A Novel Method to Extract Single-Diode PV Parameters Based on Datasheet Values
Abstract
Very few manufacturers that are providing a wide range of graphical data necessary to use high-performance predictive tools for PV systems. On the other hand, reliable graphical data require precise laboratory measurements that increase manufacturing costs. Furthermore, most of the methods used to determine photovoltaic performance require iterative techniques, additional mandatory information and users with a certain level of knowledge. For this reason, PV system designers have to choose between the use of cheap PV modules, lacking in technical data, and the reliable energy predictions that are possible only if the current–voltage characteristics are provided by the PV module manufacturers.
This paper presents a novel method to extract the single diode five parameters model for different manufacturer's modules using the minimum set of technical data that are usually provided by all manufacturers. The proposed procedure uses an accurate and easy method that does not require iterative techniques, other obligatory information or users with special knowledge but only datasheet values from a technical catalog of photovoltaic modules to simulate photovoltaic performance. The method uses an empirical relationship that enables to calculate the initial values of series and shunt resistances and extracts the parameters of the model from datasheet values provided by manufacturers only.
The capability of the proposed model to calculate the current–voltage characteristics was tested by comparing the results with data measured by different manufacturers’ panel models (mono-crystalline and poly-crystalline) silicon modules. The method was also compared with other similar methods. The results of the new model application confirm the reliability of the procedure.
References
1. Рефаат А., Элгамал M., Коровкин Н.В. Новая централизованная топология фотоэлектрических преобразователей, работающих с сетью, оптимизированная для условий частичного затенения. – Электричество, 2019, №7, с. 59–68.
2. Рефаат А., Осман М. Х., Коровкин Н.В. Оптимальное извлечение энергии из неоднородно стареющего фотоэлектрического массива с использованием сумматора тока. – Электричество, 2019, №10, с. 54–60.
3. Averbukh M., Lineykin S., Kuperman A. Obtaining small photovoltaic array operational curves for arbitrary cell temperatures and solar irradiation densities from standard conditions data, Prog. Photovolt. Res. Appl. 21 (2012), pp.1016–1024.
4. Sera D., Teodorescu R., Rodriguez P. PV panel model based on datasheet values. – Proc. IEEE Int. Symp. Ind. Electron., 2007, pp. 2392–2396.
5. Ismail M.S., Moghavvemi M., Mahlia T.M.I. Characterization of PV panel and global optimization of its model parameters using genetic algorithm. – Energy Conversion and Management, 2013, 73, pp. 10–25.
6. Tina G.M., Ventura C. Evaluation and validation of an electrical model of photovoltaic module based on manufacturer measurement. – Sustainability in Energy and Buildings, 2013, vol. 22, pp. 15–24.
7. Etienne Saloux, Alberto Teyssedou, Mikhaïl Sorin. Explicit model of photovoltaic panels to determine voltages and currents at the maximum power point. – Solar Energy, 2011, vol.85, No.5, pp.713–722.
8. El-Sayed M. I., Mohamed M. A. E. H., Osman M. H. A novel parameter estimation of a PV model. – 2016 IEEE 43rd Photovoltaic Specialists Conference, 2016, pp. 3027–3032.
9. Senturk A., Eke R. A new method to simulate photovoltaic performance of crystalline silicon photovoltaic modules based on datasheet values. – Renewable energy, 2017, 103, pp. 58–69.
10. Mohammad H., Mokhtari H. On the comprehensive parametrization of the photovoltaic (PV) cells and modules. – IEEE Journal of Photovoltaics, 2017, 7.1, pp. 250–258.
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1. Refaat A., Elgamal M., Korovkin N.V. A novel grid connected photovoltaic centralized inverter topology to improve the power harvest during partial shading condition. – Electricity, 2019, No. 7, pp. 59–68.
2. Refaat A., Osman M. H., Korovkin N. V. Optimum Power Extraction from Non-Uniform Aged PV Array Using Current Collector Optimizer Topology. – Electricity, 2019, No. 10, pp.54–60.
3. Averbukh M., Lineykin S., Kuperman A. Obtaining small photovoltaic array operational curves for arbitrary cell temperatures and solar irradiation densities from standard conditions data, Prog. Photovolt. Res. Appl. 21 (2012), pp.1016–1024.
4. Sera D., Teodorescu R., Rodriguez P. PV panel model based on datasheet values. – Proc. IEEE Int. Symp. Ind. Electron., 2007, pp. 2392–2396.
5. Ismail M.S., Moghavvemi M., Mahlia T.M.I. Characterization of PV panel and global optimization of its model parameters using genetic algorithm. – Energy Conversion and Management, 2013, 73, pp. 10–25.
6. Tina G.M., Ventura C. Evaluation and validation of an electrical model of photovoltaic module based on manufacturer measurement. – Sustainability in Energy and Buildings, 2013, vol. 22, pp. 15–24.
7. Etienne Saloux, Alberto Teyssedou, Mikhaïl Sorin. Explicit model of photovoltaic panels to determine voltages and currents at the maximum power point. – Solar Energy, 2011, vol.85, No.5, pp.713–722.
8. El-Sayed M. I., Mohamed M. A. E. H., Osman M. H. A novel parameter estimation of a PV model. – 2016 IEEE 43rd Photovoltaic Specialists Conference, 2016, pp. 3027–3032.
9. Senturk A., Eke R. A new method to simulate photovoltaic performance of crystalline silicon photovoltaic modules based on datasheet values. – Renewable energy, 2017, 103, pp. 58–69.
10. Mohammad H., Mokhtari H. On the comprehensive parametrization of the photovoltaic (PV) cells and modules. – IEEE Journal of Photovoltaics, 2017, 7.1, pp. 250–258.
