In solar photovoltaic system, tracking the maximum power point (MPP) is challenging task due to varying climatic conditions. Moreover, the tracking algorithm becomes more complicated under the condition of partial sha...
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In solar photovoltaic system, tracking the maximum power point (MPP) is challenging task due to varying climatic conditions. Moreover, the tracking algorithm becomes more complicated under the condition of partial shading due to the presence of multiple peaks in the power voltage characteristics. This paper introduces a novel method to track the global maximum power point under partially shaded conditions. The method combines an artificial neural network controller with a scanning algorithm. The PV system along with the proposed MPPT algorithm was simulated using Matlab/Simulink environment. The simulated system was evaluated under uniform and non-uniform irradiation conditions. For comparison, an improved variable step P&O with global scanning (PO&GS) and incremental conductance controller based on a fuzzy duty cycle change estimator (FLE) with direct control were used and the results show that the proposed approach is effective in tracking the MPP and presents fast response time.
The aim of this work is to study the efficient energy utilization of stand-alone photovoltaic (PV) system under rapid changes in load. The PV system conceived included a typical MSX60 photovoltaic panel feeding a line...
The aim of this work is to study the efficient energy utilization of stand-alone photovoltaic (PV) system under rapid changes in load. The PV system conceived included a typical MSX60 photovoltaic panel feeding a linear load. This panel provided, under standard test conditions (STC), a maximum power of 60 W, an optimal current of 3.55 A and an optimal voltage of 17 V. The PV system include also a DC/DC boost converter operating at 100 KHz and where the MOSFET transistor is controlled by a new simple maximum power point tracking (MPPT) command based on detection of maximum power point (MPP) and optimal duty cycle. The PV system model, including the effects of sudden changes in load is developed and simulated in MATLAB/Simulink environment. The obtained simulation results show that the PV system converges for less than 10 ms towards the optimal conditions independently of the rapid changes in load. The results show also that the boost converter efficiency is very satisfactory. Its value is of the order of 96%. Furthermore, the proposed MPPT algorithm improves the performances and efficiency of the PV system significantly. The MPPT efficiency is about 99.7% irrespective to the rapid changes of load that can happen at any time. So, this new developed command can ensure better exploitation of solar energy under load variations.
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