Article
Mathematics
Mostafa Elshahed, Ali M. M. El-Rifaie, Mohamed A. A. Tolba, Ahmed Ginidi, Abdullah Shaheen, Shazly A. A. Mohamed
Summary: This study presents an efficient hybrid optimization approach based on the hunter-prey optimizer for extracting PV parameters. The proposed method demonstrates superior performance in parameter extraction compared to other techniques.
Article
Mathematics
Rabeh Abbassi, Salem Saidi, Shabana Urooj, Bilal Naji Alhasnawi, Mohamad A. Alawad, Manoharan Premkumar
Summary: This paper proposes a developed Mountain Gazelle Optimizer (MGO) for accurate parameter estimation of PV cells/modules. The experimental findings demonstrate that the MGO outperforms other algorithms in identifying the parameters of PV models.
Article
Energy & Fuels
Martin Calasan, Shady H. E. Abdel Aleem, Ahmed F. Zobaa
Summary: An approximated expression for the calculated solar cell current is used in parameters estimation of solar photovoltaic equivalent circuits. A novel iterative approach based on Lambert W function is proposed to calculate the solar cell current and RMSE values are computed using various optimization algorithms. The results show that the proposed algorithm achieves better solutions than other algorithms in the literature.
Article
Engineering, Chemical
Amir Y. Hassan, Alaa A. K. Ismaeel, Mokhtar Said, Rania M. Ghoniem, Sanchari Deb, Abeer Galal Elsayed
Summary: The study focuses on the use of photovoltaic energy as a clean and renewable energy source. It introduces the identification of solar cell variables and compares the effectiveness of the INFO technique with seven other optimization methods.
Article
Green & Sustainable Science & Technology
Wenjing Lei, Qing He, Liu Yang, Hongzan Jiao
Summary: This paper proposes an improved honey badger algorithm (IHBA) for accurately identifying the parameters of solar photovoltaic cells. The IHBA utilizes a spiral exploration mechanism and a density update factor to enhance the algorithm's global exploration ability and convergence speed, and employs a pinhole imaging strategy to improve optimization accuracy. Experimental results demonstrate that the IHBA shows remarkable performance in convergence speed, optimization accuracy, and robustness.
Article
Green & Sustainable Science & Technology
Ibrahim Anwar Ibrahim, M. J. Hossain, Benjamin C. Duck
Summary: The paper introduces a novel hybrid optimization algorithm for determining the unknown parameters of a double-diode photovoltaic cell model. The proposed model outperforms other models in terms of accuracy, convergence speed, and feasibility.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2022)
Article
Green & Sustainable Science & Technology
Jianping Zhao, Damin Zhang, Qing He, Lun Li
Summary: This paper proposes a hybrid-strategy-improved dragonfly algorithm (HIDA) for high-accuracy parameter identification. The HIDA utilizes chaotic mapping for generating initial positions and increasing population diversity, and uses an adjacent position decision approach for adaptive position updates. It also incorporates the spiral bubble-net attack mechanism from the whale optimization algorithm to improve optimization precision, and a perturbation strategy to reduce local optima. Experimental results demonstrate the good performance of the HIDA in various scenarios with high stability, wide application range, and high accuracy.
Article
Optics
Xianzhong Jian, Yizhuang Zhu
Summary: An accurate and robust parameter identification method is crucial for the optimization of photovoltaic systems. The newly proposed metaheuristic algorithm, MRao-1, enhances the global search ability without increasing time complexity, making it a promising alternative for parameter identification in PV models.
Article
Energy & Fuels
Kawtar Tifidat, Noureddine Maouhoub, S. S. Askar, Mohamed Abouhawwash
Summary: This paper proposes a novel method for estimating the performance of photovoltaic modules under various weather conditions. The method extracts the five parameters of the single-diode model without any approximations or iterative processes, combining accuracy and rapid convergence. The method solves matrix equations based on reduced forms, ensuring simplicity and avoiding tedious calculations. The effectiveness of the method is demonstrated through testing with different PV module technologies and comparing with well-known simulating methods for the one-diode model. The results show the relevance of the new method for dynamic applications and for PV designers seeking simple modeling techniques.
Article
Thermodynamics
Youssef Kharchouf, Rachid Herbazi, Adil Chahboun
Summary: This study proposes an improved differential evolution technique using the Lambert W function and a meta-heuristic step to select optimal parameters. By applying it to various solar photovoltaic cells and modules, the method has shown significant advantages in reducing computation time and enhancing convergence characteristics.
ENERGY CONVERSION AND MANAGEMENT
(2022)
Article
Energy & Fuels
Hussein Mohammed Ridha, Hashim Hizam, Seyedali Mirjalili, Mohammad Lutfi Othman, Mohammad Effendy Ya'acob, Masoud Ahmadipour
Summary: Experimental data-oriented parameter extraction is crucial for accurately assessing the output current of photovoltaic cells. In this study, a robust adaptive arithmetic optimization algorithm based on the adaptive damping Berndt-hall-hall-Hausman approach is proposed to determine the parameters of single, double, and three diode PV models. The experimental results demonstrate the effectiveness and rapid convergence of the proposed approach.
Article
Engineering, Multidisciplinary
Mohammed H. Qais, Hany M. Hasanien, Saad Alghuwainem, K. H. Loo, M. A. Elgendy, Rania A. Turky
Summary: This article utilizes the Circle Search Algorithm (CSA) to accurately model the electrical properties of photovoltaic modules. The CSA demonstrates robustness and speed in determining the optimal model parameters. Experimental results show that the CSA-TDM has lower absolute current error under various scenarios.
AIN SHAMS ENGINEERING JOURNAL
(2022)
Article
Thermodynamics
Dalia Yousri, Ahmed Fathy, Hegazy Rezk, Thanikanti Sudhakar Babu, Mohamed R. Berber
Summary: This article investigates the use of the triple diode model (TDM) for modeling various PV modules and introduces a novel hybrid algorithm called HMPA. Results demonstrate that HMPA outperforms other algorithms in identifying TDM parameters, as confirmed by statistical analysis and convergence curves.
ENERGY CONVERSION AND MANAGEMENT
(2021)
Article
Green & Sustainable Science & Technology
Houssem Ben Aribia, Ali M. El-Rifaie, Mohamed A. Tolba, Abdullah Shaheen, Ghareeb Moustafa, Fahmi Elsayed, Mostafa Elshahed
Summary: One of the major barriers to expanding the use of solar energy is the low conversion efficiency, which requires the development of novel techniques to improve solar energy conversion equipment design. This study introduces a Growth Optimization (GO) algorithm based on human learning and reflection capacities to estimate the parameters of solar PV modules. The simulation results demonstrate that the GO algorithm enhances the electrical properties of PV systems and can determine unexplained PV parameters under different operating conditions.
Article
Computer Science, Artificial Intelligence
Hegazy Rezk, Mohamed M. M. Elsenety, Seydali Ferahtia, Polycarpos Falaras, Alaa A. A. Zaky
Summary: This paper considers the experimental and mathematical modeling of triple-cation perovskite solar cells (PSCs) with two different device structures. It proposes a novel method incorporating a recent metaheuristic algorithm named COOT optimizer to estimate the optimal parameters of the three-diode equivalent circuit of triple-cation perovskite solar cells.
NEURAL COMPUTING & APPLICATIONS
(2023)
