Parameter Estimation of the Bishop Photovoltaic Model Using a Genetic Algorithm
Source abstract
Abstract
Photovoltaic panels can be affected by partial shading, which causes some shaded cells to consume the energy generated by other cells of the panel. That is, shaded cells stop operating in the first quadrant and start operating in the second quadrant, with negative voltage at their terminals, causing power losses and other negative effects in the cells. The Bishop model is an accurate representation of the cells behavior at the second quadrant, but estimating its parameters is not a trivial task. Therefore, this paper presents a procedure to estimate the parameters of the Bishop model by using the Chu–Beasley optimization technique. The effectiveness of this procedure was evaluated using different accuracy measures such as RMSE and MAPE, obtaining values lower than 0.5%. In addition, the results of this study demonstrate that it is essential to estimate all the parameters of the Bishop model, illustrate the variation in the parameters according to the cell technology and show the strong influence of the shunt resistance into the behavior at the second quadrant.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Photovoltaic System Optimization Techniques · solar cell performance optimization · Silicon and Solar Cell Technologies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Facultad de Ingenierías, Instituto Tecnológico Metropolitano, Medellin 050028, Colombia
Facultad de Minas, Universidad Nacional de Colombia, Medellin 050034, Colombia
Escuela de Ingeniería Eléctrica y Electrónica, Universidad del Valle, Cali 76001, Colombia
Funding
Minciencias · Universidad Nacional de Colombia · Instituto Tecnológico Metropolitano
References (58)
Show source-provided references
1. Low voltage ride-through capability control for single-stage inverter-based grid-connected photovoltaic power plant10.1016/j.solener.2017.11.027 ↗
2. Photovoltaic materials: Present efficiencies and future challenges10.1126/science.aad4424 ↗
3. The detection of series arc fault in photovoltaic systems based on the arc current entropy10.1109/TPEL.2015.2489759 ↗
4. A novel simplified two-diode model of photovoltaic (PV) module10.1109/JPHOTOV.2014.2316371 ↗
5. Single-diode and two-diode PV cell modeling using Matlab for studying characteristics of solar cell under varying conditions10.14810/ecij.2015.4207 ↗
6. A comprehensive MATLAB Simulink PV system simulator with partial shading capability based on two-diode model10.1016/j.solener.2011.06.008 ↗
7. Barroso, J.S., Correia, J., Barth, N., Ahzi, S., and Khaleel, M. (2014, January 17–19). A PSO algorithm for the calculation of the series and shunt resistances of the PV panel one-diode model. Proceedings of the 2014 International Renewable and Sustainable Energy Conference (IRSEC), Ouarzazate, Morocco.
8. A genetic algorithm for identifying the single diode model parameters of a photovoltaic panel10.1016/j.matcom.2015.10.008 ↗
9. Parameter estimation of photovoltaic models via cuckoo search10.1155/2013/362619 ↗
10. Characteristic output of PV systems under partial shading or mismatch conditions10.1016/j.solener.2014.09.048 ↗
11. Hosseini, S., Taheri, S., Farzaneh, M., and Taheri, H. (2016, January 12–14). An approach to precise modeling of photovoltaic modules under changing environmental conditions. Proceedings of the 2016 IEEE Electrical Power and Energy Conference (EPEC), Ottawa, ON, Canada.10.1109/EPEC.2016.7771772 ↗
12. New seven parameters model for amorphous silicon and thin film PV modules based on solar irradiance10.1016/j.solener.2016.08.056 ↗
13. A mathematical modeling framework to evaluate the performance of single diode and double diode based SPV systems10.1016/j.egyr.2016.06.004 ↗
14. Study of bypass diodes configuration on PV modules10.1016/j.apenergy.2009.01.020 ↗
15. Author Correction: Comparative study with practical validation of photovoltaic monocrystalline module for single and double diode models10.1038/s41598-021-01357-5 ↗
16. Modeling, analysis and comparison of solar photovoltaic array configurations under partial shading conditions10.1016/j.solener.2015.07.039 ↗
17. Discrete I–V model for partially shaded PV-arrays10.1016/j.solener.2014.01.037 ↗
18. Computer simulation of the effects of electrical mismatches in photovoltaic cell interconnection circuits10.1016/0379-6787(88)90059-2 ↗
19. Simulation of I–V characteristics of a PV module with shaded PV cells10.1016/S0927-0248(02)00134-4 ↗
20. King, D., Dudley, J., and Boyson, W. (1996). PVSIM ©: A Simulation Program for Photovoltaic Cells, Modules, and Arrays, Sandia National Labs.. Technical Report.10.1109/PVSC.1996.564370 ↗
21. A general modeling method for I–V characteristics of geometrically and electrically configured photovoltaic arrays10.1016/j.enconman.2011.07.011 ↗
22. Photovoltaic module parameter estimation using an analytical approach and least squares method10.1007/s10825-017-1121-5 ↗
23. A comparison of different one-diode models for the representation of I–V characteristic of a PV cell10.1016/j.rser.2014.01.027 ↗
24. Nunes, H., Pombo, J., Fermeiro, J., Mariano, S., and do Rosário Calado, M. (2017, January 5). Particle Swarm Optimization for photovoltaic model identification. Proceedings of the 2017 International Young Engineers Forum (YEF-ECE), Costa da Caparica, Portugal.10.1109/YEF-ECE.2017.7935640 ↗
25. Grasshopper optimization algorithm for parameter estimation of photovoltaic modules based on the single diode model10.1007/s40095-020-00342-4 ↗
26. Benkercha, R., Moulahoum, S., Colak, I., and Taghezouit, B. (2016, January 25–28). PV module parameters extraction with maximum power point estimation based on flower pollination algorithm. Proceedings of the 2016 IEEE International Power Electronics and Motion Control Conference (PEMC), Varna, Bulgaria.10.1109/EPEPEMC.2016.7752038 ↗
27. Petrone, G., Ramos-Paja, C.A., and Spagnuolo, G. (2017). Photovoltaic Sources Modeling, John Wiley & Sons.10.1002/9781118755877 ↗
28. An approach to extract the parameters of solar cells from their illuminated IV curves using the Lambert W function10.3906/fiz-1309-7 ↗
29. Cell modelling and model parameters estimation techniques for photovoltaic simulator application: A review10.1016/j.apenergy.2015.05.035 ↗
30. Solar cell parameters estimation from illuminated I-V characteristic using linear slope equations and Newton-Raphson technique10.1063/1.4803748 ↗
31. Identification of photovoltaic source models10.1109/TEC.2011.2159268 ↗
32. A novel approach to parameter estimation of photovoltaic systems using hybridized optimizer10.1016/j.enconman.2019.01.102 ↗
33. Comparison of different metaheuristic algorithms for parameter identification of photovoltaic cell/module10.1063/1.4822054 ↗
34. Characterization of PV panel and global optimization of its model parameters using genetic algorithm10.1016/j.enconman.2013.03.033 ↗
35. Parameters extraction of photovoltaic sources based on experimental data10.1049/iet-rpg.2018.5418 ↗
36. Hamadi, S.A., Chouder, A., Rezaoui, M.M., Motahhir, S., and Kaddouri, A.M. (2021). Improved Hybrid Parameters Extraction of a PV Module Using a Moth Flame Algorithm. Sci. Rep., 10.10.3390/electronics10222798 ↗
37. Tobón, A., Peláez-Restrepo, J., Montano, J., Durango, M., Herrera, J., and Ibeas, A. (2020). MPPT of a photovoltaic panels array with partial shading using the IPSM with implementation both in simulation as in hardware. Energies, 13.10.3390/en13040815 ↗
38. Estimación de los parámetros del modelo de un solo diodo del módulo fotovoltaico aplicando el método de optimización basado en búsqueda de patrones mejorado10.22395/rium.v20n38a1 ↗
39. The Shockley five-parameter model of a solar cell: A short note10.1080/20421338.2015.1038007 ↗
40. Rohde-Schwarz (2021, September 01). R&S®RTE OSCILLOSCOPE: Specifications. Available online: https://scdn.rohde-schwarz.com/ur/pws/dl_downloads/dl_common_library/dl_brochures_and_datasheets/pdf_1/RTE_dat-sw_en_3607-1494-22_v2500.pdf.
41. A population classification evolution algorithm for the parameter extraction of solar cell models10.1155/2016/2174573 ↗
42. Parameter extraction of solar cell models using repaired adaptive differential evolution10.1016/j.solener.2013.05.007 ↗
43. Extraction of solar cell modelling parameters using differential evolution algorithm
44. Parameter optimization of single-diode model of photovoltaic cell using memetic algorithm10.1155/2015/963562 ↗
45. Vélez-Sánchez, J., Bastidas-Rodríguez, J.D., Ramos-Paja, C.A., González Montoya, D., and Trejos-Grisales, L.A. (2019). A Non-Invasive Procedure for Estimating the Exponential Model Parameters of Bypass Diodes in Photovoltaic Modules. Energies, 12.10.3390/en12020303 ↗
46. Parameters identification of photovoltaic models using hybrid adaptive Nelder-Mead simplex algorithm based on eagle strategy10.1016/j.apenergy.2016.08.083 ↗
47. Parameter extraction of solar photovoltaic modules using penalty-based differential evolution10.1016/j.apenergy.2012.05.017 ↗
48. Ma, J. (2014). Optimization Approaches for Parameter Estimation and Maximum Power Point Tracking (MPPT) of Photovoltaic Systems. [Ph.D. Thesis, University of Liverpool].
49. A comparative study of evolutionary algorithms and adapting control parameters for estimating the parameters of a single-diode photovoltaic module’s model10.1016/j.renene.2016.04.072 ↗
50. Grisales-Noreña, L.F., Gonzalez Montoya, D., and Ramos-Paja, C.A. (2018). Optimal sizing and location of distributed generators based on PBIL and PSO techniques. Energies, 11.10.3390/en11041018 ↗
51. Montano, J., Mejia, A.F.T., Rosales Muñoz, A.A., Andrade, F., Garzon Rivera, O.D., and Palomeque, J.M. (2021). Salp Swarm Optimization Algorithm for Estimating the Parameters of Photovoltaic Panels Based on the Three-Diode Model. Electronics, 10.10.3390/electronics10243123 ↗
52. Effects of shadowing on photovoltaic module performance10.1002/pip.780 ↗
53. An explicit PV string model based on the lambert W function and simplified MPP expressions for operation under partial shading10.1109/TSTE.2013.2282168 ↗
54. Fezzani, A., Mahammed, I.H., and Said, S. (2014, January 21–23). MATLAB-based modeling of shading effects in photovoltaic arrays. Proceedings of the 2014 15th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA), Hammamet, Tunisia.10.1109/STA.2014.7086686 ↗
55. A method for simulating large PV arrays that include reverse biased cells10.1016/j.apenergy.2014.02.052 ↗
56. Belhadj, C.A., Banat, I., and Deriche, M. (2017, January 28–31). A detailed analysis of photovoltaic panel hot spot phenomena based on the bishop model. Proceedings of the 2017 14th International Multi-Conference on Systems, Signals & Devices (SSD), Marrakech, Morocco.10.1109/SSD.2017.8166924 ↗
57. Outdoor study of partial shading effects on different PV modules technologies10.1016/j.egypro.2017.11.016 ↗
58. Dynamic electro-thermal modeling of solar cells and modules10.1016/j.solener.2018.12.067 ↗