Critical Comparison of MPPT Standards in Photovoltaic Systems: EN 50530, IEC 62816, and ASTM E2848 Comparación Crítica de Normas MPPT en Sistemas Fotovoltaicos: EN 50530, IEC 62816 y ASTM E2848

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Carlos David Amaya Jaramillo
Adriano Efraín Pérez Toapanta

Abstract

Over one hundred Maximum Power Point Tracking (MPPT) algorithms have been published; however, the lack of a unified evaluation framework leads to inconsistent performance assessments. The international standards EN 50530, IEC 62816, and ASTM E2848 are the primary initiatives to specify quantification methods for tracking quality. Yet, critical discrepancies exist in their scope, metrics, test profiles, and uncertainty treatment. This article conducts a comprehensive comparative analysis that identifies 14 evaluation criteria, thoroughly examines the mathematical formulation of each performance metric, and discusses the limitations that hinder a clear classification of algorithms. The main findings include: (i) the only standard that requires specific irradiance ramps is EN 50530 (0.5–100 W/(m² s)) for dynamic testing; (ii) the IEC 62816 standard defines the "tracking energy loss" (εTL) and establishes an A-to-E classification; (iii) the ASTM E2848 standard uses multiple regression to estimate expected power, an approach that reduces accuracy in dynamic conditions.

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How to Cite
Amaya Jaramillo, C. D., & Pérez Toapanta, A. E. (2025). Critical Comparison of MPPT Standards in Photovoltaic Systems: EN 50530, IEC 62816, and ASTM E2848: Comparación Crítica de Normas MPPT en Sistemas Fotovoltaicos: EN 50530, IEC 62816 y ASTM E2848. Boletín Científico Ideas Y Voces, 5(3), Pág. 233 – 250. https://doi.org/10.60100/bciv.v5i3.251
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References

Bhatnagar, P., & Nema, R. K. (2013). Maximum power point tracking control techniques: State-of-the-art in photovoltaic applications. Renewable and Sustainable Energy Reviews, 23, 224–241. https://doi.org/10.1016/J.RSER.2013.02.011

Bhatti, S., Khan, A. R., Zoha, A., Hussain, S., & Ghannam, R. (2024). A Machine Learning Frontier for Predicting LCOE of Photovoltaic System Economics. Advanced Energy and Sustainability Research, 5(8). https://doi.org/10.1002/aesr.202300178

Bortoni, E. C., Guardia, E. C., Guerrini, A. B., Lopes, E. A. S., Ferreira, T. V. V., & Neto, R. A. (2022). Probabilistic and Possibilistic Approaches for LCOE Appraisal of Renewable Generation. 2022 IEEE Power & Energy Society General Meeting (PESGM), 01–05. https://doi.org/10.1109/PESGM48719.2022.9917132

Chmielowiec, K., Topolski, Ł., Piszczek, A., Rodziewicz, T., & Hanzelka, Z. (2022). Study on Energy Efficiency and Harmonic Emission of Photovoltaic Inverters. Energies, 15(8). https://doi.org/10.3390/en15082857

Deline, C., Dobos, A., Janzou, S., Meydbray, J., & Donovan, M. (2013). A simplified model of uniform shading in large photovoltaic arrays. Solar Energy, 96, 274–282. https://doi.org/10.1016/J.SOLENER.2013.07.008

Dirnberger, D., Blackburn, G., Müller, B., & Reise, C. (2015). On the impact of solar spectral irradiance on the yield of different PV technologies. Solar Energy Materials and Solar Cells, 132, 431–442. https://doi.org/10.1016/J.SOLMAT.2014.09.034

Elbaksawi, O., Elminshawy, N. A. S., Diab, S., Eltamaly, A. M., Mahmoud, A., & Elhadidy, H. (2024). Innovative metaheuristic algorithm with comparative analysis of MPPT for 5.5 kW floating photovoltaic system. Process Safety and Environmental Protection, 185, 1072–1088. https://doi.org/10.1016/J.PSEP.2024.03.082

Eltawil, M. A., & Zhao, Z. (2013). MPPT techniques for photovoltaic applications. Renewable and Sustainable Energy Reviews, 25, 793–813. https://doi.org/10.1016/J.RSER.2013.05.022

Endiz, M. S., Gökkuş, G., Coşgun, A. E., & Demir, H. (2025). A Review of Traditional and Advanced MPPT Approaches for PV Systems Under Uniformly Insolation and Partially Shaded Conditions. In Applied Sciences (Switzerland) (Vol. 15, Issue 3). Multidisciplinary Digital Publishing Institute (MDPI). https://doi.org/10.3390/app15031031

Femia, N., Petrone, G., Spagnuolo, G., & Vitelli, M. (2017). Power Electronics and Control Techniques for Maximum Energy Harvesting in Photovoltaic Systems. CRC Press. https://doi.org/10.1201/b14303

Fusch, P., Fusch, G. E., & Ness, L. R. (2018). Denzin’s Paradigm Shift: Revisiting Triangulation in Qualitative Research. Journal of Social Change, 10(1). https://doi.org/10.5590/josc.2018.10.1.02

Ishaque, K., Salam, Z., Amjad, M., & Mekhilef, S. (2012). An improved particle swarm optimization (PSO)-based MPPT for PV with reduced steady-state oscillation. IEEE Transactions on Power Electronics, 27(8), 3627–3638. https://doi.org/10.1109/TPEL.2012.2185713

Kamarzaman, N. A., & Tan, C. W. (2014). A comprehensive review of maximum power point tracking algorithms for photovoltaic systems. Renewable and Sustainable Energy Reviews, 37, 585–598. https://doi.org/10.1016/J.RSER.2014.05.045

Kratochvil, J., Boyson, W., & King, D. (2004). Photovoltaic array performance model. https://doi.org/10.2172/919131

Landis, J. R., & Koch, G. G. (1977). The Measurement of Observer Agreement for Categorical Data. Biometrics, 33(1), 159. https://doi.org/10.2307/2529310

Lo Brano, V., Orioli, A., Ciulla, G., & Di Gangi, A. (2010). An improved five-parameter model for photovoltaic modules. Solar Energy Materials and Solar Cells, 94(8), 1358–1370. https://doi.org/10.1016/j.solmat.2010.04.003

Logeswaran, T., & SenthilKumar, A. (2014). A Review of Maximum Power Point Tracking Algorithms for Photovoltaic Systems under Uniform and Non-uniform Irradiances. Energy Procedia, 54, 228–235. https://doi.org/10.1016/J.EGYPRO.2014.07.266

Marion, B., Adelstein, J., Boyle, K., Hayden, H., Hammond, B., Fletcher, T., Canada, B., Narang, D., Kimber, A., Mitchell, L., Rich, G., & Townsend, T. (2005). Performance parameters for grid-connected PV systems. Conference Record of the Thirty-First IEEE Photovoltaic Specialists Conference, 2005., 1601–1606. https://doi.org/10.1109/PVSC.2005.1488451

Ordóñez, F., Fasquelle, T., Dollet, A., & Vossier, A. (2023). Making solar electricity dispatchable: A technical and economic assessment of the main conversion and storage technologies. IScience, 26(11). https://doi.org/10.1016/j.isci.2023.108028

Peiris, K., Elphick, S., David, J., & Robinson, D. (2024). Impact of Multiple Grid-Connected Solar PV Inverters on Harmonics in the High-Frequency Range. Energies , 17(11). https://doi.org/10.3390/en17112639

Pilawa-Podgurski, R. C. N., & Perreault, D. J. (2013). Submodule integrated distributed maximum power point tracking for solar photovoltaic applications. IEEE Transactions on Power Electronics, 28(6), 2957–2967. https://doi.org/10.1109/TPEL.2012.2220861

Sangwongwanich, A., & Blaabjerg, F. (2019). Mitigation of Interharmonics in PV Systems With Maximum Power Point Tracking Modification. IEEE Transactions on Power Electronics, 34(9), 8279–8282. https://doi.org/10.1109/TPEL.2019.2902880

Verma, D., Nema, S., Shandilya, A. M., & Dash, S. K. (2016a). Maximum power point tracking (MPPT) techniques: Recapitulation in solar photovoltaic systems. Renewable and Sustainable Energy Reviews, 54, 1018–1034. https://doi.org/10.1016/J.RSER.2015.10.068

Verma, D., Nema, S., Shandilya, A. M., & Dash, S. K. (2016b). Maximum power point tracking (MPPT) techniques: Recapitulation in solar photovoltaic systems. Renewable and Sustainable Energy Reviews, 54, 1018–1034. https://doi.org/10.1016/J.RSER.2015.10.068

Wiegmann, P. M., de Vries, H. J., & Blind, K. (2017). Multi-mode standardisation: A critical review and a research agenda. Research Policy, 46(8), 1370–1386. https://doi.org/10.1016/J.RESPOL.2017.06.002