Effects of Crossover Operators on Genetic Algorithms for the Extraction of Solar Cell Parameters from Noisy Data
Received: 28 January 2023 | Revised: 12 March 2023 | Accepted: 16 March 2023 | Online: 9 April 2023
Corresponding author: Ibtissam Tebbal
Abstract
This study analyzed the accuracy of solar cell modeling parameters extracted from noisy data using Genetic Algorithms (GAs). Three crossover operators (XOs) were examined, namely the Uniform (UXO), Arithmetic (AXO), and Blend (BXO) operators. The data used were an experimental benchmark cell and a simulated curve where noise levels (p) from 0 to 10% were added. For each XO, the analysis was carried out by running GAs 100 times and varying p and population size (Npop). Simulation results showed that UXO and AXO suffered from premature convergence and failed to provide parameters with good precision even with very high Npop, although they provided good fitting. In all analyzed cases, BXO outperformed UXO and AXO and the results showed that it can compete with the most efficient methods. For the benchmark curve, BXO reproduced the best RMSE found in the literature (0.7730062 mA) while providing the exact values of the parameters and a very low RMSE (1E-13) for the clean curve (p=0). For noisy curves, the errors of the extracted parameters were smaller than 10% for p lower than or equal to 6%. For higher values of p, the errors were smaller than 30%.
Keywords:
solar cells, parameter extraction, genetic algorithms, crossover operatorsDownloads
References
V. J. Chin, Z. Salam, and K. Ishaque, "Cell modelling and model parameters estimation techniques for photovoltaic simulator application: A review," Applied Energy, vol. 154, pp. 500–519, Sep. 2015. DOI: https://doi.org/10.1016/j.apenergy.2015.05.035
D. T. Cotfas, P. A. Cotfas, and S. Kaplanis, "Methods to determine the dc parameters of solar cells: A critical review," Renewable and Sustainable Energy Reviews, vol. 28, pp. 588–596, Dec. 2013. DOI: https://doi.org/10.1016/j.rser.2013.08.017
A. M. Humada, M. Hojabri, S. Mekhilef, and H. M. Hamada, "Solar cell parameters extraction based on single and double-diode models: A review," Renewable and Sustainable Energy Reviews, vol. 56, pp. 494–509, Apr. 2016. DOI: https://doi.org/10.1016/j.rser.2015.11.051
R. Abbassi, A. Abbassi, M. Jemli, and S. Chebbi, "Identification of unknown parameters of solar cell models: A comprehensive overview of available approaches," Renewable and Sustainable Energy Reviews, vol. 90, pp. 453–474, Jul. 2018. DOI: https://doi.org/10.1016/j.rser.2018.03.011
E. Batzelis, "Non-Iterative Methods for the Extraction of the Single-Diode Model Parameters of Photovoltaic Modules: A Review and Comparative Assessment," Energies, vol. 12, no. 3, Jan. 2019, Art. no. 358. DOI: https://doi.org/10.3390/en12030358
A. R. Jordehi, "Parameter estimation of solar photovoltaic (PV) cells: A review," Renewable and Sustainable Energy Reviews, vol. 61, pp. 354–371, Aug. 2016. DOI: https://doi.org/10.1016/j.rser.2016.03.049
M. Bashahu and P. Nkundabakura, "Review and tests of methods for the determination of the solar cell junction ideality factors," Solar Energy, vol. 81, no. 7, pp. 856–863, Jul. 2007. DOI: https://doi.org/10.1016/j.solener.2006.11.002
S. Bader, X. Ma, and B. Oelmann, "One-diode photovoltaic model parameters at indoor illumination levels – A comparison," Solar Energy, vol. 180, pp. 707–716, Mar. 2019. DOI: https://doi.org/10.1016/j.solener.2019.01.048
K. Bouzidi, M. Chegaar, and A. Bouhemadou, "Solar cells parameters evaluation considering the series and shunt resistance," Solar Energy Materials and Solar Cells, vol. 91, no. 18, pp. 1647–1651, Nov. 2007. DOI: https://doi.org/10.1016/j.solmat.2007.05.019
F. Caracciolo, E. Dallago, D. G. Finarelli, A. Liberale, and P. Merhej, "Single-Variable Optimization Method for Evaluating Solar Cell and Solar Module Parameters," IEEE Journal of Photovoltaics, vol. 2, no. 2, pp. 173–180, Apr. 2012. DOI: https://doi.org/10.1109/JPHOTOV.2011.2182181
X. Ma et al., "Data-Driven I–V Feature Extraction for Photovoltaic Modules," IEEE Journal of Photovoltaics, vol. 9, no. 5, pp. 1405–1412, Sep. 2019. DOI: https://doi.org/10.1109/JPHOTOV.2019.2928477
N. Maouhoub, "Photovoltaic module parameter estimation using an analytical approach and least squares method," Journal of Computational Electronics, vol. 17, no. 2, pp. 784–790, Jun. 2018. DOI: https://doi.org/10.1007/s10825-017-1121-5
D. M. Fébba, E. C. Bortoni, A. F. Oliveira, and R. M. Rubinger, "The effects of noises on metaheuristic algorithms applied to the PV parameter extraction problem," Solar Energy, vol. 201, pp. 420–436, May 2020. DOI: https://doi.org/10.1016/j.solener.2020.02.093
M. Mitchell, An Introduction to Genetic Algorithms. Cambridge, MA, USA: MIT Press, 1998. DOI: https://doi.org/10.7551/mitpress/3927.001.0001
W. Peng, Y. Zeng, H. Gong, Y. Leng, Y. Yan, and W. Hu, "Evolutionary algorithm and parameters extraction for dye-sensitised solar cells one-diode equivalent circuit model," Micro & Nano Letters, vol. 8, no. 2, pp. 86–89, 2013. DOI: https://doi.org/10.1049/mnl.2012.0806
F. J. Toledo and J. M. Blanes, "Analytical and quasi-explicit four arbitrary point method for extraction of solar cell single-diode model parameters," Renewable Energy, vol. 92, pp. 346–356, Jul. 2016. DOI: https://doi.org/10.1016/j.renene.2016.02.012
J. H. Holland, Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence. Cambridge, MA, USA: MIT Press, 1992. DOI: https://doi.org/10.7551/mitpress/1090.001.0001
K. Soleimani and J. Mazloum, "Designing a GA-Based Robust Controller For Load Frequency Control (LFC)," Engineering, Technology & Applied Science Research, vol. 8, no. 2, pp. 2633–2639, Apr. 2018. DOI: https://doi.org/10.48084/etasr.1592
V. H. Nguyen, H. Nguyen, M. T. Cao, and K. H. Le, "Performance Comparison between PSO and GA in Improving Dynamic Voltage Stability in ANFIS Controllers for STATCOM," Engineering, Technology & Applied Science Research, vol. 9, no. 6, pp. 4863–4869, Dec. 2019. DOI: https://doi.org/10.48084/etasr.3032
E. Jamalian and R. Foukerdi, "A Hybrid Data Mining Method for Customer Churn Prediction," Engineering, Technology & Applied Science Research, vol. 8, no. 3, pp. 2991–2997, Jun. 2018. DOI: https://doi.org/10.48084/etasr.2108
J. Kingdon and K. Feldman, "Genetic algorithms and applications to finance," Applied Mathematical Finance, vol. 2, no. 2, pp. 89–116, Jun. 1995. DOI: https://doi.org/10.1080/13504869500000006
R. Drechsler, Evolutionary Algorithms for VLSI CAD. Berlin, Germany: Springer Science & Business Media, 2013.
R. Drechsler and N. Drechsler, Evolutionary Algorithms for Embedded System Design. Norwell, MA, USA: Springer Science & Business Media, 2002. DOI: https://doi.org/10.1007/978-1-4615-1035-2
V. Kumar and S. K. Dhull, "Genetic Algorithm based Optimization of Uniform Circular Array," Engineering, Technology & Applied Science Research, vol. 10, no. 6, pp. 6403–6409, Dec. 2020. DOI: https://doi.org/10.48084/etasr.3792
M. Abdul-Niby, M. Alameen, A. Salhieh, and A. Radhi, "Improved Genetic and Simulating Annealing Algorithms to Solve the Traveling Salesman Problem Using Constraint Programming," Engineering, Technology & Applied Science Research, vol. 6, no. 2, pp. 927–930, Apr. 2016. DOI: https://doi.org/10.48084/etasr.627
D. E. Goldberg, Genetic Algorithms in Search, Optimization and Machine Learning, 13th ed.,Reading, MA, USA: Addison-Wesley Professional, 1989.
P. K. Singh, "A Modified Real-Coded Extended Line Crossover for Genetic Algorithm," in Social Transformation – Digital Way, Kolkata, India, 2018, pp. 702–716. DOI: https://doi.org/10.1007/978-981-13-1343-1_58
F. Herrera, M. Lozano, and A. M. Sánchez, "A taxonomy for the crossover operator for real-coded genetic algorithms: An experimental study," International Journal of Intelligent Systems, vol. 18, no. 3, pp. 309–338, 2003. DOI: https://doi.org/10.1002/int.10091
A. E. Eiben and J. E. Smith, Introduction to Evolutionary Computing. Berlin, Germany: Springer, 2015. DOI: https://doi.org/10.1007/978-3-662-44874-8
E. Wirsansky, Hands-On Genetic Algorithms with Python: Applying genetic algorithms to solve real-world deep learning and artificial intelligence problems. Birmingham, UK: Packt Publishing Ltd, 2020.
A. Sorsa, R. Peltokangas, and K. Leiviska, "Real-coded genetic algorithms and nonlinear parameter identification," in 2008 4th International IEEE Conference Intelligent Systems, Varna, Bulgaria, Sep. 2008, vol. 2. DOI: https://doi.org/10.1109/IS.2008.4670495
L. J. Eshelman and J. D. Schaffer, "Real-Coded Genetic Algorithms and Interval-Schemata," Foundations of Genetic Algorithms, vol. 2, pp. 187–202, Jan. 1993. DOI: https://doi.org/10.1016/B978-0-08-094832-4.50018-0
"GAlib: Matthew’s Genetic Algorithms Library." http://lancet.mit.edu/
ga/.
T. Easwarakhanthan, J. Bottin, I. Bouhouch, and C. Boutrit, "Nonlinear Minimization Algorithm for Determining the Solar Cell Parameters with Microcomputers," International Journal of Solar Energy, vol. 4, no. 1, pp. 1–12, Jan. 1986. DOI: https://doi.org/10.1080/01425918608909835
A. Ferhat-Hamida, Z. Ouennoughi, A. Hoffmann, and R. Weiss, "Extraction of Schottky diode parameters including parallel conductance using a vertical optimization method," Solid-State Electronics, vol. 46, no. 5, pp. 615–619, May 2002. DOI: https://doi.org/10.1016/S0038-1101(01)00337-9
J. H. Werner, "Schottky barrier and pn-junctionI/V plots — Small signal evaluation," Applied Physics A, vol. 47, no. 3, pp. 291–300, Nov. 1988. DOI: https://doi.org/10.1007/BF00615935
A. Askarzadeh and A. Rezazadeh, "Parameter identification for solar cell models using harmony search-based algorithms," Solar Energy, vol. 86, no. 11, pp. 3241–3249, Nov. 2012. DOI: https://doi.org/10.1016/j.solener.2012.08.018
S. M. Parida and P. K. Rout, "Differential evolution with dynamic control factors for parameter estimation of photovoltaic models," Journal of Computational Electronics, vol. 20, no. 1, pp. 330–343, Feb. 2021. DOI: https://doi.org/10.1007/s10825-020-01617-z
K. Ishaque, Z. Salam, H. Taheri, and A. Shamsudin, "A critical evaluation of EA computational methods for Photovoltaic cell parameter extraction based on two diode model," Solar Energy, vol. 85, no. 9, pp. 1768–1779, Sep. 2011. DOI: https://doi.org/10.1016/j.solener.2011.04.015
N. Barth, R. Jovanovic, S. Ahzi, and M. A. Khaleel, "PV panel single and double diode models: Optimization of the parameters and temperature dependence," Solar Energy Materials and Solar Cells, vol. 148, pp. 87–98, Apr. 2016. DOI: https://doi.org/10.1016/j.solmat.2015.09.003
Downloads
How to Cite
License
Copyright (c) 2023 Ibtissam Tebbal, Abdelhak Ferhat Hamida
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain the copyright and grant the journal the right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) after its publication in ETASR with an acknowledgement of its initial publication in this journal.
