2021
DOI: 10.35833/mpce.2019.000086
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Optimized Fuzzy Controller for MPPT of Grid-connected PV Systems in Rapidly Changing Atmospheric Conditions

Abstract: Due to nonlinear behavior of power production of photovoltaic (PV) systems, it is necessary to apply the maximum power point tracking (MPPT) techniques to generate the maximum power. The conventional MPPT methods do not function properly in rapidly changing atmospheric conditions. In this study, a fuzzy logic controller (FLC) optimized by a combination of particle swarm optimization (PSO) and genetic algorithm (GA) is proposed to obtain the maximum power point (MPP). The proposed FLC uses the ratio of power va… Show more

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Cited by 85 publications
(61 citation statements)
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“…The fractional order controller (PID (λδ)) is the same as the traditional PID controller, but the only difference is the fractional derivative order (δ) and integral order (λ). The FoPID controller transfer function [19] illustration is given by,…”
Section: Fopid Controllermentioning
confidence: 99%
See 1 more Smart Citation
“…The fractional order controller (PID (λδ)) is the same as the traditional PID controller, but the only difference is the fractional derivative order (δ) and integral order (λ). The FoPID controller transfer function [19] illustration is given by,…”
Section: Fopid Controllermentioning
confidence: 99%
“…Swati Singh et al (2020) represented that review of optimization and modeling methodologies, as well as the interface mechanism of various renewable energy sources with various control designs such as the Fuzzy Controller, Fractional Order FPID (Fuzzy PID) Controller, and FOPID (Fractional Order PID) Controller. Majid Dehghani et al (2021) presented that to achieve the full PowerPoint; a fuzzy logic controller (FLC) was optimized by a combination of particle swarm optimization (PSO) and genetic algorithm (GA).…”
Section: Introductionmentioning
confidence: 99%
“…Moreover, it is difficult to select a proper perturbation step considering the trade-off between convergence time and oscillation [8] . Under some rapidly changing atmospheric conditions, it is well known that the P&O algorithm can face difficulty during such time intervals [10] . Regarding these problems with P&O, the incremental conductance (INC) algorithm was introduced in Ref.…”
mentioning
confidence: 99%
“…If the derivative is equal to zero, the power point is at the MPP; otherwise, it is at the left side of the MPP when the derivative is positive and at the right side when the derivative is negative. Hence, the INC algorithm is superior to P&O when determining the best direction of perturbation and identifying whether the MPP has been reached [10][11][12] . However, similar to P&O, there is a tradeoff between convergence time and oscillation when choosing the increment (step) size.…”
mentioning
confidence: 99%
“…A fuzzy logic MPPT optimized by a combination of PSO and GA is presented in [35]. The range of changes in fuzzy membership functions and fuzzy rules are proposed as an optimization problem solved by using PSO-GA.…”
mentioning
confidence: 99%