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Triple diode parameter estimation of solar PV cell using hybrid algorithm

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Abstract

Solar photovoltaic (PV) systems are now one of the most prominent green energy technologies for producing a significant proportion of electricity. With the increased attention towards solar PV-based systems, the effective and precise estimation of PV cell parameters has received considerable attention from researchers. Extracting the parameters of the solar PV model is quite important for precise modelling, assessment and control of the PV system. Mostly theoretical, computational and meta-heuristic in the last few years have been proposed which extract parameters of PV cell based on the experimental results. Extracting PV model parameters, however, remains a major challenge. The application of a new hybrid algorithm that relies on the Grey Wolf Optimizer and Cuckoo Search Algorithm is being proposed in this manuscript to extract the parameters of various PV cell models. The parameter optimization results are obtained using GWOCSA and are further compared with those obtained with five other algorithms, i.e. PSO, MVO, SCA, CSA, and GWO. The complete error analysis is carried out for TDM of PV cells to establish the superiority of GWOCSA. The superiority of proposed algorithm is established using ranking test, statistical error analysis, and sensitivity temperature variation.

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References

  • Abbassi R, Abbassi A, Heidari AA, Mirjalili S (2019) An efficient salp swarm-inspired algorithm for parameters identification of photovoltaic cell models. Energy Convers Manag 179:362–372

    Article  Google Scholar 

  • Abd Elaziz M, Oliva D (2018) Parameter estimation of solar cells diode models by an improved opposition-based whale optimization algorithm. Energy Convers Manag 171:1843–1859

    Article  Google Scholar 

  • Alam DF, Yousri DA, Eteiba MB (2015) Flower pollination algorithm based solar PV parameter estimation. Energy Convers Manag 101:410–422

    Article  Google Scholar 

  • Ali EE, El-Hameed MA, El-Fergany AA, El-Arini MM (2016) Parameter extraction of photovoltaic generating units using multi-verse optimizer. Sustain Energy Technol Assess 17:68–76

    Google Scholar 

  • Allam D, Yousri DA, Eteiba MB (2016) Parameters extraction of the three diode model for the multi-crystalline solar cell/module using Moth-flame optimization algorithm. Energy Convers Manag 123:535–548

    Article  Google Scholar 

  • Askarzadeh A, dos Santos Coelho L (2015) Determination of photovoltaic modules parameters at different operating conditions using a novel bird mating optimizer approach. Energy Convers Manag 89:608–614

    Article  Google Scholar 

  • Askarzadeh A, Rezazadeh A (2012) Parameter identification for solar cell models using harmony search-based algorithms. Solar Energy 86(11):3241–3249

    Article  Google Scholar 

  • Balasubramanian K, Jacob B, Priya K, Sangeetha K, Rajasekar N, Babu TS (2015) Critical evaluation of genetic algorithm based fuel cell parameter extraction. Energy Procedia 75:1975–1982

    Article  Google Scholar 

  • Beigi AM, Maroosi A (2018) Parameter identification for solar cells and module using a hybrid firefly and pattern search algorithms. Solar Energy 171:435–446

    Article  Google Scholar 

  • Chen X, Yu K (2019) Hybridizing cuckoo search algorithm with biogeography-based optimization for estimating photovoltaic model parameters. Sol Energy 180:192–206

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Chen Z, Wu L, Lin P, Wu Y, Cheng S (2016) Parameters identification of photovoltaic models using hybrid adaptive Nelder-Mead simplex algorithm based on eagle strategy. Appl Energy 182:47–57

    Article  CAS  Google Scholar 

  • Chen X, Xu B, Mei C, Ding Y, Li K (2018) Teaching–learning–based artificial bee colony for solar photovoltaic parameter estimation. Appl energy 212:1578–1588

    Article  Google Scholar 

  • Chen H, Jiao S, Heidari AA, Wang M, Chen X, Zhao X (2019) An opposition-based sine cosine approach with local search for parameter estimation of photovoltaic models. Energy Convers Manag 195:927–942

    Article  Google Scholar 

  • Elazab OS, Hasanien HM, Elgendy MA, Abdeen AM (2018) Parameters estimation of single-and multiple-diode photovoltaic model using whale optimisation algorithm. IET Renewe Power Gen 12(15):1755–1761

    Article  Google Scholar 

  • Fathabadi H (2013) Novel neural-analytical method for determining silicon/plastic solar cells and modules characteristics. Energy Convers Manag 76:253–259

    Article  CAS  Google Scholar 

  • Fathy A, Rezk H (2017) Parameter estimation of photovoltaic system using imperialist competitive algorithm. Renew Energy 111:307–320

    Article  Google Scholar 

  • Fouad MM, Shihata LA, Morgan EI (2017) An integrated review of factors influencing the performance of photovoltaic panels. Renew Sustain Energy Rev 80:1499–1511

    Article  Google Scholar 

  • Guo L, Meng Z, Sun Y, Wang L (2016) Parameter identification and sensitivity analysis of solar cell models with cat swarm optimization algorithm. Energy Convers Manag 108:520–528

    Article  Google Scholar 

  • Gupta S, Deep K (2019) A novel random walk grey wolf optimizer. Swarm Evol Comput 44:101–112

    Article  Google Scholar 

  • Hasanien HM (2015) Shuffled frog leaping algorithm for photovoltaic model identification. IEEE Trans Sustain Energy 6(2):509–515

    Article  Google Scholar 

  • Ishaque K, Salam Z, Mekhilef S, Shamsudin A (2012) Parameter extraction of solar photovoltaic modules using penalty-based differential evolution. Appl Energy 99:297–308

    Article  Google Scholar 

  • Ismail MS, Moghavvemi M, Mahlia TMI (2013) Characterization of PV panel and global optimization of its model parameters using genetic algorithm. Energy Convers Manag 73:10–25

    Article  Google Scholar 

  • Jordehi AR (2018) Enhanced leader particle swarm optimisation (ELPSO): an efficient algorithm for parameter estimation of photovoltaic (PV) cells and modules. Sol Energy 159:78–87

    Article  CAS  Google Scholar 

  • Karatepe E, Boztepe M, Colak M (2007) Development of a suitable model for characterizing photovoltaic arrays with shaded solar cells. Solar energy 81(8):977–992

    Article  CAS  Google Scholar 

  • Kler D, Sharma P, Banerjee A, Rana KPS, Kumar V (2017) PV cell and module efficient parameters estimation using evaporation rate based water cycle algorithm. Swarm Evol Comput 35:93–110

    Article  Google Scholar 

  • Lin P, Cheng S, Yeh W, Chen Z, Wu L (2017) Parameters extraction of solar cell models using a modified simplified swarm optimization algorithm. Sol Energy 144:594–603

    Article  Google Scholar 

  • Li S, Gong W, Yan X, Hu C, Bai D, Wang L (2019) Parameter estimation of photovoltaic models with memetic adaptive differential evolution. Sol Energy 190:465–474

    Article  Google Scholar 

  • Long W, Jiao J, Liang X, Tang M (2018) An exploration-enhanced grey wolf optimizer to solve high-dimensional numerical optimization. Eng Appl Artif Intell 68:63–80

    Article  Google Scholar 

  • Maghami MR, Hizam H, Gomes C, Radzi MA, Rezadad MI, Hajighorbani S (2016) Power loss due to soiling on solar panel: a review. Renew Sustain Energy Rev 59:1307–1316

    Article  Google Scholar 

  • Mares O, Paulescu M, Badescu V (2015) A simple but accurate procedure for solving the five-parameter model. Energy Convers Manag 105:139–148

    Article  Google Scholar 

  • Mirjalili S, Mirjalili SM, Lewis A (2014) Grey wolf optimizer. Adv Eng Softw 69:46–61

    Article  Google Scholar 

  • Mlakar U, Fister I Jr, Fister I (2016) Hybrid self-adaptive cuckoo search for global optimization. Swarm Evol Comput 29:47–72

    Article  Google Scholar 

  • Niu Q, Zhang L, Li K (2014) A biogeography-based optimization algorithm with mutation strategies for model parameter estimation of solar and fuel cells. Energy Convers Manag 86:1173–1185

    Article  Google Scholar 

  • Nunes HGG, Pomboa JAN, Marianoa SJPS, Caladoa MRA (2018) Felippe de Souza JAM. A new high performance method for determining the parameters of PV cells and modules based on guaranteed convergence particle swarm optimization. Appl Energy 211:774–91

    Article  Google Scholar 

  • Oliva D, Abd El Aziz M, Hassanien AE (2017) Parameter estimation of photovoltaic cells using an improved chaotic whale optimization algorithm. Appl Energy 200:141–154

    Article  Google Scholar 

  • Oliva D, Ewees AA, Aziz MAE, Hassanien AE, Peréz-Cisneros M (2017) A chaotic improved artificial bee colony for parameter estimation of photovoltaic cells. Energies 10(7):865

    Article  Google Scholar 

  • Oliva D, Abd Elaziz M, Elsheikh AH, Ewees AA (2019) A review on meta-heuristics methods for estimating parameters of solar cells. J Power Sour 435:126683

    Article  CAS  Google Scholar 

  • Patel SJ, Panchal AK, Kheraj V (2014) Extraction of solar cell parameters from a single current–voltage characteristic using teaching learning based optimization algorithm. Appl Energy 119:384–393

    Article  Google Scholar 

  • Pelap FB, Dongo PD, Kapim AD (2016) Optimization of the characteristics of the PV cells using nonlinear electronic components. Sustain Energy Technol Assess 16:84–92

    Google Scholar 

  • Premkumar, M., Babu, T. S., Umashankar, S., & Sowmya, R. (2020). A new metaphor-less algorithms for the photovoltaic cell parameter estimation. Optik, 164559.

  • Rajasekar N, Kumar NK, Venugopalan R (2013) Bacterial foraging algorithm based solar PV parameter estimation. Sol Energy 97:255–265

    Article  Google Scholar 

  • Rezk H, Fathy A (2017) A novel optimal parameters identification of triple-junction solar cell based on a recently meta-heuristic water cycle algorithm. Sol Energy 157:778–791

    Article  CAS  Google Scholar 

  • Saxena A, Kumar R, Das S (2019) β-chaotic map enabled grey wolf optimizer. Appl Soft Comput 75:84–105

    Article  Google Scholar 

  • Sen S, Ganguly S (2017) Opportunities, barriers and issues with renewable energy development–A discussion. Renew Sustain Energy Rev 69:1170–1181

    Article  Google Scholar 

  • Subudhi B, Pradhan R (2017) Bacterial foraging optimization approach to parameter extraction of a photovoltaic module. IEEE Trans Sustain Energy 9(1):381–389

    Article  Google Scholar 

  • Tran TT, Smith AD (2017) Evaluation of renewable energy technologies and their potential for technical integration and cost-effective use within the US energy sector. Renew Sustain Energy Rev 80:1372–1388

    Article  Google Scholar 

  • Trifunović-Dragišić VZ, Stanković MD, Brajović DV, Kartalović NM (2019) Estimation of the lifetime of solar cells in real conditions using accelerated aging under the influence of neutron and gamma radiation. Nucl Technol Radiat Protect 34(3):256–263

    Article  Google Scholar 

  • Wu Z, Yu D, Kang X (2017) Parameter identification of photovoltaic cell model based on improved ant lion optimizer. Energy Convers Manag 151:107–115

    Article  Google Scholar 

  • Xu S, Wang Y (2017) Parameter estimation of photovoltaic modules using a hybrid flower pollination algorithm. Energy Convers Manag 144:53–68

    Article  Google Scholar 

  • Yang, X. S., & Deb, S. (2009). Cuckoo search via Lévy flights. In 2009 World congress on nature & biologically inspired computing (NaBIC) (pp. 210-214). IEEE

  • Yousri D, Allam D, Eteiba MB, Suganthan PN (2019) Static and dynamic photovoltaic models’ parameters identification using chaotic heterogeneous comprehensive learning particle swarm optimizer variants. Energy Convers Manag 182:546–563

    Article  Google Scholar 

  • Yu K, Liang JJ, Qu BY, Chen X, Wang H (2017) Parameters identification of photovoltaic models using an improved JAYA optimization algorithm. Energy Convers Manag 150:742–753

    Article  Google Scholar 

  • Yu K, Chen X, Wang X, Wang Z (2017) Parameters identification of photovoltaic models using self-adaptive teaching-learning-based optimization. Energy Convers Manag 145:233–246

    Article  Google Scholar 

  • Yu K, Liang JJ, Qu BY, Cheng Z, Wang H (2018) Multiple learning backtracking search algorithm for estimating parameters of photovoltaic models. Appl energy 226:408–422

    Article  Google Scholar 

  • 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. Appl Energy 237:241–257

    Article  Google Scholar 

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Acknowledgement

Thapar Institute of Engineering and Technology Patiala, India, has well-equipped laboratories for effective academic and research work. The authors are really grateful to the Thapar Institute of Engineering and Technology for providing the necessary support and facilities to carry out the work presented in this manuscript.

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  1. Electrical and Instrumentation Engineering Department, Thapar Institute of Engineering and Technology Patiala, Patiala, India

    M. K. Singla & P. Nijhawan

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  1. M. K. Singla
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  2. P. Nijhawan
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Correspondence to M. K. Singla.

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Editorial responsibility: Q. Aguilar-Virgen.

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Singla, M.K., Nijhawan, P. Triple diode parameter estimation of solar PV cell using hybrid algorithm. Int. J. Environ. Sci. Technol. 19, 4265–4288 (2022). https://doi.org/10.1007/s13762-021-03286-2

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