Solar photovoltaic Maximum Power Point Tracking controller optimization using Grey Wolf Optimizer: A performance comparison between bio-inspired and traditional algorithms

Águila-León, Jesús; Vargas‐Salgado, Carlos; Chiñas-Palacios, Cristian; Díaz-Bello, Dácil

doi:10.1016/j.eswa.2022.118700

Cited by 51 publications

(25 citation statements)

References 64 publications

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“…The drawbacks associated with the methodology include significant computational overhead, increased expenses, and necessitated exploration of the search domain. [10] A pioneering technique, which leverages the Nelder-Mead algorithm introduced. It exhibits superior performance as compared to the bat optimization algorithm, artificial bee colony (ABC), and deterministic PSO regarding success rate and accuracy for all analyzed shading scenarios, as demonstrated using simulation and experimental outcomes.…”

Section: Status Quo Of Mppt Techniquesmentioning

confidence: 99%

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Framework of Maximum Solar Energy Conversion Using Lyapunov‐Based Model Reference Adaptive Control Technique in Stochastic Weather Conditions

Singh,

Akella,

Manna

2023

Energy Tech

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The solar photovoltaic (PV) energy generation technology has grown rapidly. Herein, a novel continuous‐time Lyapunov‐based model reference adaptive control (LB‐MRAC) technique is suggested for determining the duty cycle of boost converter to maintain maximum power point (MPP) of the solar PV panel. For ensuring the fast‐tracking speed, the reference voltage of, respectively, MPP is calculated using perturb and observe (PO) and input to the MRAC technique. Using MATLAB/Simulink, the performances of the LB‐MRAC maximum power point tracking are comparatively analyzed with PO, incremental conductance, and adaptive neuro‐fuzzy inference system under diverse testing modes such as stand‐alone, partial shading, grid integrated, and real time. The proposed technique tracks MPP in just 3.7 ms having tracking efficacy between 99.15% and 99.59% under highly fluctuating irradiance and temperature with load uncertainties. In partial shading mode, four patterns (3 × 1 PV string) are devised and determined where that the suggested approach monitors the global MPP in merely 0.04 s with the highest power tracked and the least amount of shading loss. Next, the efficacy is checked in a three‐phase 50 kW grid‐integrated mode under realistic weather. Finally, the performance of the suggested continuous‐time LB‐MRAC technique is experimentally corroborated employing OPAL‐RT(OP4510) in the real‐time mode.

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Section: Status Quo Of Mppt Techniquesmentioning

confidence: 99%

“…The drawbacks associated with the methodology include significant computational overhead, increased expenses, and necessitated exploration of the search domain. [ 10 ]…”

Section: Introductionmentioning

confidence: 99%

Framework of Maximum Solar Energy Conversion Using Lyapunov‐Based Model Reference Adaptive Control Technique in Stochastic Weather Conditions

Singh,

Akella,

Manna

2023

Energy Tech

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“…That is why this study has suggested GWO-type MPPT approaches. Aguila- Leon et al (2023) propose a grey wolf optimization-based optimized MPPT as a substitute for the conventional methods where grey wolf optimizer, wolf optimizer, simulated annealing, and particle swarm optimization algorithms have been used to examine the reaction time. The incremental conductance (IC) and perturb and observe (P&O) metaheuristic algorithms are contrasted with these four metaheuristic algorithms.…”

Section: Introductionmentioning

confidence: 99%

“…Bio-inspired (BI), artificial intelligence (AI), and soft computing methods (Salam et al, 2013) are more sophisticated than traditional ones and provide better tracking results. Advanced MPPT grey wolf optimization (GWO; Aguila-Leon et al, 2023; a special type of bio-inspired methods) methods have recently drawn considerable attention due to its capacity to identify nearly optimal solutions to challenging optimization problems like multimodal objective functions. These algorithms often have an easy search strategy and great optimization effectiveness.…”

Section: Introductionmentioning

confidence: 99%

Sustainable solar energy potential on marine passenger ships of Bay of Bengal: A way of reducing carbon dioxide emissions and disaster risk reduction

Abdullah-Al-Mahbub,

Towfiqul Islam,

Alam

et al. 2023

Energy Exploration & Exploitation

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In Bangladesh, there are roughly 31 marine passenger ships that are in operation. These ships might be a good location for solar photovoltaic (PV) plants since solar energy is the best renewable energy to replace the fossil fuel used in the ships. A “tower rounded flower-shaped solar PV” system of PV panel arrangement—just looks like a “sunflower,” is proposed in this research. To harness maximum power, solar towers are designed in such a way that they may be freely rotated on their vertical axes and that the tilt angles of their solar panels can be adjusted from 0° to 50° on their horizontal axes freely. The “tower rounded flower-shaped solar PV” architecture of the PV array atop a maritime vessel is presented in this research along with a unique method for calculating the PV system's anticipated energy production. Finally calculated the realistic CO2 emission reduction by using this approach for a sustainable future. Applying globalsolaratlas (for horizon and sun's path estimation); PVsyst 7.2, HOMER Pro, and NREL's PVWatt calculator (for solar radiation calculation); vesselfinder (for the number of vessels analysis); shiptraffic (for vessels path analysis), this research suggests that marine passenger vessels are one of the best places to construct a proposed “tower rounded flower-shaped solar PV” power plant. According to estimates, 17 passenger ships can produce roughly 1240 MW of electricity per year and may save approximately 325.56 tons of CO2 gas emissions annually to the environment per year as compared to using fossil fuel-based power plants to produce electricity.

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“…Mirjalili et al were inspired by grey wolf predation and proposed an intelligent optimization algorithm in 2014, which was named GWO. GWO has been widely applied in various fields [8][9][10][11][12] including feature selection. The GWO algorithm has the advantages of a simple structure, few parameters to be adjusted, and easy implementation.…”

Section: Introductionmentioning

confidence: 99%

Binary grey wolf optimizer with a novel population adaptation strategy for feature selection

Wang

et al. 2023

IET Control Theory & Appl

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Feature selection is a fundamental pre‐processing step in machine learning that aims to reduce the dimensionality of a dataset by selecting the most effective features from the original features. This process is regarded as a combinatorial optimization problem, and the grey wolf optimizer (GWO), a novel meta‐heuristic algorithm, has gained popularity in feature selection due to its fast convergence speed and easy implementation. In this paper, an improved binary GWO algorithm incorporating a novel Population Adaptation strategy called PA‐BGWO is proposed. The PA‐BGWO takes into account the characteristics of the feature selection problem and designs three strategies. The proposed strategy includes an adaptive individual update procedure to enhance the exploitation ability and accelerate convergence speed, a head wolf fine‐tuned mechanism to exert the impact on each independent feature of the objective function, and a filter‐based method ReliefF for calculating feature weights with dynamically adjusted mutation probabilities based on the ranking features to effectively escape from local optima. Experimental comparisons with several state‐of‐the‐art feature selection methods on 15 classification problems demonstrate that the proposed approach can select a small feature subset with higher classification accuracy in most cases.

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Solar photovoltaic Maximum Power Point Tracking controller optimization using Grey Wolf Optimizer: A performance comparison between bio-inspired and traditional algorithms

Cited by 51 publications

References 64 publications

Framework of Maximum Solar Energy Conversion Using Lyapunov‐Based Model Reference Adaptive Control Technique in Stochastic Weather Conditions

Framework of Maximum Solar Energy Conversion Using Lyapunov‐Based Model Reference Adaptive Control Technique in Stochastic Weather Conditions

Sustainable solar energy potential on marine passenger ships of Bay of Bengal: A way of reducing carbon dioxide emissions and disaster risk reduction

Binary grey wolf optimizer with a novel population adaptation strategy for feature selection

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