Solar energy is becoming the mainstream energy source by drawing considerable attention of analysts these days. The output power of a photovoltaic (PV) system fluctuates with temperature and sunlight, affecting its ef...
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Solar energy is becoming the mainstream energy source by drawing considerable attention of analysts these days. The output power of a photovoltaic (PV) system fluctuates with temperature and sunlight, affecting its efficiency. To extract accessible power by a PV system, Maximum Power Point Tracking (MPPT) method is adopted. A famous strategy regularly utilized due to its simplicity and low cost is the perturb and observe (PO) algorithm. However, there are a few downsides with PO algorithm, which result in power loss and low efficiency. We compared the performance of the conventional PO with some enhancements, especially a recent PO variant, for MPPT. Experiments were conducted at different irradiances and temperature levels in two ways, namely with load and with battery, by conventional PO and its variants. The strategy to reach optima and stability of the methods were discussed. The PO variants were rated from the viewpoints of stability, accuracy, post-MPP oscillations, and tracking speed. The modifications were proven to be fruitful for the practitioners working with MPPT in PV solar systems using PO algorithms. Simulation results were validated using real-time experimental results. The new PO variant appeared to be a reliable computing algorithm for MPPT in solar PV systems. (C) 2019 Sharif University of Technology. All rights reserved.
Sluggish tracking for change in solar irradiations is the main demerit of the perturb and observe (P&O) algorithm because of its fixed perturb. To overcome this, an adaptive tracking algorithm based on Takagi-Suge...
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Sluggish tracking for change in solar irradiations is the main demerit of the perturb and observe (P&O) algorithm because of its fixed perturb. To overcome this, an adaptive tracking algorithm based on Takagi-Sugeno fuzzy implications is proposed in this study. Input to the fuzzy controller is the error between conductance and incremental conductance which is otherwise zero at the maximum power point. The P&O algorithm and the proposed algorithm along with the recently published adaptive incremental conductance algorithm are examined for their performance efficacy on a photovoltaic (PV) generating system with fabricated as well as real irradiation data. As a case study, all the considered algorithms are validated under partial shading conditions also. The effectiveness of the proposed algorithm is verified for the tracking of the maximum power point of a PV system in steady as well as changing irradiations and the conclusions are supported through some experimental validations.
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