Squirrel search algorithm applied to effective estimation of solar PV model parameters: a real-world practice

Maden, Dincer; Çelik, Emre; Houssein, Essam H.

doi:10.1007/s00521-023-08451-x

Cited by 19 publications

(2 citation statements)

References 39 publications

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“…According to the experimental results, the lowest error value was obtained with the HHO, thus proving its superiority in solving this problem. Maden et al [50] conducted a study on the estimation of parameters of photovoltaic cells. In this study, the values of single diode and double diode parameters were obtained by using the squirrel search algorithm (SSA).…”

Section: Related Workmentioning

confidence: 99%

I-CPA: An Improved Carnivorous Plant Algorithm for Solar Photovoltaic Parameter Identification Problem

Beşkirli,

Dağ

2023

Biomimetics

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The carnivorous plant algorithm (CPA), which was recently proposed for solving optimization problems, is a population-based optimization algorithm inspired by plants. In this study, the exploitation phase of the CPA was improved with the teaching factor strategy in order to achieve a balance between the exploration and exploitation capabilities of CPA, minimize getting stuck in local minima, and produce more stable results. The improved CPA is called the I-CPA. To test the performance of the proposed I-CPA, it was applied to CEC2017 functions. In addition, the proposed I-CPA was applied to the problem of identifying the optimum parameter values of various solar photovoltaic modules, which is one of the real-world optimization problems. According to the experimental results, the best value of the root mean square error (RMSE) ratio between the standard data and simulation data was obtained with the I-CPA method. The Friedman mean rank statistical analyses were also performed for both problems. As a result of the analyses, it was observed that the I-CPA produced statistically significant results compared to some classical and modern metaheuristics. Thus, it can be said that the proposed I-CPA achieves successful and competitive results in identifying the parameters of solar photovoltaic modules.

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Section: Related Workmentioning

confidence: 99%

I-CPA: An Improved Carnivorous Plant Algorithm for Solar Photovoltaic Parameter Identification Problem

Beşkirli,

Dağ

2023

Biomimetics

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“… Year Algorithm OF Modelling Contributions References 2023 Improved moth flame algorithm RMSE SDM; DDM This study improved the moth flame algorithm using local escape operators to enhance its exploration operator and population diversity. This algorithm could achieve outstanding outcomes in comparison to some algorithms, but it required a huge number of function evaluations, up to 125,000 32 2023 Hybrid grey wolf optimization RMSE DDM This study combined the analytical technique and grey wolf algorithm to present a strong variant for tackling this problem 33 2023 Chaos game optimization algorithm RMSE SDM; DDM; TDM In this study, the Chaos game optimization is combined with the least squares (LS) estimator to aid in accelerating the convergence speed and achieving better outcomes 34 2023 Squirrel search algorithm RMSE SDM; DDM This study adapted the squirrel search algorithm for estimating the unknown parameters of SDM and DDM by minimizing the root mean squared error between the measured and estimated data 35 2023 Growth Optimizer RMSE SDM; DDM The growth optimizer was developed to find the unknown parameters for two different PV modules, namely KKC and RTC. This algorithm consumed a huge number of function evaluations for solving this problem 36 2023 L-SHADE RMSE SDM In this study, a parameter decomposition technique was used to alleviate this problem's complexity.…”

Section: Introductionmentioning

confidence: 99%

Novel hybrid kepler optimization algorithm for parameter estimation of photovoltaic modules

Mohamed,

Abdel-Basset,

Sallam

et al. 2024

Sci Rep

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The parameter identification problem of photovoltaic (PV) models is classified as a complex nonlinear optimization problem that cannot be accurately solved by traditional techniques. Therefore, metaheuristic algorithms have been recently used to solve this problem due to their potential to approximate the optimal solution for several complicated optimization problems. Despite that, the existing metaheuristic algorithms still suffer from sluggish convergence rates and stagnation in local optima when applied to tackle this problem. Therefore, this study presents a new parameter estimation technique, namely HKOA, based on integrating the recently published Kepler optimization algorithm (KOA) with the ranking-based update and exploitation improvement mechanisms to accurately estimate the unknown parameters of the third-, single-, and double-diode models. The former mechanism aims at promoting the KOA’s exploration operator to diminish getting stuck in local optima, while the latter mechanism is used to strengthen its exploitation operator to faster converge to the approximate solution. Both KOA and HKOA are validated using the RTC France solar cell and five PV modules, including Photowatt-PWP201, Ultra 85-P, Ultra 85-P, STP6-120/36, and STM6-40/36, to show their efficiency and stability. In addition, they are extensively compared to several optimization techniques to show their effectiveness. According to the experimental findings, HKOA is a strong alternative method for estimating the unknown parameters of PV models because it can yield substantially different and superior findings for the third-, single-, and double-diode models.

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Parameters Estimation of Photovoltaic Solar Cell Using a Stochastic Optimization Approach

Djeblahi,

Mahdad,

Srairi

et al. 2024

Lecture Notes in Networks and Systems

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Squirrel search algorithm applied to effective estimation of solar PV model parameters: a real-world practice

Cited by 19 publications

References 39 publications

I-CPA: An Improved Carnivorous Plant Algorithm for Solar Photovoltaic Parameter Identification Problem

I-CPA: An Improved Carnivorous Plant Algorithm for Solar Photovoltaic Parameter Identification Problem

Novel hybrid kepler optimization algorithm for parameter estimation of photovoltaic modules

Parameters Estimation of Photovoltaic Solar Cell Using a Stochastic Optimization Approach

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