Parameter estimation of PV solar cells and modules using Metaheuristic Optimization Algorithm

Yıl 2024, Cilt: 3 Sayı: 1, 9 - 16, 30.06.2024

Rafa Elshara Aybaba Hançerlioğulları

Öz

Photovoltaic (PV) solar cells and modules are crucial components of renewable energy systems, necessitating accurate parameter estimation for optimal performance and efficiency. This paper proposes the utilization of the Grasshopper Optimization Algorithm (GOA) for parameter estimation in PV solar cells and modules. The proposed methodology aims to enhance the accuracy and efficiency of parameter estimation by leveraging the unique search mechanism of the GOA, which mimics the foraging behavior of grasshoppers in nature. Through iterative optimization, the GOA efficiently explores the solution space to identify optimal parameters that best fit experimental data, such as current-voltage (IV) and power-voltage (PV) characteristics. The paper provides a comprehensive overview of the parameter estimation process, detailing the formulation of the objective function to minimize the error between experimental and simulated data. Furthermore, it discusses the implementation of the GOA algorithm and its integration with mathematical models of PV solar cells and modules. To validate the effectiveness of the proposed approach, experimental data from real-world PV systems are utilized. Comparative analyses with other optimization algorithms demonstrate the superior performance of the GOA in terms of convergence speed and accuracy in parameter estimation. The results indicate that the proposed methodology offers a robust and efficient solution for parameter estimation in PV solar cells and modules, thereby facilitating the design, optimization, and maintenance of photovoltaic systems. The integration of the GOA algorithm contributes to advancing the state-of-the-art in renewable energy technologies, promoting the widespread adoption of solar power generation for sustainable development.

Anahtar Kelimeler

Photovoltaic solar cells, Metaheuristic Optimization Algorithm, Parameter estimation

Kaynakça

• [1] A. Rauf, N. Nureen, M. Irfan, and M. Ali, “The current developments and future prospects of solar photovoltaic industry in an emerging economy of India,” Environ. Sci. Pollut. Res., vol. 30, no. 16, pp. 46270–46281, 2023.
• [2] Z. Yusupov, N. Almagrahi, E. Yaghoubi, E. Yaghoubi, A. Habbal, and D. Kodirov, “Modeling and Control of Decentralized Microgrid Based on Renewable Energy and Electric Vehicle Charging Station,” in World Conference Intelligent System for Industrial Automation, 2022, pp. 96–102.
• [3] X. Wu, B. Liao, Y. Su, and S. Li, “Multi-objective and multi-algorithm operation optimization of integrated energy system considering ground source energy and solar energy,” Int. J. Electr. Power Energy Syst., vol. 144, p. 108529, 2023.
• [4] Z. Yusupov, E. Yaghoubi, and V. Soyibjonov, “REDUCING THE VULNERABILITY IN MICROGRID POWER SYSTEMS,” Sci. Innov., vol. 2, no. A5, pp. 166–175, 2023.
• [5] A. S. Irshad, “Design and comparative analysis of grid-connected BIPV system with monocrystalline silicon and polycrystalline silicon in Kandahar climate,” in MATEC Web of Conferences, 2023, vol. 374, p. 3002.
• [6] N. Balamurugan, P. Karuppasamy, and P. Ramasamy, “Investigation on different crystal grains from the multi-crystalline silicon (mc-Si) wafer,” Silicon, vol. 15, no. 3, pp. 1465–1474, 2023.
• [7] S. Kar, S. Banerjee, and C. K. Chanda, “Performance study of Amorphous-Si thin-film solar cell for the recent application in photovoltaics,” Mater. Today Proc., vol. 80, pp. 1286–1290, 2023.
• [8] S. B. Hamed et al., “A robust MPPT approach based on first-order sliding mode for triple-junction photovoltaic power system supplying electric vehicle,” Energy Reports, vol. 9, pp. 4275–4297, 2023.
• [9] P. K. Bonthagorla and S. Mikkili, “A Novel Hybrid Slime Mould MPPT Technique for BL-HC Configured Solar PV System Under PSCs,” J. Control. Autom. Electr. Syst., pp. 1–14, 2023.
• [10] S. C. Nwokolo, A. U. Obiwulu, and J. C. Ogbulezie, “Machine learning and analytical model hybridization to assess the impact of climate change on solar PV energy production,” Phys. Chem. Earth, Parts A/B/C, vol. 130, p. 103389, 2023.
• [11] A. D. Tuncer et al., “Experimental and numerical analysis of a grooved hybrid photovoltaic-thermal solar drying system,” Appl. Therm. Eng., vol. 218, p. 119288, 2023.
• [12] Y. Zhang, Y. Wu, L. Li, and Z. Liu, “A Hybrid Energy Storage System Strategy for Smoothing Photovoltaic Power Fluctuation Based on Improved HHO-VMD,” Int. J. Photoenergy, vol. 2023, 2023.