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New Solar MPPT Control Technique Based on Incremental Conductance and Multi-Objective Genetic Algorithm Optimization

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Solar energy is highly dependent on climatic conditions and swings sporadically, making photovoltaic integration into power systems difficult. In order to improve the design of power infrastructure and the successful deployment of decentralized and renewable energy sources, a new paradigm for the energy supply chain is established, leading to the creation of microgrids. Intelligence should be introduced at all levels of the grid, and it should act over a long period. This article introduces new research tools and methodologies to help utility engineers better understand the grid's potential impact from these new power sources. Therefore, this research proposes a novel PV solar system control method. The strategy is an innovative Maximum Power Point Tracking (MPPT) technology for solar systems. Designing an effective controller capable of lowering Power Stress inside the PV System is critical in this respect. In this research, the Proportional Integral (PI) controller has been utilized in conjunction with a heuristic technique termed Genetic Algorithm (GA) in order to regulate and stabilize the MPP of the power supplied by the PV system. Then the GA technique has been utilized to identify the ideal settings, based on the four performance indices of Integrated Squared Error (ISE), Integrated Absolute Error (IAE), Integrated Time Absolute Error (ITAE), and Integrated Time Squared Error (ITSE) (Kp, Ki). The simulation results show that the PV system can successfully monitor the required MPP.
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Solar Energy; MPPT Technique; PI Controller; GA Optimization

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