<![CDATA[Solar energy is naturally available from sun, and it can be extracted by using a photovoltaic (PV) cell. However, solar energy extraction entirely depends on the climatic conditions and angle of rays falling on PV cells. Hence, maximum powerpoint tracking (MPPT) is considered in most areas under variable climatic conditions, which acts as a controller unit for PV cells. MPPT can enhance the efficiency of PV cells. However, designing an MPPT model is challenging as different uncertainties in the climatic condition may lead to more fluctuations in voltage and current in PV cells. Under the shaded condition, the PV cell may have other MPPT points that lead to the PV cell’s low efficiency in analyzing maximum power. Hence, this paper introduces a cost-effective and optimized system for the PV model that can find optimal power and improve PV cells’ efficiency. The proposed system achieves better computational performance with ~35% and ~42% than existing MPPT techniques. The improved particle swarm optimization (PSO) is smoother due to the enhanced form of MPP tracking. Hence, improved PSO takes 0.038 sec while the existing PSO technique takes 0.045 sec to obtain the MPP tracking.]]>
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