A Novel Nature-Inspired Maximum Power Point Tracking (MPPT) Controller Based on SSA-GWO Algorithm for Partially Shaded Photovoltaic Systems

Wan, Yihao; Mao, Mingxuan; Zhou, Lin; Zhang, Qianjin; Xi, Xinze; Zheng, Chen

doi:10.3390/electronics8060680

Cited by 45 publications

(29 citation statements)

References 31 publications

(18 reference statements)

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“…The GWO algorithm is used in PV generation system for the first time in [31]. The MPPT controller is achieved by combining SSA with GWO [32]. The leader structure of the GWO algorithm is introduced into the basic SSA algorithm to enhance the global search capability.…”

Section: Introductionmentioning

confidence: 99%

An Improved Gray Wolf Optimizer MPPT Algorithm for PV System With BFBIC Converter Under Partial Shading

et al. 2020

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Based on the boost full bridge isolated converter (BFBIC) topology and considering the sudden changes in the external environment, a global maximum power point tracking (GMPPT) control strategy based on an improved gray wolf optimizer (IGWO) algorithm is proposed in this paper. In the strategy, a nonlinear tangent trigonometric function as a convergence factor is integrated into the gray wolf optimizer (GWO) algorithm. In addition, the active-clamp circuit and phase-shift are used to implement the soft switch technology for BFBIC converter in photovoltage (PV) system. Finally, the maximum power point tracking (MPPT) performance on PV system with the proposed IGWO algorithm under static and dynamic partial shading conditions (PSCs) was investigated and compared with other common perturb and observe(P&O), particle swarm optimization (PSO), artificial bee colony (ABC), adapt inertia weight salp swarm algorithm (WSSA), salp swarm algorithm with grey wolf optimizer (SSA-GWO), SSA with PSO (SSA-PSO), enhanced GWO (EGWO) MPPT algorithms. The effectiveness and stability of the proposed control strategy are validated, especially tracking speed under PSCs. Simulation results show that the BFBIC topology with the proposed IGWO algorithm outperforms other algorithms on most cases, especially only takes the tracking time of 0.24s and reaches the efficiency of 98.54% under the most severe PSCs. INDEX TERMS Boost full bridge isolated converter (BFBIC), improved grey wolf optimizer (IGWO), global maximum power point tracking (GMPPT), partial shading conditions (PSCs)

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Section: Introductionmentioning

confidence: 99%

An Improved Gray Wolf Optimizer MPPT Algorithm for PV System With BFBIC Converter Under Partial Shading

et al. 2020

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“…The P&O algorithm is a widely used technique used for PV-MPPT due to its simple implementation and low cost-however, it does face various issues, such as a slow tracking speed, high fluctuation and drift issues associated with fast changing irradiation [10,11]. Consequently, the IC-MPPT is designed to overcome the limitations of the P&O algorithm.…”

Section: Introductionmentioning

confidence: 99%

Design of an Efficient Maximum Power Point Tracker Based on ANFIS Using an Experimental Photovoltaic System Data

2019

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Maximum power point tracking (MPPT) techniques are a fundamental part in photovoltaic system design for increasing the generated output power of a photovoltaic array. Whilst varying techniques have been proposed, the adaptive neural-fuzzy inference system (ANFIS) is the most powerful method for an MPPT because of its fast response and less oscillation. However, accurate training data are a big challenge for designing an efficient ANFIS-MPPT. In this paper, an ANFIS-MPPT method based on a large experimental training data is designed to avoid the system from experiencing a high training error. Those data are collected throughout the whole of 2018 from experimental tests of a photovoltaic array installed at Brunel University, London, United Kingdom. Normally, data from experimental tests include errors and therefore are analyzed using a curve fitting technique to optimize the tuning of ANFIS model. To evaluate the performance, the proposed ANFIS-MPPT method is simulated using a MATLAB/Simulink model for a photovoltaic system. A real measurement test of a semi-cloudy day is used to calculate the average efficiency of the proposed method under varying climatic conditions. The results reveal that the proposed method accurately tracks the optimized maximum power point whilst achieving efficiencies of more than 99.3%.

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“…They compare the results in terms of time convergence and maximum power of the PVs obtained for one consecrated method P&O, and three algorithms PSO, SSA, and SSA-GWO. The consecrated method P&O gives better results for the uniform irradiance case from the time convergence point of view (0.48 s) than PSO (0.72 s) and SSA (0.58 s) algorithms, but not for SSA-GWO (0.46 s) algorithm [109]. The maximum power determined through P&O is the lowest one due to the oscillations.…”

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confidence: 96%

“…Mirjalili et al proposed the salp swarm algorithm (SSA) which uses a control parameter and assures the convergence through the adaptive mechanism [108]. Wan et al improved the performance of the SSA algorithm using the grey wolf optimization algorithm in order to provide a better leader structure but which keeps the adaptive mechanism [109]. They compare the results in terms of time convergence and maximum power of the PVs obtained for one consecrated method P&O, and three algorithms PSO, SSA, and SSA-GWO.…”

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confidence: 99%

“…In the case of one pattern with three local maximum points, the P&O determined the global maximum very fast in comparison with the other three ones, but the accuracy is the lowest. Thus, the time for the P&O is 0.15 while for SSA-GWO it is 0.53 s, but the P max is 34.64 W for P&O and 44.55 W for SSA-GWO [109]. By using bioinspired algorithms or the hybrid algorithms, the power fluctuations are reduced, the global maximum power point is rapidly but accurately determined, and they can be successfully used for partial shading and for rapid changes in irradiance.…”

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Multiconcept Methods to Enhance Photovoltaic System Efficiency

Cotfas

2019

International Journal of Photoenergy

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The main goal of this paper is to review the most important methods previously developed to enhance the efficiency and increase the lifetime of photovoltaic panels. The methods to increase the solar radiation incident on photovoltaic panels, as well as the cooling and the maximum power point tracker methods, are concisely presented in this paper. The pros and cons analysis reveals that the methods to enhance the power generated by the photovoltaic panels are strongly dependent on geographical location, climatic conditions, and the materials used. This review paper is also of interest for engineers who attempt to identify the most adequate solutions to maximize the energy output of photovoltaic systems for each location.

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A Novel Nature-Inspired Maximum Power Point Tracking (MPPT) Controller Based on SSA-GWO Algorithm for Partially Shaded Photovoltaic Systems

Cited by 45 publications

References 31 publications

An Improved Gray Wolf Optimizer MPPT Algorithm for PV System With BFBIC Converter Under Partial Shading

An Improved Gray Wolf Optimizer MPPT Algorithm for PV System With BFBIC Converter Under Partial Shading

Design of an Efficient Maximum Power Point Tracker Based on ANFIS Using an Experimental Photovoltaic System Data

Multiconcept Methods to Enhance Photovoltaic System Efficiency

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