energy can be exploited to meet its electrical power needs. However, because of a lack of expertise in solar energy conversion and the high cost of smart technology, Syrians have typically used photovoltaic systems in primitive ways, in which the efficiency of solar energy conversion is low. There is, therefore, a need for inexpensive, easy-to-implement, yet highly efficient and high performing solutions. Using the STMicroelectronics 32-bit ARM as a maximum power point tracking (MPPT) controller offers a potential solution to the problem of low conversion efficiency in standalone solar systems. In this study, using Matlab-Simulink and STMicrelectronics-32 bit ARM board, simulation and practical test is set up to evaluate the performance of the Perturbation & Observation, Incremental Conductance and Fuzzy Logic MPPT algorithms, in order to determine the most appropriate algorithm to use in small scale solar energy systems. Therefore, one main objective of this study is to explore rapid control prototyping tools for saving time and effort to the experts in the implementation process of the proposed systems. The results indicate the effectiveness of Fuzzy logic algorithm to draw more energy, decrease oscillation and provide a fast response under variable weather conditions. Furthermore, the three algorithms were able to find and track MPP. |
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