TY  - JOUR
T1  - Tasmanian devil optimization for optimal identification of photovoltaic model parameters
TT  - Fotovoltaik Model Parametrelerinin Optimal Tanımlanması için Tazmanya Canavarı Optimizasyonu
AU  - Boylu Ayvaz, Birsen
AU  - Doğan, Zafer
PY  - 2025
DA  - November
Y2  - 2025
DO  - 10.21597/jist.1648962
JF  - Journal of the Institute of Science and Technology
JO  - J. Inst. Sci. and Tech.
PB  - Iğdır Üniversitesi
WT  - DergiPark
SN  - 2536-4618
SP  - 1297
EP  - 1310
VL  - 15
IS  - 4
LA  - en
AB  - In the whole world, when the distribution of electricity generation according to resources is examined, it is seen that photovoltaic (PV) systems constitute an important part of electricity generation. Considering this situation, to improve the PV system efficiency, high-accuracy models for PV cells should be developed depending on the current-voltage measurement data of the PV cell. In literature studies, single-diode and two-diode circuits are often utilized as PV cell models. The precision of the models is frequently determined by the accuracy of the characteristic parameters. These parameters need to be estimated effectively and accurately using PV cell measurement data. To get the optimal parameters that provide the best match between the estimated and experimental measurement data, metaheuristics are the most preferred optimization methods. This study proposed the Tasmanian devil optimization (TDO) algorithm for identifying the optimal PV model parameters. The proposed method is applied to solar cells that are frequently used in literature. The performance of the proposed method is evaluated by comparing it with other literature methods. It is seen that the PV cell models obtained by using TDO for two diode circuits, i.e. single-diode and two-diode, and PV module, demonstrate higher accuracy in matching experimental data compared to other models obtained by different methods.
KW  - Photovoltaic cells
KW  - Parameter estimation
KW  - Metaheuristic algorithms
KW  - Tasmanian devil optimization
KW  - Optimization
N2  - Dünya genelinde, elektrik üretiminin kaynaklara göre dağılımı incelendiğinde, fotovoltaik (PV) sistemlerin elektrik üretiminde önemli bir paya sahip olduğu görülmektedir. Bu durum göz önüne alındığında, PV sistem verimliliğini artırmak için PV hücresinin akım-gerilim ölçüm verilerine dayalı yüksek doğruluklu modeller geliştirilmelidir. Literatürde, PV hücre modelleri olarak genellikle tek diyotlu ve iki diyotlu devreler kullanılmaktadır. Modellerin hassasiyeti, çoğunlukla karakteristik parametrelerin doğruluğuna bağlıdır. Bu parametrelerin, PV hücresi ölçüm verileri kullanılarak etkili ve doğru bir şekilde tahmin edilmesi gerekmektedir. Tahmini ve deneysel ölçüm verileri arasındaki en iyi uyumu sağlayan optimal parametreleri elde etmek için en çok tercih edilen optimizasyon yöntemleri meta-sezgisel algoritmalardır. Bu çalışma, optimal PV model parametrelerini belirlemek için Tazmanya canavarı optimizasyon (TDO) algoritmasını önermektedir. Önerilen yöntem, literatürde yaygın olarak kullanılan güneş hücrelerine uygulanmıştır. Önerilen yöntemin performansı, literatürdeki diğer yöntemlerle karşılaştırılarak değerlendirilmiştir. Tek diyotlu ve iki diyotlu devreler ile PV modülü için TDO kullanılarak elde edilen PV hücre modellerinin, diğer yöntemlerle elde edilen modellere kıyasla deneysel verilerle daha yüksek doğrulukta eşleşme sağladığı görülmüştür.
CR  - Abdel-Basset, M., Mohamed, R., Mirjalili, S., Chakrabortty, R. K., & Ryan, M. J. (2020). Solar photovoltaic parameter estimation using an improved equilibrium optimizer. Solar Energy, 209, 694-708. https://doi.org/10.1016/j.solener.2020.09.032.
CR  - Abdollahzadeh, B., Gharehchopogh, F. S., & Mirjalili, S. (2021). African vultures optimization algorithm: A new nature-inspired metaheuristic algorithm for global optimization problems. Computers & Industrial Engineering, 158, 107408.
CR  - Askarzadeh, A., & Rezazadeh, A. (2012). Parameter identification for solar cell models using harmony search-based algorithms. Solar Energy, 86(11), 3241-3249.
CR  - Ayyarao, T. S., & Kumar, P. P. (2022). Parameter estimation of solar PV models with a new proposed war strategy optimization algorithm. International Journal of Energy Research, 46(6), 7215-7238.
CR  - Ayvaz, A. (2022). An improved chicken swarm optimization algorithm for extracting the optimal parameters of proton exchange membrane fuel cells. International Journal of Energy Research, 46(11), 15081-15098.
CR  - Chaib, L., Tadj, M., Choucha, A., Khemili, F. Z., & Attia, E. F. (2024). Improved crayfish optimization algorithm for parameters estimation of photovoltaic models. Energy Conversion and Management, 313, 118627.
CR  - Chenouard, R., & El-Sehiemy, R. A. (2020). An interval branch and bound global optimization algorithm for parameter estimation of three photovoltaic models. Energy Conversion and Management, 205, 112400.
CR  - Chou, J. S., & Truong, D. N. (2021). A novel metaheuristic optimizer inspired by behavior of jellyfish in ocean. Applied Mathematics and Computation, 389, 125535.
CR  - Dehghani, M., Hubálovský, Š., & Trojovský, P. (2022). Tasmanian devil optimization: a new bio-inspired optimization algorithm for solving optimization algorithm. IEEE Access, 10, 19599-19620.
CR  - Devarajah, L. A., Ahmad, M. A., & Jui, J. J. (2024). Identifying and estimating solar cell parameters using an enhanced slime mould algorithm. Optik, 171890.
CR  - Dogan, Z. & Boylu Ayvaz, B. (2022). A comprehensive comparison of different meta-heuristic methods for estimating the optimal parameters of photovoltaic cell model. 5th International Symposium on Innovative Approaches in Smart Technologies, 28-29 May 2022, Turkey.
CR  - Garip, Z. (2023). Parameters estimation of three-diode photovoltaic model using fractional-order Harris Hawks optimization algorithm. Optik, 272, 170391.
CR  - Izci, D., Ekinci, S., & Hussien, A. G. (2024). Efficient parameter extraction of photovoltaic models with a novel enhanced prairie dog optimization algorithm. Scientific Reports, 14(1), 7945.
CR  - Kennedy, J., & Eberhart, R. (1995, November). Particle swarm optimization. In Proceedings of ICNN'95-international conference on neural networks (Vol. 4, pp. 1942-1948). IEEE.
CR  - Kler, D., Goswami, Y., Rana, K. P. S., & Kumar, V. (2019). A novel approach to parameter estimation of photovoltaic systems using hybridized optimizer. Energy Conversion and Management, 187, 486-511.
CR  - Li, S., Gong, W., Yan, X., Hu, C., Bai, D., & Wang, L. (2019). Parameter estimation of photovoltaic models with memetic adaptive differential evolution. Solar Energy, 190, 465-474.
CR  - Ma, J., Ting, T. O., Man, K. L., Zhang, N., Guan, S. U., & Wong, P. W. (2013). Parameter estimation of photovoltaic models via cuckoo search. Journal of applied mathematics, 2013.
CR  - Nunes, H. G. G., Pombo, J. A. N., Bento, P. M. R., Mariano, S. J. P. S., & Calado, M. R. A. (2019). Collaborative swarm intelligence to estimate PV parameters. Energy Conversion and Management, 185, 866-890.
CR  - Oliva, D., Cuevas, E., & Pajares, G. (2014). Parameter identification of solar cells using artificial bee colony optimization. Energy, 72, 93-102.
CR  - Pourmousa, N., Ebrahimi, S. M., Malekzadeh, M., & Alizadeh, M. (2019). Parameter estimation of photovoltaic cells using improved Lozi map based chaotic optimization Algorithm. Solar Energy, 180, 180-191.
CR  - Ramadan, A. E., Kamel, S., Khurshaid, T., Oh, S. R., & Rhee, S. B. (2021). Parameter extraction of three diode solar photovoltaic model using improved grey wolf optimizer. Sustainability, 13(12), 6963.
CR  - Rizk-Allah, R. M., El-Sehiemy, R. A., & Abdelwanis, M. I. (2024). Improved Tasmanian devil optimization algorithm for parameter identification of electric transformers. Neural Computing and Applications, 36(6), 3141-3166.
CR  - Sahu, B. K. (2015). A study on global solar PV energy developments and policies with special focus on the top ten solar PV power producing countries. Renewable and Sustainable Energy Reviews, 43, 621-634.
CR  - Solarin, S. A. (2020). An environmental impact assessment of fossil fuel subsidies in emerging and developing economies. Environmental Impact Assessment Review, 85, 106443.
CR  - Wang, W., & Lyu, L. (2024). Adaptive Tasmanian Devil Optimizer for Global Optimization and Application in Wireless Sensor Network Deployment. IEEE Access.
CR  - Wu, L., Zheng, Y., Ezzahrae, E. H. F., Chen, C., Zhang, Z., Hong, Z., & Zhao, S. (2025). Improved Particle Swarm Optimization Algorithm Based Robust Parameter Estimation of Photovoltaic Array Model under Partial Shading Conditions. IEEJ Transactions on Electrical and Electronic Engineering, 20, 899-909.
UR  - https://doi.org/10.21597/jist.1648962
L1  - https://dergipark.org.tr/tr/download/article-file/4650284
ER  -