A Forensic-Based Investigation Algorithm for Parameter Extraction of Solar Cell Models
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TLDR
In this article, a new application of the Forensic-Based Investigation Algorithm (FBIA), which is a new meta-heuristic optimization technique, is introduced to accurately extract the electrical parameters of different PV models.Abstract:
The accurate parameter extraction of photovoltaic (PV) module is pivotal for determining and optimizing the energy output of PV systems into electric power networks. Consequently, a Photovoltaic Single-Diode Model (PVSDM), Double Diode Model (PVDDM), and Triple- Diode Model (PVTDM) is demonstrated to consider the PV losses. This article introduces a new application of the Forensic-Based Investigation Algorithm (FBIA), which is a new meta-heuristic optimization technique, to accurately extract the electrical parameters of different PV models. The FBIA is inspired by the suspect investigation, location, and pursuit processes that are used by police officers. The FBIA has two phases, which are the investigation phase applying by the investigators team, and the pursuit phase employing by the police agents team. The validity of the FBIA for PVSDM, PVDDM, and PVTDM is commonly considered by the numerical analysis executing under diverse values of solar irradiations and temperatures. The optimal five, seven, and nine parameters of PVSDM, PVDDM, and PVTDM, respectively, are accomplished using the FBIA and compared with those manifested by various optimization techniques. The numerical results are compared for the marketable Photowatt-PWP 201 polycrystalline and Kyocera KC200GT modules. The efficacy of the FBIA for the three models is properly carried out checking its standard deviation error with that obtained from various recently proposed optimization techniques in 2020 which are Jellyfish search (JFS) optimizer, Manta Ray Foraging optimizer (MRFO), Marine Predators Algorithm(MPA), Equilibrium Optimizer (EO), Heap Based Optimizer (HBO). The standard deviations of the fitness values over 30 runs are developed to be less than $1 \times 10^{-6}$ for the three models, which make the FBIA results are extremely consistent. Therefore, FBIA is foreseen to be a competitive technique for PV module parameter extraction.read more
Citations
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Journal ArticleDOI
Identification of Solar Photovoltaic Model Parameters Using an Improved Gradient-Based Optimization Algorithm With Chaotic Drifts
M. Premkumar,Pradeep Jangir,C. Ramakrishnan,G. Nalinipriya,Hassan Haes Alhelou,B. Santhosh Kumar +5 more
TL;DR: In this article, the Chaotic-GBO (CGBO) algorithm is proposed to derive the parameters of PV modules while offering precise I-V and P-V curves.
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Estimating Parameters of Photovoltaic Models Using Accurate Turbulent Flow of Water Optimizer
Mokhtar Said,Abdullah M. Shaheen,Ahmed R. Ginidi,Ragab A. El-Sehiemy,Karar Mahmoud,Matti Lehtonen,Mohamed M. F. Darwish +6 more
TL;DR: The findings show a high closeness between the estimated power–voltage (P–V) and current–voltages (I-V) curves achieved by the proposed TFWO compared with the experimental data as well as the competitive optimization algorithms, thanks to the effectiveness of the developed T FWO solution mechanism.
Journal ArticleDOI
Gorilla Troops Optimizer for Electrically Based Single and Double-Diode Models of Solar Photovoltaic Systems
Ahmed R. Ginidi,Sherif M. Ghoneim,Abdallah M. Elsayed,Ragab A. El-Sehiemy,Abdullah M. Shaheen,Attia A. El-Fergany +5 more
TL;DR: A new implementation of the Gorilla Troops Optimization (GTO) technique for parameter extraction of several PV models is created and its efficacy and superiority are expressed by calculating the standard deviations of the fitness values, which indicates that the SD and DD models are smaller than 1E−16, and 1E −6, respectively.
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Assessment of an Improved Three-Diode against Modified Two-Diode Patterns of MCS Solar Cells Associated with Soft Parameter Estimation Paradigms
TL;DR: The simulation results show that the MTDM gives more accurate solutions as a model to the MCSSC compared with the results reported in the literature, and the EHO outperforms CLPSO in terms of the solution quality and convergence rates.
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A reliable approach for modeling the photovoltaic system under partial shading conditions using three diode model and hybrid marine predators-slime mould algorithm
TL;DR: In this article, a hybrid algorithm of the marine predator's algorithm (MPA) and slime mould algorithm (SMA) is proposed to enhance the MPA exploitation phase while identifying the triple diode model parameters.
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