Analysis and Implementation of Robust Metaheuristic Algorithm to Extract Essential Parameters of Solar Cell

Arandhakar, Sairaj; Chaudhary, Nalin; Depuru, Shobha Rani; Dubey, Rajesh Kumar; Bhukya, Muralidhar Nayak

doi:10.1109/access.2021.3136209

Cited by 17 publications

(6 citation statements)

References 41 publications

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“…In [22,23], the circuit parameters of the PV cell were found with the Grey Wolf Optimizer and Robust Metaheuristic Algorithm, while in [24] they were found with the Salp Swarm algorithm. Parameter values in the PV cell equivalent circuit model depend on radiation and temperature.…”

Section: Fig 3 Pv Cell Single Diode Equivalent Circuit Modelmentioning

confidence: 99%

Development software program for finding photovoltaic cell open-circuit voltage and fill factor based on the photovoltaic cell one-diode equivalent circuit model

Adak,

Cangi

2024

Electr Eng

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The fill factor is used to determine the quality of electricity generated by the photovoltaic cell. . Open circuit voltage in PV cell is the maximum voltage value that the cell can transmit. The analysis of PV cell fill factor and open circuit voltage was carried out with the developed software program. The PV cell is the smallest building block of the PV solar system and produces voltages between 0.5V and 0.7V. It acts as a current source in the equivalent circuit. The amount of radiation hitting the cell determines how much current it produces. The equivalent circuit of an ideal PV cell consists of a diode and a parallel current source. In order to express losses in applications, series and parallel resistance are added to the ideal equivalent circuit of the PV cell. There are many equivalent circuits in the literature for modeling the equivalent circuit of a PV cell. The single diode equivalent circuit is the most widely used model because of its simplicity and ease of analysis. In this study, Newton-Raphson method was used to find the equivalent circuit parameters of a PV cell. Then, the open circuit voltage and fill factor were found with the software program prepared in Matlab and given in Appendix A. KeywordsPV cell fill factor, PV cell open circuit voltage. Software program. Five unknown parameters. I-V characteristics of PV cell. PV cell equivalent circuit models .

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Section: Fig 3 Pv Cell Single Diode Equivalent Circuit Modelmentioning

confidence: 99%

Development software program for finding photovoltaic cell open-circuit voltage and fill factor based on the photovoltaic cell one-diode equivalent circuit model

Adak,

Cangi

2024

Electr Eng

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“…The solar cell output current equation [31‐33] is:

I_{pv} goodbreak= I_{ph} goodbreak- I_{drs} ((), \exp ([], \frac{((), V_{pv} goodbreak+ normalI R_{s})}{italicaVt}) goodbreak- 1) goodbreak- \frac{((), V_{pv} goodbreak+ normalI R_{s})}{{normalR}_{Rh}} with Vt goodbreak= \frac{KT}{q}

…”

Section: System Modelingmentioning

confidence: 99%

Improved salp swarm algorithm based on particle swarm optimization for maximum power point tracking of optimal photovoltaic systems

Dagal

Akın

Akboy

2022

Intl J of Energy Research

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In this study, an improved salp swarm algorithm based on particle swarm optimization for maximum power point tracking of optimal photovoltaic systems is investigated. The effect of PV partial shading conditions, uniform and fasttracking irradiance, duty cycle, frequency, temperature changes, and load types, and besides some comparative studies of different algorithms are adequately examined for better performance study of the proposed technique. The proposed improved salp swarm algorithm based particle swarm optimization utilizes the PV Solarex-MSX-60 photovoltaic solar panel, which considers voltage and current as inputs based on the proposed algorithm parameters selection. Besides, it uses a buck-boost converter as an interface between input and output. The particle swarm optimization monitors the PV voltage and current, and the salp swarm algorithm does for the duty cycle (particles) in various environmental conditions. The proposed algorithm performs efficiencies 99.99%, 99.63%, and 99.24% comparison with other methods, under uniform irradiance and fast-tracking irradiance respectively. Moreover, the highest power of 316.32 W reached at the duty cycle of 0.6 and 428.6 W at the frequency of 30 kHz under the same partial shading condition with optimal operating temperature values 10 C

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“…The extraction is based on P-V and I-V characteristic data. Sairaj et al, [12] proposed a Tabu search optimization for eliminating the parasitic or unknown parameters from PV modules such as polycrystalline, monocrystalline, and thin film. The Enhanced Slime Mold (ESM) optimization algorithm addresses solar panel modelling and tracking behaviour.…”

Section: Introductionmentioning

confidence: 99%

Efficiency Improvement of Solar Panels Through Parasitic Parameters Extraction and Maximum Power Improvement with Enhanced Slime Mold Optimization Under Partial Shading Conditions

venkateshwarlu¹,

Rao²,

Saleem³

2023

Preprint

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Solar energy offers several environmental, economic, and energy security advantages. Parasitic parameters and shading on solar panels can reduce efficiency. This paper presents a bio-inspired Enhanced Slime Mold (ESM) algorithm search strategy to find the optimal power point by simulating the behaviour of slime molds in a virtual environment. In a solar panel, proposed ESM provides not only for parameter extraction but also serves as Maximum Power Point Tracking (MPPT) during Partial Shading Conditions (PSC). Proposed ESM dynamic behaviour is examined under solar irradiation and various temperature conditions. The effectiveness of proposed technique has been validated by extracting parameters from conventional polycrystalline and monocrystalline modules in the form of a 5S-5P arrangement. In the instance of MPPT operation, the proposed ESM algorithm is compared with Ant Bee Colony and Perturb& Observe (ABC-PO) to determine its efficacy. Moreover, during extraction of unknown parameters of solar cell ESM is compared with existing optimization algorithms such as Artificial Bee Swarm Optimization (ABC SO), Genetic Algorithm (GA), Covariant Matrix (CM), Ant Bee Colony (ABC), and Advanced Particle Swarm Optimization (APSO). In this connection, proposed ESM algorithm is superior to above-mentioned algorithms due to high accuracy, a smaller number of computations, and minimum computational time.

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Analysis and Implementation of Robust Metaheuristic Algorithm to Extract Essential Parameters of Solar Cell

Cited by 17 publications

References 41 publications

Development software program for finding photovoltaic cell open-circuit voltage and fill factor based on the photovoltaic cell one-diode equivalent circuit model

Development software program for finding photovoltaic cell open-circuit voltage and fill factor based on the photovoltaic cell one-diode equivalent circuit model

Improved salp swarm algorithm based on particle swarm optimization for maximum power point tracking of optimal photovoltaic systems

Efficiency Improvement of Solar Panels Through Parasitic Parameters Extraction and Maximum Power Improvement with Enhanced Slime Mold Optimization Under Partial Shading Conditions

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