Extraction of Photovoltaic Cell and Photovoltaic Module Parameters Using African Vultures Optimization Algorithm

Yıl 2021, Cilt: 9 Sayı: 4, 708 - 725, 29.12.2021

Mehmet Yeşilbudak

https://doi.org/10.29109/gujsc.997972

Cited By: 2

Öz

In order to characterize the actual electrical behavior of photovoltaic cells and photovoltaic modules, it is required to construct the equivalent circuit models effectively, and to identify the unknown model parameters properly. This improves the design, control and performance of photovoltaic systems. In this study, African vultures optimization was applied to solve the parameter extraction problem encountered in single diode- and double diode-based photovoltaic cell modeling and single diode-based photovoltaic module modeling. African vultures optimization algorithm efficiently balances the optimization process by using two different strategies in the exploration phase and four different strategies in the exploitation phase. The root mean squared error between simulated and measured output current was computed to evaluate the parameter extraction performance. In addition, the obtained results were compared with different parameter extraction methods commonly-used in the literature. It has been shown that the African vultures optimization algorithm is a stable and reliable technique for the extraction of photovoltaic cell and module parameters.

Anahtar Kelimeler

Photovoltaic cell, Photovoltaic module, Metaheuristic optimization, Parameter extraction

Afrika Akbabaları Optimizasyon Algoritması Kullanılarak Fotovoltaik Hücre ve Fotovoltaik Modül Parametrelerinin Çıkarımı

Öz

Fotovoltaik hücrelerin ve fotovoltaik modüllerin gerçek elektriksel davranışlarını karakterize etmek için eşdeğer devre modellerinin etkin bir şekilde oluşturulması ve bilinmeyen model parametrelerinin doğru bir şekilde tanımlanması gerekir. Bu sayede, fotovoltaik sistemlerin tasarımı, kontrolü ve performansı iyileştirilir. Bu çalışmada, tek diyot ve çift diyot tabanlı fotovoltaik hücre modellemeleri ile tek diyot tabanlı fotovoltaik modül modellemesinde karşılaşılan parametre çıkarım problemini çözmek için Afrika akbabaları optimizasyonu uygulanmıştır. Afrika akbabaları optimizasyon algoritması keşif aşamasında iki farklı strateji ve sömürü aşamasında dört farklı strateji kullanarak optimizasyon sürecini verimli bir şekilde dengeler. Parametre çıkarım performansını değerlendirmek için simüle edilmiş ve ölçülen çıkış akımları arasındaki karekök ortalama hata hesaplanmıştır. Ayrıca, elde edilen sonuçlar literatürde yaygın olarak kullanılan farklı parametre çıkarım metotlarıyla karşılaştırılmıştır. Afrika akbabaları optimizasyon algoritmasının fotovoltaik hücre ve modül parametrelerinin çıkarımı için kararlı ve güvenilir bir teknik olduğu gösterilmiştir.

Anahtar Kelimeler

Fotovoltaik hücre, Fotovoltaik modül, Metasezgisel optimizasyon, Parametre çıkarımı

Kaynakça

• Ismaeel, A.A.K., Houssein, E.H., Oliva, D., & Said, M. (2021). Gradient-based optimizer for parameter extraction in photovoltaic models. IEEE Access, 9, 13403-13416.
• Khursheed, M.U.N., Alghamdi, M.A., Khan, M.F.N., Khan, A.K., Khan, I., Ahmed, A., Kiani, A.T., & Khan, M.A. (2021). PV model parameter estimation using modified FPA with dynamic switch probability and step size function. IEEE Access, 9, 42027-42044.
• Ibrahim, I.A., Hossain, M.J., Duck, B.C., & Fell, C.J. (2020). An adaptive wind-driven optimization algorithm for extracting the parameters of a single-diode PV cell model. IEEE Transactions on Sustainable Energy, 11(2), 1054-1066.
• Ridha, H.M., Gomes, C., & Hizam, H. (2020). Estimation of photovoltaic module model’s parameters using an improved electromagnetic-like algorithm. Neural Computing and Applications, 32(16), 12627-12642.
• Muhsen, D.H., Ghazali, A.B., Khatib, T., & Abed, I.A. (2015). Parameters extraction of double diode photovoltaic module’s model based on hybrid evolutionary algorithm. Energy Conversion and Management, 105, 552-561.
• Ridha, H.M. (2020). Parameters extraction of single and double diodes photovoltaic models using Marine Predators Algorithm and Lambert W function. Solar Energy, 209, 674-693.
• Chaibi, Y., Allouhi, A., & Salhi, M. (2020). A simple iterative method to determine the electrical parameters of photovoltaic cell. Journal of Cleaner Production, 269, 122363.
• Ganesh Pardhu, B.S.S. & Kota, V. R. (2021). Radial movement optimization based parameter extraction of double diode model of solar photovoltaic cell. Solar Energy, 213, 312-327.
• Et-torabi, K., Nassar-eddine, I., Obbadi, A., Errami, Y., Rmaily, R., Sahnoun, S., El fajri, A., & Agunaou, M. (2017). Parameters estimation of the single and double diode photovoltaic models using a Gauss-Seidel algorithm and analytical method: A comparative study. Energy Conversion and Management, 148, 1041-1054.
• Long, W., Wu, T., Jiao, J., Tang, M., & Xu, M. (2020). Refraction-learning-based whale optimization algorithm for high-dimensional problems and parameter estimation of PV model. Engineering Applications of Artificial Intelligence, 89, 103457.
• Ndi, F.E., Perabi, S.N., Ndjakomo, S.E., Abessolo, G.O., & Mengata, G.M. (2021). Estimation of single-diode and two diode solar cell parameters by equilibrium optimizer method. Energy Reports, 7, 4761-4768.
• Chen, X., Yu, K., Du, W., Zhao, W., & Liu, G. (2016). Parameters identification of solar cell models using generalized oppositional teaching learning based optimization. Energy, 99, 170-180.
• Jamadi, M., Merrikh-Bayat, F., & Bigdeli, M. (2015). Very accurate parameter estimation of single- and double-diode solar cell models using a modified artificial bee colony algorithm. International Journal of Energy and Environmental Engineering. 7(1), 13-25.
• Weng, X., Heidari, A.A., Liang, G., Chen, H., Ma, X., Mafarja, M., & Turabieh, H. (2021). Laplacian Nelder-Mead spherical evolution for parameter estimation of photovoltaic models. Energy Conversion and Management, 243, 114223.
• Gude, S. & Jana, K.C. (2020). Parameter extraction of photovoltaic cell using an improved cuckoo search optimization. Solar Energy, 204, 280-293.
• Yu, K., Qu, B., Yue, C., Ge, S., Chen, X., & Liang, J. (2019). A performance-guided JAYA algorithm for parameters identification of photovoltaic cell and module. Applied Energy, 237, 241-257.
• Jian, X. & Zhu, Y. (2021). Parameters identification of photovoltaic models using modified Rao-1 optimization algorithm. Optik, 231, 166439.
• Basset, M.A., Mohamed, R., Chakrabortty, R.K., Sallam, K, & Ryan, M.J. (2021). An efficient teaching-learning-based optimization algorithm for parameters identification of photovoltaic models: Analysis and validations. Energy Conversion and Management, 227, 113614.
• Long, W., Wu, T., Xu, M., Tang, M., & Cai, S. (2021). Parameters identification of photovoltaic models by using an enhanced adaptive butterfly optimization algorithm. Energy, 229, 120750.
• Jiao, S., Chong, G., Huang, C., Hu, H., Wang, M., Heidari, A.A., Chen, H., & Zhao, X. (2020). Orthogonally adapted Harris hawks optimization for parameter estimation of photovoltaic models. Energy, 203, 117804.
• Zhang, Y., Ma, M., & Jin, Z. (2020). Backtracking search algorithm with competitive learning for identification of unknown parameters of photovoltaic systems. Expert Systems with Applications, 160, 113750.
• Zhang, Y., Huang, C., & Jin, Z. (2020). Backtracking search algorithm with reusing differential vectors for parameter identification of photovoltaic models. Energy Conversion and Management, 223, 113266.
• Mi, X., Liao, Z., Li, S., & Gu, Q. (2021). Adaptive teaching-learning-based optimization with experience learning to identify photovoltaic cell parameters. Energy Reports, 7, 4114-4125.
• Zhang, H., Heidari, A.A., Wang, M., Zhang, L., Chen, H., & Li, C. (2020). Orthogonal Nelder-Mead moth flame method for parameters identification of photovoltaic modules. Energy Conversion and Management, 211, 112764.
• Liu, Y., Heidari, A.A., Ye, X., Liang, G., Chen, H., & He, C. (2021). Boosting slime mould algorithm for parameter identification of photovoltaic models. Energy, 234, 121164.
• Deotti, L.M.P., Pereira, J.L.R., & Júnior, I.C.S. (2020). Parameter extraction of photovoltaic models using an enhanced Lévy flight bat algorithm. Energy Conversion and Management, 221, 113114.
• Lekouaghet, B., Boukabou, A., & Boubakir, C. (2021). Estimation of the photovoltaic cells/modules parameters using an improved Rao-based chaotic optimization technique. Energy Conversion and Management, 229, 113722.
• Premkumar, M., Jangir, P., Sowmya, R., Elavarasan, R.M., & Kumar, B.S. (2021). Enhanced chaotic JAYA algorithm for parameter estimation of photovoltaic cell/modules. ISA Transactions, 116, 139-166.
• Chen, X. & Yu, K. (2019). Hybridizing cuckoo search algorithm with biogeography-based optimization for estimating photovoltaic model parameters. Solar Energy, 180, 192-206.
• Long, W., Cai, S., Jiao, J., Xu, M., & Wu, T. (2020). A new hybrid algorithm based on grey wolf optimizer and cuckoo search for parameter extraction of solar photovoltaic models. Energy Conversion and Management, 203, 112243.
• Chen, H., Jiao, S., Heidari, A.A., Wang, M., Chen, X., & Zhao, X. (2019). An opposition-based sine cosine approach with local search for parameter estimation of photovoltaic models. Energy Conversion and Management, 195, 927-942.
• Xiong, G. , Li, L., Mohamed, A.W., Yuan, X., & Zhang, J. (2021). A new method for parameter extraction of solar photovoltaic models using gaining-sharing knowledge based algorithm. Energy Reports, 7, 3286-3301.
• Abdel-Basset, M., El-Shahat, D., Chakrabortty, R.K., & Ryan, M. (2021). Parameter estimation of photovoltaic models using an improved marine predators algorithm. Energy Conversion and Management, 227, 113491.
• Li, S., Gu, Q., Gong, W., & Ning, B. (2020). An enhanced adaptive differential evolution algorithm for parameter extraction of photovoltaic models. Energy Conversion and Management, 205, 112443.
• Gao, S., Wang, K., Tao, S., Jin, T., Dai, H., & Cheng, J. (2021). A state-of-the-art differential evolution algorithm for parameter estimation of solar photovoltaic models. Energy Conversion and Management, 230, 113784.
• Hu, Z., Gong, W., & Li, S. (2021). Reinforcement learning-based differential evolution for parameters extraction of photovoltaic models. Energy Reports, 7, 916-928.
• Liang, J., Ge, S., Qu, B., Yu, K., Liu, F., Yang, H., Wei, P., & Li, Z. (2020). Classified perturbation mutation based particle swarm optimization algorithm for parameters extraction of photovoltaic models. Energy Conversion and Management, 203, 112138.
• Çelik, E., Öztürk, N. & Arya, Y. (2021). Advancement of the search process of salp swarm algorithm for global optimization problems. Expert Systems with Applications, 182, 115292.
• 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.
• Easwarakhanthan, T., Bottin, J., Bouhouch, I., & Boutrit, C. (1986). Nonlinear minimization algorithm for determining the solar cell parameters with microcomputers. International Journal of Solar Energy, 4, 1-12.
• Chen, X., Xu, B., Mei, C., Ding, Y., & Lia, K. (2018). Teaching-learning-based artificial bee colony for solar photovoltaic parameter estimation. Applied Energy, 212, 1578-1588.
• Liang, J., Qiao, K., Yuan, M., Yu, K., Qu, B., Ge, S., Li, Y., & Chen, G. (2020). Evolutionary multi-task optimization for parameters extraction of photovoltaic models. Energy Conversion and Management, 207, 112509.
• Askarzadeh, A. & Rezazadeh, A. (2012). Parameter identification for solar cell models using harmony search-based algorithms. Solar Energy, 86(11), 3241-3249.
• Xiong, G., Zhang, J., Shi, D., & He, Y. (2018). Parameter extraction of solar photovoltaic models using an improved whale optimization algorithm. Energy Conversion and Management, 174, 388-405.
• Oliva, D., Cuevas, E., & Pajares, G. (2014). Parameter identification of solar cells using artificial bee colony optimization. Energy, 72, 93-102.
• El-Naggar, K.M., AlRashidi, M.R., AlHajri, M.F., & Al-Othman, A.K. (2012). Simulated annealing algorithm for photovoltaic parameters identification. Solar Energy, 86(1), 266-274.
• AlHajri, M.F., El-Naggar, K.M., AlRashidi, M.R., & Al-Othman, A.K. (2012). Optimal extraction of solar cell parameters using pattern search. Renewable Energy, 44, 238-245.
• Rajasekar, N., Kumar, N.K., & Venugopalan, R. (2013). Bacterial foraging algorithm based solar PV parameter estimation. Solar Energy, 97, 255-265.
• Li, S., Gong, W., Yan, X., Hu, C., Bai, D., Wang, L., & Gao, L. (2019). Parameter extraction of photovoltaic models using an improved teaching-learning-based optimization. Energy Conversion and Management, 186, 293-305.
• Yu, K., Liang, J.J., Qu, B.Y., Cheng, Z., & Wang, H. (2018). Multiple learning backtracking search algorithm for estimating parameters of photovoltaic models. Applied Energy, 226, 408-422.
• Alam, D.F., Yousri, D.A., & Eteiba, M.B. (2015). Flower pollination algorithm based solar PV parameter estimation. Energy Conversion and Management, 101, 410-422.
• Hachana, O., Hemsas, K.E., Tina, G.M., & Ventura, C. (2013). Comparison of different metaheuristic algorithms for parameter identification of photovoltaic cell/module. Journal of Renewable & Sustainable Energy, 5, 053122.
• Wei, H., Cong, J., Lingyun, X., & Deyun, S. (2011). Extracting solar cell model parameters based on chaos particle swarm algorithm. IEEE International Conference on Electric Information & Control Engineering, 398-402, 15-17 April 2011, Wuhan, China.
• Patel, S.J., Panchal, A.K., & Kheraj, V. (2014). Extraction of solar cell parameters from a single current-voltage characteristic using teaching learning based optimization algorithm. Applied Energy, 119, 384-393.
• Yeşilbudak, M., Çolak, M., ve Bayındır, R. (2018). Ankara ilinin uzun dönem global güneş ışınım şiddeti, güneşlenme süresi ve hava sıcaklığı verilerinin analizi ve eğri uydurma metotlarıyla modellenmesi. Gazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım ve Teknoloji, 6(1), 189-203.