Abstract
Solar Photovoltaic (PV) systems have become prominent and have attained the attention of energy engineers, governments and researchers. To achieve the maximum benefit from the PV system in spite of its nonlinear characteristic and environmental conditions, finding a robust maximum power point tracking method is essential. Over two decades, various researchers proposed numerous MPPT methods, but they failed to evaluate their methods on consistency, reliability, and robustness over several numbers of runs. Most of the researchers examined one configuration and they did not to consider the dynamic change in the irradiation conditions. Therefore, in this manuscript, the authors introduced a novel optimization technique Fractional chaotic Flower Pollination Algorithm (FC-FPA), by merging fractional chaos maps with flower pollination algorithm (FPA). The proposed technique, help FPA in extracting the Global Maximum Power Point (GMPP) under different partial shading patterns including with different PV array configurations. The proposed FC-FPA technique is tested and evaluated over 5 different patterns of partial shading conditions. The first three patterns are tested over 4S configuration made with Shell S36 PV module. The other two patterns are applied to the 4S2P configuration of Shell SM55 PV panels. The performance of the proposed variant is investigated by tracking the GMPP for abruptly changing shade pattern. Exclusive statistical analysis is performed over several numbers of runs. Comparison with perturb and observe MPPT technique is established. These results confirm that, the proposed method shows fast convergence, zero oscillation and rapid response for the dynamic change in irradiation with consistent behavior.
Highlights
The development of renewable energy resources have been drastically increases due to the effect of greenhouse gases, depletion of fossil fuels and high demand of electricity [1]
The converging speed for transients is improved and oscillations around the maximum power point (MPP) are completely eliminated compared with conventional maximum power point tracking (MPPT) methods, Single pattern is used solar PV module of MSX-60W, Proposed method is compared with these two algorithms perturbation and observation (P&O), FLC-hill climbing (HC)
Three fractional chaotic (Logistic, Sine, Tent) have been merged with the basic version of flower pollination algorithm (FPA) to enhance the superiority of FPA
Summary
The development of renewable energy resources have been drastically increases due to the effect of greenhouse gases, depletion of fossil fuels and high demand of electricity [1]. For the evolutionary algorithm (EA) based MPPT techniques, the commonly noticeable drawbacks are the trade-off between exploration-exploitation which is very less, which results in fluctuations during the process of optimization These methods may fall in LMPP during wider (strong) shading conditions. In this article, authors proposed a new and unique technique of introducing chaotic variants to achieve the GMPP irrespective of environmental conditions, type of PV module, uniform and dynamic change in irradiation conditions. The converging speed for transients is improved and oscillations around the MPPs are completely eliminated compared with conventional MPPT methods, Single pattern is used solar PV module of MSX-60W, Proposed method is compared with these two algorithms P&O, FLC-HC.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
