Browsing by Author "Touabi, Cilina"

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    Photovoltaic cell I-V characteristics: simulation versus measurement
    (2021) Touabi, Cilina; Bentarzi, Hamid (Supervisor)
    Among all renewable energy sources, solar energy has acquired the highest growth rate worldwide in the last years. The major application of solar energy is photovoltaic (PV) power generation. For an accurate study in different PV applications, it is very important to model the basic device of the PV cell. However, the model parameters are usually unavailable in the datasheet provided by the manufacturers and their values change over time due to the PV degradation. Thus, how to estimate appropriate parameters is of high importance. This work presents two methods for identifying the optimal parameters of a PV generating unit. In both methods the PV generator is simulated using the one diode model. The first method is based on grey wolf algorithm where the parameters of the model are identified using only datasheets provided my manufacturers, this algorithm is included in a SIMULINK simulation for constructing the I-V and P-V characteristics. The second method is based on an opposition- based particle swarm optimization algorithm where the objective function is derived from the experimental current-voltage data. These approaches are found to be useful for designers since they are simple, fast and provide accurate results. The analysis is performed on various PV modules under different environmental conditions. The final results are compared and discussed to demonstrate the efficiency and accuracy of the proposed work.
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    Photovoltaic Panel Parameter Estimation Enhancement Using a Modified Quasi-Opposition-Based Killer Whale Optimization Technique
    (Multidisciplinary Digital Publishing Institute, 2025) Touabi, Cilina; Ouadi, Abderrahmane; Bentarzi, Hamid; Recioui, Abdelmadjid
    Photovoltaic (PV) energy generation has seen rapid growth in recent years due to its sustainability and environmental benefits. However, accurately identifying PV panel parameters is crucial for enhancing system performance, especially under varying environmental conditions. This study presents an enhanced approach for estimating PV panel parameters using a Modified Quasi-Opposition-Based Killer Whale Optimization (MQOB-KWO) technique. The research aims to improve parameter extraction accuracy by optimizing the one-diode model (ODM), a widely used representation of PV cells, using a modified metaheuristic optimization technique. The proposed algorithm leverages a Quasi-Opposition-Based Learning (QOBL) mechanism to enhance search efficiency and convergence speed. The methodology involves implementing the MQOB-KWO in MATLAB R2021a and evaluating its effectiveness through experimental I-V data from two unlike photovoltaic panels. The findings are contrasted to established optimization techniques from the literature, such as the original Killer Whale Optimization (KWO), Improved Opposition-Based Particle Swarm Optimization (IOB-PSO), Improved Cuckoo Search Algorithm (ImCSA), and Chaotic Improved Artificial Bee Colony (CIABC). The findings demonstrate that the proposed MQOB-KWO achieves superior accuracy with the lowest Root Mean Square Error (RMSE) compared to other methods, and the lowest error rates (Root Mean Square Error—RMSE, and Integral Absolute Error—IAE) compared to the original KWO, resulting in a better value of the coefficient of determination (R2 ), hence effectively capturing PV module characteristics. Additionally, the algorithm shows fast convergence, making it suitable for real-time PV system modeling. The study confirms that the proposed optimization technique is a reliable and efficient tool for improving PV parameter estimation, contributing to better system efficiency and operational performance
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    Photovoltaic panel parameters estimation using grey wolf optimization technique †
    (MDPI, 2022) Touabi, Cilina; Bentarzi, Hamid
    In different photovoltaic PV applications, it is very important to model the PV cell. However, the model parameters are usually unavailable in the datasheet provided by the manufacturers and they change due to degradation. This paper presents a method for identifying the optimal parameters of a PV cell. This method is based on the one diode model using the grey wolf algorithm as well as datasheets. An algorithm is implemented in a SIMULINK simulator for making the I-V and P-V characteristics. This approach is found to be useful for designers due to its simplicity, fastness, and accuracy. The final results are compared to demonstrate the efficiency and accuracy of the proposed method