Solar photovoltaic model parameter identification using robust niching chimp optimization

•A niching concept is inspired to enhance the original ChOA.•RN-ChOA proposes a novel constraint handling technique.•The RN-ChOA is applied to estimate parameters on the SM55, SW255, and KC200GT.•RN-ChOA is compared with ten well-known algorithms. Researchers are becoming increasingly interested in...

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Published in:	Solar energy Vol. 239; pp. 179 - 197
Main Authors:	Bo, Qiuyu, Cheng, Wuqun, Khishe, Mohammad, Mohammadi, Mokhtar, Mohammed, Adil Hussein
Format:	Journal Article
Language:	English
Published:	New York Elsevier Ltd 01.06.2022 Pergamon Press Inc
Subjects:	Algorithms Biogeography Chimp optimization algorithm Constraint modelling Crystal structure Crystallinity Irradiance Machine learning Niching concept Optimization algorithms Parameter estimation Parameter identification Parameter robustness Particle swarm optimization Photovoltaic cells Photovoltaic modules Photovoltaics RN-ChOA Robustness Solar cell Solar energy Solar cell Niching concept Chimp optimization algorithm RN-ChOA Photovoltaic modules
ISSN:	0038-092X, 1471-1257
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Abstract	•A niching concept is inspired to enhance the original ChOA.•RN-ChOA proposes a novel constraint handling technique.•The RN-ChOA is applied to estimate parameters on the SM55, SW255, and KC200GT.•RN-ChOA is compared with ten well-known algorithms. Researchers are becoming increasingly interested in studying how to accurately estimate the parameters of solar PV models. In this regard, this paper proposes a newly proposed nature-inspired technique named chimp optimization algorithm (ChOA) to create accurate and dependable PV models, such as single diode, double diodes, three diodes, and PV module models. In the PV models’ parameters estimation using optimization algorithms, two significant concerns need to be addressed: classifying various local/global optima and preserving these optimum values until the termination. Since ChOA is a general optimizer, it lacks an operator to address the two issues mentioned above. In order to address the mentioned problems, this paper embeds the niching technique in ChOA that includes the personal best qualities of PSO and a local search technique. In addition, a novel constraint handling approach is utilized to ensure that the algorithm is robust in tackling PV Models’ parameters estimation constraints. The outcome of RN-ChOA is evaluated using seven well-known optimization algorithms, including the whippy Harris hawks optimization algorithm (WHHOA), performance-guided JAYA (PGJAYA), enriched Harris hawks optimization algorithm (EHHOA), improved JAYA (IJAYA), birds mating optimizer (BMO), flexible particle swarm optimization algorithm (FPSO), chaotic biogeography-based optimizer (CBBO), and generalized oppositional teaching-learning algorithm (GOTLA), as well as dynamic Levy flight ChOA (DLF-ChOA) and weighted ChOA (WChOA) as the most recent modified version of ChOA. Furthermore, the performance of the RN-ChOA method has been assessed in a practical application for parameter evaluation of three widely-used commercial modules, namely, multi-crystalline (KC200GT), polycrystalline (SW255), and mono-crystalline (SM55), under a variety of temperature and irradiance conditions that cause changes in the photovoltaic model’s parameters. The findings demonstrate the robustness and excellent performance of the suggested approach.
AbstractList	Researchers are becoming increasingly interested in studying how to accurately estimate the parameters of solar PV models. In this regard, this paper proposes a newly proposed nature-inspired technique named chimp optimization algorithm (ChOA) to create accurate and dependable PV models, such as single diode, double diodes, three diodes, and PV module models. In the PV models' parameters estimation using optimization algorithms, two significant concerns need to be addressed: classifying various local/global optima and preserving these optimum values until the termination. Since ChOA is a general optimizer, it lacks an operator to address the two issues mentioned above. In order to address the mentioned problems, this paper embeds the niching technique in ChOA that includes the personal best qualities of PSO and a local search technique. In addition, a novel constraint handling approach is utilized to ensure that the algorithm is robust in tackling PV Models' parameters estimation constraints. The outcome of RN-ChOA is evaluated using seven well-known optimization algorithms, including the whippy Harris hawks optimization algorithm (WHHOA), performance-guided JAYA (PGJAYA), enriched Harris hawks optimization algorithm (EHHOA), improved JAYA (IJAYA), birds mating optimizer (BMO), flexible particle swarm optimization algorithm (FPSO), chaotic biogeography-based optimizer (CBBO), and generalized oppositional teaching-learning algorithm (GOTLA), as well as dynamic Levy flight ChOA (DLF-ChOA) and weighted ChOA (WChOA) as the most recent modified version of ChOA. Furthermore, the performance of the RN-ChOA method has been assessed in a practical application for parameter evaluation of three widely-used commercial modules, namely, multi-crystalline (KC200GT), polycrystalline (SW255), and mono-crystalline (SM55), under a variety of temperature and irradiance conditions that cause changes in the photovoltaic model's parameters. The findings demonstrate the robustness and excellent performance of the suggested approach. •A niching concept is inspired to enhance the original ChOA.•RN-ChOA proposes a novel constraint handling technique.•The RN-ChOA is applied to estimate parameters on the SM55, SW255, and KC200GT.•RN-ChOA is compared with ten well-known algorithms. Researchers are becoming increasingly interested in studying how to accurately estimate the parameters of solar PV models. In this regard, this paper proposes a newly proposed nature-inspired technique named chimp optimization algorithm (ChOA) to create accurate and dependable PV models, such as single diode, double diodes, three diodes, and PV module models. In the PV models’ parameters estimation using optimization algorithms, two significant concerns need to be addressed: classifying various local/global optima and preserving these optimum values until the termination. Since ChOA is a general optimizer, it lacks an operator to address the two issues mentioned above. In order to address the mentioned problems, this paper embeds the niching technique in ChOA that includes the personal best qualities of PSO and a local search technique. In addition, a novel constraint handling approach is utilized to ensure that the algorithm is robust in tackling PV Models’ parameters estimation constraints. The outcome of RN-ChOA is evaluated using seven well-known optimization algorithms, including the whippy Harris hawks optimization algorithm (WHHOA), performance-guided JAYA (PGJAYA), enriched Harris hawks optimization algorithm (EHHOA), improved JAYA (IJAYA), birds mating optimizer (BMO), flexible particle swarm optimization algorithm (FPSO), chaotic biogeography-based optimizer (CBBO), and generalized oppositional teaching-learning algorithm (GOTLA), as well as dynamic Levy flight ChOA (DLF-ChOA) and weighted ChOA (WChOA) as the most recent modified version of ChOA. Furthermore, the performance of the RN-ChOA method has been assessed in a practical application for parameter evaluation of three widely-used commercial modules, namely, multi-crystalline (KC200GT), polycrystalline (SW255), and mono-crystalline (SM55), under a variety of temperature and irradiance conditions that cause changes in the photovoltaic model’s parameters. The findings demonstrate the robustness and excellent performance of the suggested approach.
Author	Cheng, Wuqun Khishe, Mohammad Bo, Qiuyu Mohammed, Adil Hussein Mohammadi, Mokhtar
Author_xml	– sequence: 1 givenname: Qiuyu surname: Bo fullname: Bo, Qiuyu organization: Institute of Urban and Rural Construction, Hebei Agricultural University, Hebei Province, China – sequence: 2 givenname: Wuqun surname: Cheng fullname: Cheng, Wuqun email: wuquncheng314@outlook.com organization: Institute of Urban and Rural Construction, Hebei Agricultural University, Hebei Province, China – sequence: 3 givenname: Mohammad surname: Khishe fullname: Khishe, Mohammad email: m_khishe@alumni.iust.ac.ir organization: Department of Electrical Engineering, Imam Khomeini Marine Science University, Nowshahr, Iran – sequence: 4 givenname: Mokhtar surname: Mohammadi fullname: Mohammadi, Mokhtar email: mukhtar@lfu.edu.krd organization: Department of Information Technology, College of Engineering and Computer Science, Lebanese French University, Kurdistan Region, Iraq – sequence: 5 givenname: Adil Hussein surname: Mohammed fullname: Mohammed, Adil Hussein email: adil.mohammed@cihanuniversity.edu.iq organization: Department of Communication and Computer Engineering, Faculty of Engineering, Cihan University-Erbil, Kurdistan Region, Iraq
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Cites_doi	10.3390/math9091002 10.1016/j.solener.2013.08.019 10.1016/j.swevo.2017.02.005 10.1109/PVSC.2018.8547901 10.1016/j.advengsoft.2013.12.007 10.1016/j.enconman.2017.08.063 10.1016/j.apenergy.2012.09.052 10.1016/j.solener.2011.09.032 10.1109/ACCESS.2021.3130933 10.24425/aoa.2020.135281 10.1016/j.enconman.2017.12.033 10.1007/978-3-540-30499-9_34 10.1016/j.solener.2011.06.025 10.1016/j.energy.2014.05.011 10.1002/cpe.4295 10.1016/j.egyr.2021.08.188 10.1016/j.egyr.2021.06.085 10.1109/CEIT.2015.7233137 10.1016/j.enconman.2018.05.062 10.1016/j.egyr.2021.01.069 10.1016/j.apenergy.2018.06.010 10.1016/j.enconman.2018.10.069 10.1016/j.solener.2013.01.010 10.1016/j.ins.2014.12.037 10.1016/j.knosys.2021.107625 10.1016/j.enconman.2021.114051 10.1007/s12559-021-09933-7 10.1109/TIE.2016.2615590 10.1016/j.enconman.2017.08.088 10.1016/j.enconman.2019.01.102 10.1016/j.ref.2019.04.003 10.2514/3.10007 10.1016/j.enconman.2016.06.076 10.1109/PECI.2011.5740496 10.1016/j.enconman.2015.05.074 10.21203/rs.3.rs-122787/v1 10.1063/1.4822054 10.3390/en15010140 10.1109/JPHOTOV.2017.2769000 10.1016/j.solener.2014.07.013 10.1016/j.solener.2012.08.018 10.1016/j.enconman.2020.112595 10.1016/j.energy.2019.01.010 10.1016/j.eswa.2020.113338 10.1016/j.jclepro.2019.118778 10.24425/aoa.2019.126360 10.1016/j.egyr.2021.11.219 10.1155/2013/362619 10.1016/j.apenergy.2014.01.027 10.1016/j.apenergy.2019.01.008 10.1016/j.renene.2017.04.014 10.1016/j.solener.2016.10.044 10.1016/j.apacoust.2018.03.012 10.1016/j.apenergy.2017.05.029 10.1016/j.egypro.2015.07.375 10.1016/j.solener.2019.01.026 10.1109/4235.585893 10.1016/j.apacoust.2019.05.006 10.1109/TEVC.2005.857610 10.1007/BF00175354 10.1016/j.solener.2011.04.013 10.1109/ICNN.1995.488968 10.1002/1099-1476(200008)23:12<1073::AID-MMA152>3.0.CO;2-D
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References	Mirjalili, Lewis (b0200) 2015; 300 Wolpert, Macready (b0305) 1997; 1 Mosavi, M., Kaveh, M., Khishe, M., Aghababaee, M., 2016. Design and implementation a sonar data set classifier by using MLP NN trained by improved biogeography-based optimization. In: Proceedings of the second National Conference on marine technology, pp. 1–6. Elattar (b0080) 2019; 171 Yang (b0315) 2020; 208 Ginidi, Shaheen, El-Sehiemy, Elattar (b0105) 2021; 7 Qin, H., Kimball, J.W., 2011. Parameter determination of photovoltaic cells from field testing data using particle swarm optimization. In: 2011 IEEE Power and Energy Conference at Illinois. IEEE, pp. 1–4. Yu, Liang, Qu, Cheng, Wang (b0335) 2018; 226 Whitley (b0300) 1994; 4 Fathy, Rezk (b0095) 2017; 111 Zeng, Shu, Wang, Chen, Yang (b0355) 2021; 7 Abbassi, Abbassi, Heidari, Mirjalili (b0005) 2019; 179 Khishe, Mosavi (b0155) 2019; 154 Mosavi, Khishe, Naseri, Parvizi, Mehdi (b0220) 2019; 44 Nayak, Mohapatra, Mohanty (b0235) 2019; 30 Khishe, Caraffini, Kuhn (b0145) 2021; 9 Dali, A., Bouharchouche, A., Diaf, S., 2015. Parameter identification of photovoltaic cell/module using genetic algorithm (GA) and particle swarm optimization (PSO). In: 2015 3rd International Conference on Control, Engineering & Information Technology (CEIT). IEEE, pp. 1–6. Ishaque, Salam (b0125) 2011; 85 Gao (b0100) 2018; 157 Elyaqouti (b0090) 2021; 7 Ibrahim, Hossain, Duck (b0120) 2022; 50 Mousavi, Kaveh, Khishe (b0225) 2016; 20 Reis, L., Camacho, J., Novacki, D., 2017. The Newton Raphson method in the extraction of parameters of PV modules. In: Proceedings of the International Conference on Renewable Energies and Power Quality (ICREPQ’17), Malaga, Spain, pp. 4–6. Oliva, Cuevas, Pajares (b0240) 2014; 72 Kler, Goswami, Rana, Kumar (b0175) 2019; 187 Alam, Yousri, Eteiba (b0015) 2015; 101 El-Naggar, AlRashidi, AlHajri, Al-Othman (b0085) 2012; 86 Kennedy, J., Eberhart, R., 1995. Particle swarm optimization. In: Proceedings of ICNN'95-International Conference on Neural Networks, vol. 4. IEEE, pp. 1942–1948. Oliva, Abd El Aziz, Hassanien (b0245) 2017; 200 Askarzadeh, Rezazadeh (b0040) 2013; 102 Askarzadeh, Rezazadeh (b0045) 2013; 90 Jacob, Balasubramanian, Azharuddin, Rajasekar (b0130) 2015; 75 Hachana, Hemsas, Tina, Ventura (b0110) 2013; 5 Kaidi, Khishe, Mohammadi (b0135) 2022; 235 Pourmousa, Ebrahimi, Malekzadeh, Alizadeh (b0255) 2019; 180 AlRashidi, AlHajri, El-Naggar, Al-Othman (b0020) 2011; 85 Yoon, Jameson (b0320) 1988; 26 Rajasekar, Kumar, Venugopalan (b0265) 2013; 97 Khishe, Mosavi (b0165) 2020 Babu, Ram, Sangeetha, Laudani, Rajasekar (b0050) 2016; 140 Patel, Panchal, Kheraj (b0250) 2014; 119 Al-Shamma’a, A.A., et al., 2022. Parameter estimation of photovoltaic cell/modules using bonobo optimizer. Energies 15(1), p. 140. Wang, Khishe, Kaveh, Mohammadi (b0295) 2021; 13 Hafez, A., Yousef, A., Soliman, A., Ismail, I., 2018. A comprehensive review for solar tracking systems design in Photovoltaic cell, module, panel, array, and systems applications. In: 2018 IEEE 7th World Conference on Photovoltaic Energy Conversion (WCPEC)(A Joint Conference of 45th IEEE PVSC, 28th PVSEC & 34th EU PVSEC). IEEE, pp. 1188-1193. Yu, Liang, Qu, Chen, Wang (b0330) 2017; 150 Saffari, A., Zahiri, S., Khishe, M., 2022. Fuzzy Grasshopper Optimization Algorithm: A Hybrid Technique for Tuning the Control Parameters of GOA Using Fuzzy System for Big Data Sonar Classification. Iranian J. Electr. Electronic Eng. 18(1), 2131–2131. Wang (b0285) 2021; 236 Chin, Salam, Ishaque (b0070) 2016; 124 Kler, Sharma, Banerjee, Rana, Kumar (b0170) 2017; 35 Chen, Jiao, Wang, Heidari, Zhao (b0065) 2020; 244 Ma, J., Ting, T., Man, K.L., Zhang, N., Guan, S.-U., Wong, P.W., 2013. Parameter estimation of photovoltaic models via cuckoo search. J. Appl. Math. vol. 2013. Yuan, Xiang, He (b0345) 2014; 108 Abd Elaziz, Oliva (b0010) 2018; 171 Yu, Qu, Yue, Ge, Chen, Liang (b0340) 2019; 237 Mathew, Rani, Kumar, Wang, Binns, Busawon (b0195) 2017; 8 Liang, Qin, Suganthan, Baskar (b0185) 2006; 10 Saffari, A., Khishe, M., 2020. Classification of Marine Mammals Using Trained Multilayer Perceptron Neural Network With Whale Algorithm Developed With Fuzzy System. Mirjalili, Mirjalili, Lewis (b0205) 2014; 69 Cárdenas, Carrasco, Mancilla-David, Street, Cárdenas (b0060) 2016; 64 Zeng, Cui (b0350) 2004; 41 Khishe, Mosavi, Moridi (b0160) 2018; 137 Wu, Yu, Kang (b0310) 2017; 151 Liang, J.J., Qin, A.K., Suganthan, P.N., Baskar, S., 2004. Evaluation of comprehensive learning particle swarm optimizer. In: International Conference on Neural Information Processing. Springer, 2004, pp. 230–235. Arunarani, Manjula, Sugumaran (b0030) 2017; 29 Wang, Y., Yuan, L., Khishe, M., Moridi, A., Mohammadzade, F., 2020. Training RBF NN Using Sine-Cosine Algorithm for Sonar Target Classification. Arch. Acoust. pp. 753–764. Naeijian, Rahimnejad, Ebrahimi, Pourmousa, Gadsden (b0230) 2021; 7 Mosavi, M., Kaveh, M., Khishe, M., 2016. Sonar data set classification using MLP neural network trained by non-linear migration rates BBO. In: The fourth Iranian conference on engineering electromagnetic (ICEEM 2016), pp. 1–5. Askarzadeh, Rezazadeh (b0035) 2012; 86 Yu, Heidari, Liang, Chen, Chen, Shao (b0325) 2021 Khishe, M., Nezhadshahbodaghi, M., Mosavi, M.R., Martín, D., 2021. A weighted chimp optimization algorithm. IEEE Access. Bao, Cao, Yang (b0055) 2000; 23 Jacob (10.1016/j.solener.2022.04.056_b0130) 2015; 75 Bao (10.1016/j.solener.2022.04.056_b0055) 2000; 23 Fathy (10.1016/j.solener.2022.04.056_b0095) 2017; 111 Mirjalili (10.1016/j.solener.2022.04.056_b0205) 2014; 69 Wolpert (10.1016/j.solener.2022.04.056_b0305) 1997; 1 Askarzadeh (10.1016/j.solener.2022.04.056_b0035) 2012; 86 Mosavi (10.1016/j.solener.2022.04.056_b0220) 2019; 44 10.1016/j.solener.2022.04.056_b0280 Mathew (10.1016/j.solener.2022.04.056_b0195) 2017; 8 Yu (10.1016/j.solener.2022.04.056_b0340) 2019; 237 Hachana (10.1016/j.solener.2022.04.056_b0110) 2013; 5 Yoon (10.1016/j.solener.2022.04.056_b0320) 1988; 26 Chen (10.1016/j.solener.2022.04.056_b0065) 2020; 244 Yu (10.1016/j.solener.2022.04.056_b0330) 2017; 150 Alam (10.1016/j.solener.2022.04.056_b0015) 2015; 101 Cárdenas (10.1016/j.solener.2022.04.056_b0060) 2016; 64 Naeijian (10.1016/j.solener.2022.04.056_b0230) 2021; 7 Zeng (10.1016/j.solener.2022.04.056_b0350) 2004; 41 Kler (10.1016/j.solener.2022.04.056_b0170) 2017; 35 cr-split#-10.1016/j.solener.2022.04.056_b0075.1 Khishe (10.1016/j.solener.2022.04.056_b0155) 2019; 154 cr-split#-10.1016/j.solener.2022.04.056_b0075.2 Kler (10.1016/j.solener.2022.04.056_b0175) 2019; 187 10.1016/j.solener.2022.04.056_b0290 Whitley (10.1016/j.solener.2022.04.056_b0300) 1994; 4 Chin (10.1016/j.solener.2022.04.056_b0070) 2016; 124 Ibrahim (10.1016/j.solener.2022.04.056_b0120) 2022; 50 Abbassi (10.1016/j.solener.2022.04.056_b0005) 2019; 179 Arunarani (10.1016/j.solener.2022.04.056_b0030) 2017; 29 Khishe (10.1016/j.solener.2022.04.056_b0160) 2018; 137 10.1016/j.solener.2022.04.056_b0210 Nayak (10.1016/j.solener.2022.04.056_b0235) 2019; 30 Yu (10.1016/j.solener.2022.04.056_b0335) 2018; 226 Khishe (10.1016/j.solener.2022.04.056_b0165) 2020 10.1016/j.solener.2022.04.056_b0215 AlRashidi (10.1016/j.solener.2022.04.056_b0020) 2011; 85 Rajasekar (10.1016/j.solener.2022.04.056_b0265) 2013; 97 Mousavi (10.1016/j.solener.2022.04.056_b0225) 2016; 20 Pourmousa (10.1016/j.solener.2022.04.056_b0255) 2019; 180 Wang (10.1016/j.solener.2022.04.056_b0285) 2021; 236 Ginidi (10.1016/j.solener.2022.04.056_b0105) 2021; 7 Elyaqouti (10.1016/j.solener.2022.04.056_b0090) 2021; 7 10.1016/j.solener.2022.04.056_b0180 Askarzadeh (10.1016/j.solener.2022.04.056_b0045) 2013; 90 Zeng (10.1016/j.solener.2022.04.056_b0355) 2021; 7 El-Naggar (10.1016/j.solener.2022.04.056_b0085) 2012; 86 10.1016/j.solener.2022.04.056_b0140 Ishaque (10.1016/j.solener.2022.04.056_b0125) 2011; 85 10.1016/j.solener.2022.04.056_b0260 Oliva (10.1016/j.solener.2022.04.056_b0245) 2017; 200 Yu (10.1016/j.solener.2022.04.056_b0325) 2021 10.1016/j.solener.2022.04.056_b0025 Mirjalili (10.1016/j.solener.2022.04.056_b0200) 2015; 300 Liang (10.1016/j.solener.2022.04.056_b0185) 2006; 10 Abd Elaziz (10.1016/j.solener.2022.04.056_b0010) 2018; 171 Gao (10.1016/j.solener.2022.04.056_b0100) 2018; 157 Yang (10.1016/j.solener.2022.04.056_b0315) 2020; 208 Yuan (10.1016/j.solener.2022.04.056_b0345) 2014; 108 Kaidi (10.1016/j.solener.2022.04.056_b0135) 2022; 235 10.1016/j.solener.2022.04.056_b0190 Elattar (10.1016/j.solener.2022.04.056_b0080) 2019; 171 Khishe (10.1016/j.solener.2022.04.056_b0145) 2021; 9 10.1016/j.solener.2022.04.056_b0150 10.1016/j.solener.2022.04.056_b0270 10.1016/j.solener.2022.04.056_b0275 Wu (10.1016/j.solener.2022.04.056_b0310) 2017; 151 Wang (10.1016/j.solener.2022.04.056_b0295) 2021; 13 10.1016/j.solener.2022.04.056_b0115 Askarzadeh (10.1016/j.solener.2022.04.056_b0040) 2013; 102 Babu (10.1016/j.solener.2022.04.056_b0050) 2016; 140 Oliva (10.1016/j.solener.2022.04.056_b0240) 2014; 72 Patel (10.1016/j.solener.2022.04.056_b0250) 2014; 119
References_xml	– reference: Kennedy, J., Eberhart, R., 1995. Particle swarm optimization. In: Proceedings of ICNN'95-International Conference on Neural Networks, vol. 4. IEEE, pp. 1942–1948. – volume: 64 start-page: 1468 year: 2016 end-page: 1476 ident: b0060 article-title: Experimental parameter extraction in the single-diode photovoltaic model via a reduced-space search publication-title: IEEE Trans. Ind. Electron. – reference: Liang, J.J., Qin, A.K., Suganthan, P.N., Baskar, S., 2004. Evaluation of comprehensive learning particle swarm optimizer. In: International Conference on Neural Information Processing. Springer, 2004, pp. 230–235. – volume: 30 start-page: 1 year: 2019 end-page: 12 ident: b0235 article-title: Parameter estimation of single diode PV module based on GWO algorithm publication-title: Renew. Energy Focus – volume: 124 start-page: 42 year: 2016 end-page: 50 ident: b0070 article-title: An accurate modelling of the two-diode model of PV module using a hybrid solution based on differential evolution publication-title: Energy Convers. Manage. – volume: 1 start-page: 67 year: 1997 end-page: 82 ident: b0305 article-title: No free lunch theorems for optimization publication-title: IEEE Trans. Evol. Comput. – volume: 208 year: 2020 ident: b0315 article-title: Comprehensive overview of meta-heuristic algorithm applications on PV cell parameter identification publication-title: Energy Convers. Manage. – reference: Saffari, A., Zahiri, S., Khishe, M., 2022. Fuzzy Grasshopper Optimization Algorithm: A Hybrid Technique for Tuning the Control Parameters of GOA Using Fuzzy System for Big Data Sonar Classification. Iranian J. Electr. Electronic Eng. 18(1), 2131–2131. – volume: 90 start-page: 123 year: 2013 end-page: 133 ident: b0045 article-title: Extraction of maximum power point in solar cells using bird mating optimizer-based parameters identification approach publication-title: Sol. Energy – reference: Khishe, M., Nezhadshahbodaghi, M., Mosavi, M.R., Martín, D., 2021. A weighted chimp optimization algorithm. IEEE Access. – reference: Hafez, A., Yousef, A., Soliman, A., Ismail, I., 2018. A comprehensive review for solar tracking systems design in Photovoltaic cell, module, panel, array, and systems applications. In: 2018 IEEE 7th World Conference on Photovoltaic Energy Conversion (WCPEC)(A Joint Conference of 45th IEEE PVSC, 28th PVSEC & 34th EU PVSEC). IEEE, pp. 1188-1193. – volume: 4 start-page: 65 year: 1994 end-page: 85 ident: b0300 article-title: A genetic algorithm tutorial publication-title: Statist. Comput. – volume: 85 start-page: 2349 year: 2011 end-page: 2359 ident: b0125 article-title: An improved modeling method to determine the model parameters of photovoltaic (PV) modules using differential evolution (DE) publication-title: Sol. Energy – volume: 179 start-page: 362 year: 2019 end-page: 372 ident: b0005 article-title: An efficient salp swarm-inspired algorithm for parameters identification of photovoltaic cell models publication-title: Energy Convers. Manage. – volume: 300 start-page: 158 year: 2015 end-page: 192 ident: b0200 article-title: Novel frameworks for creating robust multi-objective benchmark problems publication-title: Inf. Sci. – reference: Ma, J., Ting, T., Man, K.L., Zhang, N., Guan, S.-U., Wong, P.W., 2013. Parameter estimation of photovoltaic models via cuckoo search. J. Appl. Math. vol. 2013. – volume: 237 start-page: 241 year: 2019 end-page: 257 ident: b0340 article-title: A performance-guided JAYA algorithm for parameters identification of photovoltaic cell and module publication-title: Appl. Energy – volume: 151 start-page: 107 year: 2017 end-page: 115 ident: b0310 article-title: Parameter identification of photovoltaic cell model based on improved ant lion optimizer publication-title: Energy Convers. Manage. – volume: 150 start-page: 742 year: 2017 end-page: 753 ident: b0330 article-title: Parameters identification of photovoltaic models using an improved JAYA optimization algorithm publication-title: Energy Convers. Manage. – year: 2020 ident: b0165 article-title: Chimp optimization algorithm publication-title: Expert Syst. Appl. – volume: 187 start-page: 486 year: 2019 end-page: 511 ident: b0175 article-title: A novel approach to parameter estimation of photovoltaic systems using hybridized optimizer publication-title: Energy Convers. Manage. – volume: 102 start-page: 943 year: 2013 end-page: 949 ident: b0040 article-title: Artificial bee swarm optimization algorithm for parameters identification of solar cell models publication-title: Appl. Energy – volume: 44 start-page: 137 year: 2019 end-page: 151 ident: b0220 article-title: Multi-Layer Perceptron Neural Network Utilizing Adaptive Best-Mass Gravitational Search Algorithm to Classify Sonar Dataset publication-title: Arch. Acoust. – volume: 7 start-page: 275 year: 2021 end-page: 282 ident: b0355 article-title: Parameter identification of pv cell via adaptive compass search algorithm publication-title: Energy Rep. – volume: 7 start-page: 9035 year: 2021 end-page: 9045 ident: b0090 article-title: Parameters identification and optimization of photovoltaic panels under real conditions using Lambert W-function publication-title: Energy Rep. – reference: Mosavi, M., Kaveh, M., Khishe, M., 2016. Sonar data set classification using MLP neural network trained by non-linear migration rates BBO. In: The fourth Iranian conference on engineering electromagnetic (ICEEM 2016), pp. 1–5. – volume: 7 start-page: 5772 year: 2021 end-page: 5794 ident: b0105 article-title: Supply demand optimization algorithm for parameter extraction of various solar cell models publication-title: Energy Rep. – volume: 97 start-page: 255 year: 2013 end-page: 265 ident: b0265 article-title: Bacterial foraging algorithm based solar PV parameter estimation publication-title: Sol. Energy – volume: 7 start-page: 4047 year: 2021 end-page: 4063 ident: b0230 article-title: Parameter estimation of PV solar cells and modules using Whippy Harris Hawks Optimization Algorithm publication-title: Energy Rep. – volume: 111 start-page: 307 year: 2017 end-page: 320 ident: b0095 article-title: Parameter estimation of photovoltaic system using imperialist competitive algorithm publication-title: Renew. Energy – volume: 9 start-page: 1002 year: 2021 ident: b0145 article-title: Evolving Deep Learning Convolutional Neural Networks for early COVID-19 detection in chest X-ray images publication-title: Mathematics – volume: 140 start-page: 265 year: 2016 end-page: 276 ident: b0050 article-title: Parameter extraction of two diode solar PV model using Fireworks algorithm publication-title: Sol. Energy – reference: Saffari, A., Khishe, M., 2020. Classification of Marine Mammals Using Trained Multilayer Perceptron Neural Network With Whale Algorithm Developed With Fuzzy System. – year: 2021 ident: b0325 article-title: Solar photovoltaic model parameter estimation based on orthogonally-adapted gradient-based optimization publication-title: Optik – volume: 101 start-page: 410 year: 2015 end-page: 422 ident: b0015 article-title: Flower pollination algorithm based solar PV parameter estimation publication-title: Energy Convers. Manage. – volume: 10 start-page: 281 year: 2006 end-page: 295 ident: b0185 article-title: Comprehensive learning particle swarm optimizer for global optimization of multimodal functions publication-title: IEEE Trans. Evol. Comput. – volume: 72 start-page: 93 year: 2014 end-page: 102 ident: b0240 article-title: Parameter identification of solar cells using artificial bee colony optimization publication-title: Energy – reference: Dali, A., Bouharchouche, A., Diaf, S., 2015. Parameter identification of photovoltaic cell/module using genetic algorithm (GA) and particle swarm optimization (PSO). In: 2015 3rd International Conference on Control, Engineering & Information Technology (CEIT). IEEE, pp. 1–6. – volume: 69 start-page: 46 year: 2014 end-page: 61 ident: b0205 article-title: Grey wolf optimizer publication-title: Adv. Eng. Softw. – volume: 41 start-page: 1333 year: 2004 end-page: 1338 ident: b0350 article-title: A guaranteed global convergence particle swarm optimizer publication-title: J. Comput. Res. Develop. – volume: 86 start-page: 3241 year: 2012 end-page: 3249 ident: b0035 article-title: Parameter identification for solar cell models using harmony search-based algorithms publication-title: Sol. Energy – volume: 5 year: 2013 ident: b0110 article-title: Comparison of different metaheuristic algorithms for parameter identification of photovoltaic cell/module publication-title: J. Renew. Sustain. Energy – volume: 8 start-page: 248 year: 2017 end-page: 256 ident: b0195 article-title: Wind-driven optimization technique for estimation of solar photovoltaic parameters publication-title: IEEE J. Photovolt. – reference: Wang, Y., Yuan, L., Khishe, M., Moridi, A., Mohammadzade, F., 2020. Training RBF NN Using Sine-Cosine Algorithm for Sonar Target Classification. Arch. Acoust. pp. 753–764. – volume: 50 year: 2022 ident: b0120 article-title: A hybrid wind driven-based fruit fly optimization algorithm for identifying the parameters of a double-diode photovoltaic cell model considering degradation effects publication-title: Sustain. Energy Technol. Assess. – reference: Mosavi, M., Kaveh, M., Khishe, M., Aghababaee, M., 2016. Design and implementation a sonar data set classifier by using MLP NN trained by improved biogeography-based optimization. In: Proceedings of the second National Conference on marine technology, pp. 1–6. – volume: 200 start-page: 141 year: 2017 end-page: 154 ident: b0245 article-title: Parameter estimation of photovoltaic cells using an improved chaotic whale optimization algorithm publication-title: Appl. Energy – volume: 180 start-page: 180 year: 2019 end-page: 191 ident: b0255 article-title: Parameter estimation of photovoltaic cells using improved Lozi map based chaotic optimization Algorithm publication-title: Sol. Energy – volume: 86 start-page: 266 year: 2012 end-page: 274 ident: b0085 article-title: Simulated annealing algorithm for photovoltaic parameters identification publication-title: Sol. Energy – volume: 20 start-page: 65 year: 2016 end-page: 74 ident: b0225 article-title: Sonar Data Set Classification Using MLP Neural Network Trained By Modified Biogeography-Based Optimization publication-title: Iranian J. Mar. Sci. Technol.gy – volume: 226 start-page: 408 year: 2018 end-page: 422 ident: b0335 article-title: Multiple learning backtracking search algorithm for estimating parameters of photovoltaic models publication-title: Appl. Energy – volume: 35 start-page: 93 year: 2017 end-page: 110 ident: b0170 article-title: PV cell and module efficient parameters estimation using Evaporation Rate based Water Cycle Algorithm publication-title: Swarm Evol. Comput. – reference: Qin, H., Kimball, J.W., 2011. Parameter determination of photovoltaic cells from field testing data using particle swarm optimization. In: 2011 IEEE Power and Energy Conference at Illinois. IEEE, pp. 1–4. – volume: 26 start-page: 1025 year: 1988 end-page: 1026 ident: b0320 article-title: Lower-upper symmetric-Gauss-Seidel method for the Euler and Navier-Stokes equations publication-title: AIAA J. – volume: 244 year: 2020 ident: b0065 article-title: Parameters identification of photovoltaic cells and modules using diversification-enriched Harris hawks optimization with chaotic drifts publication-title: J. Cleaner Prod. – volume: 154 start-page: 176 year: 2019 end-page: 192 ident: b0155 article-title: Improved whale trainer for sonar datasets classification using neural network publication-title: Appl. Acoust. – volume: 171 start-page: 256 year: 2019 end-page: 269 ident: b0080 article-title: Environmental economic dispatch with heat optimization in the presence of renewable energy based on modified shuffle frog leaping algorithm publication-title: Energy – reference: Al-Shamma’a, A.A., et al., 2022. Parameter estimation of photovoltaic cell/modules using bonobo optimizer. Energies 15(1), p. 140. – volume: 13 start-page: 1297 year: 2021 end-page: 1316 ident: b0295 article-title: Binary Chimp Optimization Algorithm (BChOA): a New Binary Meta-heuristic for Solving Optimization Problems publication-title: Cognit. Comput. – volume: 75 start-page: 331 year: 2015 end-page: 336 ident: b0130 article-title: Solar PV modelling and parameter extraction using artificial immune system publication-title: Energy Procedia – volume: 119 start-page: 384 year: 2014 end-page: 393 ident: b0250 article-title: Extraction of solar cell parameters from a single current–voltage characteristic using teaching learning based optimization algorithm publication-title: Appl. Energy – volume: 157 start-page: 460 year: 2018 end-page: 479 ident: b0100 article-title: Parameter extraction of solar cell models using improved shuffled complex evolution algorithm publication-title: Energy Convers. Manage. – volume: 171 start-page: 1843 year: 2018 end-page: 1859 ident: b0010 article-title: Parameter estimation of solar cells diode models by an improved opposition-based whale optimization algorithm publication-title: Energy Convers. Manage. – volume: 235 year: 2022 ident: b0135 article-title: Dynamic Levy Flight Chimp Optimization publication-title: Knowl.-Based Syst. – volume: 108 start-page: 238 year: 2014 end-page: 251 ident: b0345 article-title: Parameter extraction of solar cell models using mutative-scale parallel chaos optimization algorithm publication-title: Sol. Energy – volume: 137 start-page: 121 year: 2018 end-page: 139 ident: b0160 article-title: Chaotic fractal walk trainer for sonar data set classification using multi-layer perceptron neural network and its hardware implementation publication-title: Appl. Acoust. – volume: 23 start-page: 1073 year: 2000 end-page: 1092 ident: b0055 article-title: Numerical solution of diffraction problems by a least-squares finite element method publication-title: Math. Methods Appl. Sci. – volume: 85 start-page: 1543 year: 2011 end-page: 1550 ident: b0020 article-title: A new estimation approach for determining the I-V characteristics of solar cells publication-title: Sol. Energy – volume: 236 year: 2021 ident: b0285 article-title: Photovoltaic cell parameter estimation based on improved equilibrium optimizer algorithm publication-title: Energy Convers. Manage. – volume: 29 year: 2017 ident: b0030 article-title: FFBAT: A security and cost-aware workflow scheduling approach combining firefly and bat algorithms publication-title: Concurrency Comput.: Pract. Exp. – reference: Reis, L., Camacho, J., Novacki, D., 2017. The Newton Raphson method in the extraction of parameters of PV modules. In: Proceedings of the International Conference on Renewable Energies and Power Quality (ICREPQ’17), Malaga, Spain, pp. 4–6. – volume: 9 start-page: 1002 issue: 9 year: 2021 ident: 10.1016/j.solener.2022.04.056_b0145 article-title: Evolving Deep Learning Convolutional Neural Networks for early COVID-19 detection in chest X-ray images publication-title: Mathematics doi: 10.3390/math9091002 – volume: 97 start-page: 255 year: 2013 ident: 10.1016/j.solener.2022.04.056_b0265 article-title: Bacterial foraging algorithm based solar PV parameter estimation publication-title: Sol. Energy doi: 10.1016/j.solener.2013.08.019 – volume: 35 start-page: 93 year: 2017 ident: 10.1016/j.solener.2022.04.056_b0170 article-title: PV cell and module efficient parameters estimation using Evaporation Rate based Water Cycle Algorithm publication-title: Swarm Evol. Comput. doi: 10.1016/j.swevo.2017.02.005 – ident: 10.1016/j.solener.2022.04.056_b0115 doi: 10.1109/PVSC.2018.8547901 – volume: 69 start-page: 46 year: 2014 ident: 10.1016/j.solener.2022.04.056_b0205 article-title: Grey wolf optimizer publication-title: Adv. Eng. Softw. doi: 10.1016/j.advengsoft.2013.12.007 – volume: 150 start-page: 742 year: 2017 ident: 10.1016/j.solener.2022.04.056_b0330 article-title: Parameters identification of photovoltaic models using an improved JAYA optimization algorithm publication-title: Energy Convers. Manage. doi: 10.1016/j.enconman.2017.08.063 – volume: 102 start-page: 943 year: 2013 ident: 10.1016/j.solener.2022.04.056_b0040 article-title: Artificial bee swarm optimization algorithm for parameters identification of solar cell models publication-title: Appl. Energy doi: 10.1016/j.apenergy.2012.09.052 – volume: 86 start-page: 266 issue: 1 year: 2012 ident: 10.1016/j.solener.2022.04.056_b0085 article-title: Simulated annealing algorithm for photovoltaic parameters identification publication-title: Sol. Energy doi: 10.1016/j.solener.2011.09.032 – ident: 10.1016/j.solener.2022.04.056_b0150 doi: 10.1109/ACCESS.2021.3130933 – ident: 10.1016/j.solener.2022.04.056_b0290 doi: 10.24425/aoa.2020.135281 – volume: 157 start-page: 460 year: 2018 ident: 10.1016/j.solener.2022.04.056_b0100 article-title: Parameter extraction of solar cell models using improved shuffled complex evolution algorithm publication-title: Energy Convers. Manage. doi: 10.1016/j.enconman.2017.12.033 – ident: 10.1016/j.solener.2022.04.056_b0180 doi: 10.1007/978-3-540-30499-9_34 – volume: 20 start-page: 65 issue: 78 year: 2016 ident: 10.1016/j.solener.2022.04.056_b0225 article-title: Sonar Data Set Classification Using MLP Neural Network Trained By Modified Biogeography-Based Optimization publication-title: Iranian J. Mar. Sci. Technol.gy – volume: 85 start-page: 2349 issue: 9 year: 2011 ident: 10.1016/j.solener.2022.04.056_b0125 article-title: An improved modeling method to determine the model parameters of photovoltaic (PV) modules using differential evolution (DE) publication-title: Sol. Energy doi: 10.1016/j.solener.2011.06.025 – volume: 72 start-page: 93 year: 2014 ident: 10.1016/j.solener.2022.04.056_b0240 article-title: Parameter identification of solar cells using artificial bee colony optimization publication-title: Energy doi: 10.1016/j.energy.2014.05.011 – volume: 29 issue: 24 year: 2017 ident: 10.1016/j.solener.2022.04.056_b0030 article-title: FFBAT: A security and cost-aware workflow scheduling approach combining firefly and bat algorithms publication-title: Concurrency Comput.: Pract. Exp. doi: 10.1002/cpe.4295 – volume: 7 start-page: 5772 year: 2021 ident: 10.1016/j.solener.2022.04.056_b0105 article-title: Supply demand optimization algorithm for parameter extraction of various solar cell models publication-title: Energy Rep. doi: 10.1016/j.egyr.2021.08.188 – volume: 7 start-page: 4047 year: 2021 ident: 10.1016/j.solener.2022.04.056_b0230 article-title: Parameter estimation of PV solar cells and modules using Whippy Harris Hawks Optimization Algorithm publication-title: Energy Rep. doi: 10.1016/j.egyr.2021.06.085 – ident: #cr-split#-10.1016/j.solener.2022.04.056_b0075.1 doi: 10.1109/CEIT.2015.7233137 – ident: #cr-split#-10.1016/j.solener.2022.04.056_b0075.2 – year: 2021 ident: 10.1016/j.solener.2022.04.056_b0325 article-title: Solar photovoltaic model parameter estimation based on orthogonally-adapted gradient-based optimization publication-title: Optik – volume: 171 start-page: 1843 year: 2018 ident: 10.1016/j.solener.2022.04.056_b0010 article-title: Parameter estimation of solar cells diode models by an improved opposition-based whale optimization algorithm publication-title: Energy Convers. Manage. doi: 10.1016/j.enconman.2018.05.062 – volume: 7 start-page: 275 year: 2021 ident: 10.1016/j.solener.2022.04.056_b0355 article-title: Parameter identification of pv cell via adaptive compass search algorithm publication-title: Energy Rep. doi: 10.1016/j.egyr.2021.01.069 – ident: 10.1016/j.solener.2022.04.056_b0210 – volume: 226 start-page: 408 year: 2018 ident: 10.1016/j.solener.2022.04.056_b0335 article-title: Multiple learning backtracking search algorithm for estimating parameters of photovoltaic models publication-title: Appl. Energy doi: 10.1016/j.apenergy.2018.06.010 – volume: 41 start-page: 1333 issue: 8 year: 2004 ident: 10.1016/j.solener.2022.04.056_b0350 article-title: A guaranteed global convergence particle swarm optimizer publication-title: J. Comput. Res. Develop. – volume: 179 start-page: 362 year: 2019 ident: 10.1016/j.solener.2022.04.056_b0005 article-title: An efficient salp swarm-inspired algorithm for parameters identification of photovoltaic cell models publication-title: Energy Convers. Manage. doi: 10.1016/j.enconman.2018.10.069 – volume: 50 year: 2022 ident: 10.1016/j.solener.2022.04.056_b0120 article-title: A hybrid wind driven-based fruit fly optimization algorithm for identifying the parameters of a double-diode photovoltaic cell model considering degradation effects publication-title: Sustain. Energy Technol. Assess. – volume: 90 start-page: 123 year: 2013 ident: 10.1016/j.solener.2022.04.056_b0045 article-title: Extraction of maximum power point in solar cells using bird mating optimizer-based parameters identification approach publication-title: Sol. Energy doi: 10.1016/j.solener.2013.01.010 – volume: 300 start-page: 158 year: 2015 ident: 10.1016/j.solener.2022.04.056_b0200 article-title: Novel frameworks for creating robust multi-objective benchmark problems publication-title: Inf. Sci. doi: 10.1016/j.ins.2014.12.037 – volume: 235 year: 2022 ident: 10.1016/j.solener.2022.04.056_b0135 article-title: Dynamic Levy Flight Chimp Optimization publication-title: Knowl.-Based Syst. doi: 10.1016/j.knosys.2021.107625 – ident: 10.1016/j.solener.2022.04.056_b0280 – volume: 236 year: 2021 ident: 10.1016/j.solener.2022.04.056_b0285 article-title: Photovoltaic cell parameter estimation based on improved equilibrium optimizer algorithm publication-title: Energy Convers. Manage. doi: 10.1016/j.enconman.2021.114051 – volume: 13 start-page: 1297 issue: 5 year: 2021 ident: 10.1016/j.solener.2022.04.056_b0295 article-title: Binary Chimp Optimization Algorithm (BChOA): a New Binary Meta-heuristic for Solving Optimization Problems publication-title: Cognit. Comput. doi: 10.1007/s12559-021-09933-7 – volume: 64 start-page: 1468 issue: 2 year: 2016 ident: 10.1016/j.solener.2022.04.056_b0060 article-title: Experimental parameter extraction in the single-diode photovoltaic model via a reduced-space search publication-title: IEEE Trans. Ind. Electron. doi: 10.1109/TIE.2016.2615590 – ident: 10.1016/j.solener.2022.04.056_b0270 – volume: 151 start-page: 107 year: 2017 ident: 10.1016/j.solener.2022.04.056_b0310 article-title: Parameter identification of photovoltaic cell model based on improved ant lion optimizer publication-title: Energy Convers. Manage. doi: 10.1016/j.enconman.2017.08.088 – volume: 187 start-page: 486 year: 2019 ident: 10.1016/j.solener.2022.04.056_b0175 article-title: A novel approach to parameter estimation of photovoltaic systems using hybridized optimizer publication-title: Energy Convers. Manage. doi: 10.1016/j.enconman.2019.01.102 – volume: 30 start-page: 1 year: 2019 ident: 10.1016/j.solener.2022.04.056_b0235 article-title: Parameter estimation of single diode PV module based on GWO algorithm publication-title: Renew. Energy Focus doi: 10.1016/j.ref.2019.04.003 – volume: 26 start-page: 1025 issue: 9 year: 1988 ident: 10.1016/j.solener.2022.04.056_b0320 article-title: Lower-upper symmetric-Gauss-Seidel method for the Euler and Navier-Stokes equations publication-title: AIAA J. doi: 10.2514/3.10007 – volume: 124 start-page: 42 year: 2016 ident: 10.1016/j.solener.2022.04.056_b0070 article-title: An accurate modelling of the two-diode model of PV module using a hybrid solution based on differential evolution publication-title: Energy Convers. Manage. doi: 10.1016/j.enconman.2016.06.076 – ident: 10.1016/j.solener.2022.04.056_b0260 doi: 10.1109/PECI.2011.5740496 – volume: 101 start-page: 410 year: 2015 ident: 10.1016/j.solener.2022.04.056_b0015 article-title: Flower pollination algorithm based solar PV parameter estimation publication-title: Energy Convers. Manage. doi: 10.1016/j.enconman.2015.05.074 – ident: 10.1016/j.solener.2022.04.056_b0275 doi: 10.21203/rs.3.rs-122787/v1 – volume: 5 issue: 5 year: 2013 ident: 10.1016/j.solener.2022.04.056_b0110 article-title: Comparison of different metaheuristic algorithms for parameter identification of photovoltaic cell/module publication-title: J. Renew. Sustain. Energy doi: 10.1063/1.4822054 – ident: 10.1016/j.solener.2022.04.056_b0025 doi: 10.3390/en15010140 – volume: 8 start-page: 248 issue: 1 year: 2017 ident: 10.1016/j.solener.2022.04.056_b0195 article-title: Wind-driven optimization technique for estimation of solar photovoltaic parameters publication-title: IEEE J. Photovolt. doi: 10.1109/JPHOTOV.2017.2769000 – volume: 108 start-page: 238 year: 2014 ident: 10.1016/j.solener.2022.04.056_b0345 article-title: Parameter extraction of solar cell models using mutative-scale parallel chaos optimization algorithm publication-title: Sol. Energy doi: 10.1016/j.solener.2014.07.013 – volume: 86 start-page: 3241 issue: 11 year: 2012 ident: 10.1016/j.solener.2022.04.056_b0035 article-title: Parameter identification for solar cell models using harmony search-based algorithms publication-title: Sol. Energy doi: 10.1016/j.solener.2012.08.018 – volume: 208 year: 2020 ident: 10.1016/j.solener.2022.04.056_b0315 article-title: Comprehensive overview of meta-heuristic algorithm applications on PV cell parameter identification publication-title: Energy Convers. Manage. doi: 10.1016/j.enconman.2020.112595 – volume: 171 start-page: 256 year: 2019 ident: 10.1016/j.solener.2022.04.056_b0080 article-title: Environmental economic dispatch with heat optimization in the presence of renewable energy based on modified shuffle frog leaping algorithm publication-title: Energy doi: 10.1016/j.energy.2019.01.010 – year: 2020 ident: 10.1016/j.solener.2022.04.056_b0165 article-title: Chimp optimization algorithm publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2020.113338 – volume: 244 year: 2020 ident: 10.1016/j.solener.2022.04.056_b0065 article-title: Parameters identification of photovoltaic cells and modules using diversification-enriched Harris hawks optimization with chaotic drifts publication-title: J. Cleaner Prod. doi: 10.1016/j.jclepro.2019.118778 – volume: 44 start-page: 137 issue: 1 year: 2019 ident: 10.1016/j.solener.2022.04.056_b0220 article-title: Multi-Layer Perceptron Neural Network Utilizing Adaptive Best-Mass Gravitational Search Algorithm to Classify Sonar Dataset publication-title: Arch. Acoust. doi: 10.24425/aoa.2019.126360 – volume: 7 start-page: 9035 year: 2021 ident: 10.1016/j.solener.2022.04.056_b0090 article-title: Parameters identification and optimization of photovoltaic panels under real conditions using Lambert W-function publication-title: Energy Rep. doi: 10.1016/j.egyr.2021.11.219 – ident: 10.1016/j.solener.2022.04.056_b0190 doi: 10.1155/2013/362619 – volume: 119 start-page: 384 year: 2014 ident: 10.1016/j.solener.2022.04.056_b0250 article-title: Extraction of solar cell parameters from a single current–voltage characteristic using teaching learning based optimization algorithm publication-title: Appl. Energy doi: 10.1016/j.apenergy.2014.01.027 – volume: 237 start-page: 241 year: 2019 ident: 10.1016/j.solener.2022.04.056_b0340 article-title: A performance-guided JAYA algorithm for parameters identification of photovoltaic cell and module publication-title: Appl. Energy doi: 10.1016/j.apenergy.2019.01.008 – volume: 111 start-page: 307 year: 2017 ident: 10.1016/j.solener.2022.04.056_b0095 article-title: Parameter estimation of photovoltaic system using imperialist competitive algorithm publication-title: Renew. Energy doi: 10.1016/j.renene.2017.04.014 – volume: 140 start-page: 265 year: 2016 ident: 10.1016/j.solener.2022.04.056_b0050 article-title: Parameter extraction of two diode solar PV model using Fireworks algorithm publication-title: Sol. Energy doi: 10.1016/j.solener.2016.10.044 – volume: 137 start-page: 121 year: 2018 ident: 10.1016/j.solener.2022.04.056_b0160 article-title: Chaotic fractal walk trainer for sonar data set classification using multi-layer perceptron neural network and its hardware implementation publication-title: Appl. Acoust. doi: 10.1016/j.apacoust.2018.03.012 – volume: 200 start-page: 141 year: 2017 ident: 10.1016/j.solener.2022.04.056_b0245 article-title: Parameter estimation of photovoltaic cells using an improved chaotic whale optimization algorithm publication-title: Appl. Energy doi: 10.1016/j.apenergy.2017.05.029 – volume: 75 start-page: 331 year: 2015 ident: 10.1016/j.solener.2022.04.056_b0130 article-title: Solar PV modelling and parameter extraction using artificial immune system publication-title: Energy Procedia doi: 10.1016/j.egypro.2015.07.375 – volume: 180 start-page: 180 year: 2019 ident: 10.1016/j.solener.2022.04.056_b0255 article-title: Parameter estimation of photovoltaic cells using improved Lozi map based chaotic optimization Algorithm publication-title: Sol. Energy doi: 10.1016/j.solener.2019.01.026 – volume: 1 start-page: 67 issue: 1 year: 1997 ident: 10.1016/j.solener.2022.04.056_b0305 article-title: No free lunch theorems for optimization publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/4235.585893 – volume: 154 start-page: 176 year: 2019 ident: 10.1016/j.solener.2022.04.056_b0155 article-title: Improved whale trainer for sonar datasets classification using neural network publication-title: Appl. Acoust. doi: 10.1016/j.apacoust.2019.05.006 – volume: 10 start-page: 281 issue: 3 year: 2006 ident: 10.1016/j.solener.2022.04.056_b0185 article-title: Comprehensive learning particle swarm optimizer for global optimization of multimodal functions publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2005.857610 – ident: 10.1016/j.solener.2022.04.056_b0215 – volume: 4 start-page: 65 issue: 2 year: 1994 ident: 10.1016/j.solener.2022.04.056_b0300 article-title: A genetic algorithm tutorial publication-title: Statist. Comput. doi: 10.1007/BF00175354 – volume: 85 start-page: 1543 issue: 7 year: 2011 ident: 10.1016/j.solener.2022.04.056_b0020 article-title: A new estimation approach for determining the I-V characteristics of solar cells publication-title: Sol. Energy doi: 10.1016/j.solener.2011.04.013 – ident: 10.1016/j.solener.2022.04.056_b0140 doi: 10.1109/ICNN.1995.488968 – volume: 23 start-page: 1073 issue: 12 year: 2000 ident: 10.1016/j.solener.2022.04.056_b0055 article-title: Numerical solution of diffraction problems by a least-squares finite element method publication-title: Math. Methods Appl. Sci. doi: 10.1002/1099-1476(200008)23:12<1073::AID-MMA152>3.0.CO;2-D
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Snippet	•A niching concept is inspired to enhance the original ChOA.•RN-ChOA proposes a novel constraint handling technique.•The RN-ChOA is applied to estimate... Researchers are becoming increasingly interested in studying how to accurately estimate the parameters of solar PV models. In this regard, this paper proposes...
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SubjectTerms	Algorithms Biogeography Chimp optimization algorithm Constraint modelling Crystal structure Crystallinity Irradiance Machine learning Niching concept Optimization algorithms Parameter estimation Parameter identification Parameter robustness Particle swarm optimization Photovoltaic cells Photovoltaic modules Photovoltaics RN-ChOA Robustness Solar cell Solar energy
Title	Solar photovoltaic model parameter identification using robust niching chimp optimization
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