Using On-Site Measurements to Identify and Adjust PV Single-Diode Model Parameters for Real Operating Conditions
Publication: Journal of Energy Engineering
Volume 149, Issue 1
Abstract
Photovoltaic (PV) module manufacturers specify their products’ performance under the standard test condition. However, such a condition is hardly found outdoors, that is, during actual operation of photovoltaic systems. Despite that, many modeling methods proposed in the literature rely on standard test condition data for parametric identification. This paper presents an experimental study concerning different modeling approaches for photovoltaic modules, focusing on assessing model performance in different scenarios. The goal is to assess the influence of the data used for the model parametric adjustment when predicting the maximum power point of two photovoltaic modules, allowing the most advantageous methods to be identified. By using an experimental outdoor photovoltaic platform, over 30,000 I-V curves referring to two photovoltaic modules were measured for 16 months. Different models were applied for cases where their parameters were identified using field measurements. It was found that using measurements obtained under real operating conditions to adjust the model parameters provides significantly better prediction of the maximum power in comparison to cases employing data sheet-extracted information. For the all methods and cases studied, using in-field measurements to adjust the model parameters provided average root-mean-square error of 3.4% for power predictions, whereas the average error level found when using data sheet information was 8.8%. An error level as low as 2.83% was reached by adopting the most complex model, although using a significantly simpler modeling approach provided error of 3.25%. Therefore, using field-measured data to adjust model parameters produced the best results, but increasing method complexity did not increase performance in the same scale.
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Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request and authorization from Université de Corse.
Acknowledgments
This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES), Finance Code 001. No potential competing interest was reported by the authors.
References
Abe, C. F., J. B. Dias, F. Haeberle, G. Notton, and G. A. Faggianelli. 2021. “Simplified approach to adjust IEC-60891 equation coefficients from experimental measurements with long-term validation.” IEEE J. Photovoltaics 11 (2): 496–503. https://doi.org/10.1109/JPHOTOV.2020.3043101.
Anjum, S., V. Mukherjee, and G. Mehta. 2021. “Maximum power generation from novel triangular-shaped PV array configurations under partial shading conditions.” J. Energy Eng. 147 (5): 04021033. https://doi.org/10.1061/(ASCE)EY.1943-7897.0000781.
Besheer, A. H., M. A. Eldreny, H. M. Emara, and A. Bahgat. 2019. “Photovoltaic energy system performance investigation: Case study of 5.1-kW rooftop grid tie in Egypt.” J. Energy Eng. 145 (3): 05019001. https://doi.org/10.1061/(ASCE)EY.1943-7897.0000605.
Boutana, N., A. Mellit, V. Lughi, and A. M. Pavan. 2017. “Assessment of implicit and explicit models for different photovoltaic modules technologies.” Energy 122 (Mar): 128–143. https://doi.org/10.1016/j.energy.2017.01.073.
Cannizzaro, S., M. C. Di Piazza, M. Luna, and G. Vitale. 2014a. “Generalized classification of PV modules by simplified single-diode models.” In Proc., 2014 IEEE 23rd Int. Symp. on Industrial Electronics (ISIE), 2266–2273. New York: IEEE.
Cannizzaro, S., M. C. Di Piazza, M. Luna, and G. Vitale. 2014b. “PVID: An interactive Matlab application for parameter identification of complete and simplified single-diode PV models.” In Proc., 2014 IEEE 15th Workshop on Control and Modeling for Power Electronics (COMPEL 2014). New York: IEEE.
Chatterjee, A., A. Keyhani, and D. Kapoor. 2011. “Identification of photovoltaic source models.” IEEE Trans. Energy Convers. 26 (3): 883–889. https://doi.org/10.1109/TEC.2011.2159268.
De Soto, W., S. A. Klein, and W. A. Beckman. 2006. “Improvement and validation of a model for photovoltaic array performance.” Sol. Energy 80 (1): 78–88. https://doi.org/10.1016/j.solener.2005.06.010.
Di Piazza, M. C., M. Luna, G. Petrone, and G. Spagnuolo. 2015. “About the identification of the single-diode model parameters of high-fill-factor photovoltaic modules.” In Proc., 5th Int. Conf. on Clean Electrical Power: Renewable Energy Resources Impact (ICCEP 2015), 85–91. New York: IEEE.
Di Piazza, M. C., M. Luna, G. Petrone, and G. Spagnuolo. 2017. “Translation of the single-diode PV model parameters identified by using explicit formulas.” IEEE J. Photovoltaics 7 (4): 1009–1016. https://doi.org/10.1109/JPHOTOV.2017.2699321.
Di Piazza, M. C., and G. Vitale. 2013. Photovoltaic sources. London: Springer.
Faggianelli, G. A., P. Haurant, A. Rodler, and P. Poggi. 2015. “An outdoor platform for PV ageing studies: Electrical parameters extraction from IV curves.” In Proc., ISES Solar World Congress 2015, 409–418. Freiburg, Germany: International Solar Energy Society.
Femia, N., G. Petrone, G. Spagnuolo, and M. Vitelli. 2017. Power electronics and control techniques for maximum energy harvesting in photovoltaic systems. London: Taylor & Francis.
Hejri, M., and H. Mokhtari. 2016. “On the comprehensive parametrization of the photovoltaic (PV) cells and modules.” IEEE J. Photovoltaics 7 (1): 250–258. https://doi.org/10.1109/JPHOTOV.2016.2617038.
Hosseini, S., S. Taheri, M. Farzaneh, H. Taheri, and M. Narimani. 2018. “Determination of photovoltaic characteristics in real field conditions.” IEEE J. Photovoltaics 8 (2): 572–580. https://doi.org/10.1109/JPHOTOV.2018.2797974.
IEC (International Electrotechnical Commission). 2009. IEC 60891—Photovoltaic devices—Procedures for temperature and irradiance corrections to measured I-V characteristics. Geneva: IEC.
Lappalainen, K., P. Manganiello, M. Piliougine, G. Spagnuolo, and S. Valkealahti. 2020. “Virtual sensing of photovoltaic module operating parameters.” IEEE J. Photovoltaics 10 (3): 852–862. https://doi.org/10.1109/JPHOTOV.2020.2972688.
Lineykin, S., M. Averbukh, and A. Kuperman. 2014. “An improved approach to extract the single-diode equivalent circuit parameters of a photovoltaic cell/panel.” Renewable Sustainable Energy Rev. 30 (Feb): 282–289. https://doi.org/10.1016/j.rser.2013.10.015.
Liu, J., L. Zéphyr, and C. L. Anderson. 2020. “Optimal operation of microgrids with load-differentiated demand response and renewable resources.” J. Energy Eng. 146 (4): 04020027. https://doi.org/10.1061/(ASCE)EY.1943-7897.0000670.
Petrone, G., C. A. Ramos-Paja, and G. Spagnuolo. 2017. Photovoltaic sources modeling. Chichester, UK: Wiley.
Piliougine, M., R. A. Guejia-Burbano, G. Petrone, F. J. Sánchez-Pacheco, L. Mora-López, and M. Sidrach-de-Cardona. 2021. “Parameters extraction of single diode model for degraded photovoltaic modules.” Renewable Energy 164 (Feb): 674–686. https://doi.org/10.1016/j.renene.2020.09.035.
Raza, M. Q., N. Mithulananthan, J. Li, K. Y. Lee, and H. B. Gooi. 2018. “An ensemble framework for day-ahead forecast of PV output in smart grids.” IEEE Trans. Ind. Inf. 15 (8): 4624–4634. https://doi.org/10.1109/TII.2018.2882598.
Ren, H., Q. Deng, F. Wen, J. Du, P. Yu, and J. Tian. 2021. “Joint planning of a distribution system and a charging network for electric vehicles.” J. Energy Eng. 147 (1): 04020085. https://doi.org/10.1061/(ASCE)EY.1943-7897.0000734.
Sera, D., R. Teodorescu, and P. Rodriguez. 2007. “PV panel model based on datasheet values.” In Proc., IEEE Int. Symp. on Industrial Electronics, 2392–2396. New York: IEEE.
Ye, M., X. Wang, and Y. Xu. 2009. “Parameter extraction of solar cells using particle swarm optimization.” J. Appl. Phys. 105 (9): 094502. https://doi.org/10.1063/1.3122082.
Information & Authors
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Published In
Journal of Energy Engineering
Volume 149 • Issue 1 • February 2023
Copyright
© 2022 American Society of Civil Engineers.
History
Received: May 27, 2022
Accepted: Aug 10, 2022
Published online: Oct 17, 2022
Published in print: Feb 1, 2023
Discussion open until: Mar 17, 2023
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