Chaos Induced Coyote Algorithm (CICA) for Extracting the Parameters in a Single, Double, and Three Diode Model of a Mono-Crystalline, Polycrystalline, and a Thin-Film Solar PV Cell

Khan, Shoeb Ahmad; Ahmad, Shafiq; Sarwar, Adil; Tariq, Mohd; Ahmad, Javed; Asim, Mohammed; Soliman, Ahmed T.; Ma, Hossain

doi:10.3390/electronics10172094

Cited by 7 publications

(1 citation statement)

References 67 publications

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“…Crystalline solar cells, polycrystalline modules, and amorphous modules were all tested with this method to ensure their reliability at varying temperatures and amounts of sunlight. In (Khan et al, 2021), SA Khan et al used the Chaos Induced Coyote Algorithm (CICA) to determine previously unknown parameters for the thin-film RTC France, monocrystalline, and polycrystalline solar cell single-, double-, and three-diode models. The introduction of disorder during population expansion is a conceptual influence for this method.…”

Section: Introductionmentioning

confidence: 99%

Archimedes optimization algorithm based parameter extraction of photovoltaic models on a decent basis for novel accurate RMSE calculation

Hussain,

Hussan,

Tariq

et al. 2024

Front. Energy Res.

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Solar photovoltaic (PV) technology stands as a promising alternative to conventional fossil fuel-based power generation, offering pollution-free and low-maintenance energy production. To harness its potential effectively, understanding the power generation process and accurately modeling solar PV systems are essential. Unfortunately, manufacturers often do not provide the necessary parameters for modeling solar cells, making it challenging for researchers. This research employs the Archimedes Optimization Algorithm (AOA), an optimization technique, to determine unknown parameters for the PVM752 GaAs thin film solar cell and the RTC France solar cell. The modeling of these solar cells utilizes both a Single Diode Model (SDM) and a Double Diode Model (DDM). Performance evaluations are conducted using the sum of individual absolute errors (SIAE) and a novel root mean square error (RMSE) method. Comparing the effectiveness of the AOA with other optimization methods, The RMSEs for the AOA applied to the SDM and DDM of RTC France solar cell were 3.7415 × 10–3 and 1.0033 × 10–3. Similarly, for PVM752 GaAs thin film solar cell were 1.6564 × 10–3, and 0.00106365, respectively. The SIAE values for both solar diode models of RTC France cells were 0.071845 and 0.021268, respectively. For the PVM752 GaAs thin film, the corresponding SIAE values were 0.031488 and 0.040224. The results highlight the efficiency of the AOA-based approach, showcasing consistent convergence and a high level of accuracy in obtained solutions. The suggested approach produces superior results with a lower RMSE compared to other algorithms, demonstrating its efficacy in determining solar PV parameters for modeling purposes.

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Section: Introductionmentioning

confidence: 99%

Archimedes optimization algorithm based parameter extraction of photovoltaic models on a decent basis for novel accurate RMSE calculation

Hussain,

Hussan,

Tariq

et al. 2024

Front. Energy Res.

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Integrated Supervisory Control and Data Acquisition System for Optimized Energy Management: Leveraging Photovoltaic and Phase Change Material Thermal Storage

Shehram,

Hamidi,

Wahab

et al. 2024

Energy Storage

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Reliable energy sources are crucial for both economic growth and quality of life. In developing countries, where expensive fuels are often the primary energy source, governments are exploring innovative solutions like small‐scale, IoT‐based projects to achieve energy independence in buildings. This research investigates the integration of renewable energy technologies, statistical modeling, cloud computing, and IoT to develop a self‐managing energy system for buildings. The system prioritizes renewable sources, specifically monocrystalline solar cells with 20% efficiency for photovoltaic (PV) energy and flat plate collectors with 90% efficiency and minimal energy loss for thermal energy. Thermal energy is stored in paraffin wax, chosen for its high storage efficiency and thermal properties. The system also utilizes an absorption chiller with a high coefficient of performance (COP) to provide cooling using solar thermal energy. The building's energy loads are categorized as A, B, C, and D, each utilizing both PV and thermal energy. A SCADA system oversees the operation, monitoring the on–off status of these loads. The system is designed for continuous operation, with simulations conducted using Anaconda Jupyter Notebook and Python. This model aims to offer a sustainable and efficient energy solution for buildings, meeting energy demands while optimizing energy use.

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Effective-diode-based analysis of industrial solar photovoltaic panel by utilizing novel three-diode solar cell model against conventional single and double solar cell

Kumar,

Kumar

2024

Environ Sci Pollut Res

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Chaos Induced Coyote Algorithm (CICA) for Extracting the Parameters in a Single, Double, and Three Diode Model of a Mono-Crystalline, Polycrystalline, and a Thin-Film Solar PV Cell

Cited by 7 publications

References 67 publications

Archimedes optimization algorithm based parameter extraction of photovoltaic models on a decent basis for novel accurate RMSE calculation

Archimedes optimization algorithm based parameter extraction of photovoltaic models on a decent basis for novel accurate RMSE calculation

Integrated Supervisory Control and Data Acquisition System for Optimized Energy Management: Leveraging Photovoltaic and Phase Change Material Thermal Storage

Effective-diode-based analysis of industrial solar photovoltaic panel by utilizing novel three-diode solar cell model against conventional single and double solar cell

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