A Method for Searching for Defective Solar Panels in Telemetry Data of a Power Plant Based on the Results of a Digital Twin
https://doi.org/10.35596/1729-7648-2023-21-6-113-120
Abstract
Searching for faulty, and therefore operating in abnormal mode, solar panels at a power plant is an urgent task in the context of the development and growth of the share of solar energy in electricity generation. The research is aimed at developing and evaluating the effectiveness of a new methodology and software algorithm for searching for anomalies in the operation of solar panels based on the results of a digital twin created and trained using telemetry data from a solar power plant. The methodology is based on studies of deviations in power values at the point of maximum efficient operation of the solar panel, calculated by the digital twin, from the average statistical values for the power plant. Using the proposed methodology, over six months of direct observations, 16 anomalies in the operation of the solar panels of the power plant were discovered and confirmed. It has been established that when analyzing deviations of normalized power values at the maximum power point PN, it is possible to detect solar panels that have defects or operate with loss of efficiency.
Keywords
About the Author
K. S. DzikBelarus
Dzik Kanstantin Sergeevich, Postgraduate at the Department of Informatics
220018, Minsk, Yakubovskogo St., 15-1-358
Tel.: +375 29 625-10-56
References
1. Dorin P., Farcas C., Ciocan I. (2008) Modelling and Simulation of Photovoltaic Cells. ACTA Technica Napocensis. 49 (1), 42–47.
2. Adeniyi O. D., Ali D. A., Olutoye M. A., Adeniyi M. I., Azeez O. S., Otaru A. J., Eniafe B. O. (2016) Modeling and Simulation of Energy Recovery from a Photovoltaic Solar Cell. Nigerian Journal of Technological Research. 11, 26–31.
3. Salmi T., Bouzguenda M., Gastli A., Masmoudi A. (2012) MATLAB/Simulink Based Modelling of Solar Photovoltaic Cell. International Journal of Renewable Energy Research. 2 (2), 213–218.
4. Tina G., Cosentino F., Ventura C. (2016) Monitoring and Diagnostics of Photovoltaic Power Plants. Renewable Energy in the Service of Mankind. 2, 505–516.
5. Ibbini M., Adawi A. (2019) Analysis and Design of a Maximum Power Point Tracker for a Stand-Alone Photo Voltaic System Using Simscape. International Journal of Advanced Trends in Computer Science and Engineering. 8 (1), 54–57.
6. Leopoldo G.-A., Belem S., Otniel P.-R., Juan C. Á.-V., Pánfilo R. M.-R., Rigoberto M.-M. (2019) Flatness-Based Control for the Maximum Power Point Tracking in a Photovoltaic System. Energies. 12, 1843–1862.
7. Asimov R. M., Valevich S. V., Kruse I., Asipovich V. S. (2019) Virtual Laboratory for Testing of Solar Power Plants in Big Data Analysis. In Collection of Materials of the V International Scientific and Practical Conference “Big Data And Advanced Analytics”. March 13–14. Minsk, Belarusian State University of Informatics and Radioelectronics. 61–65.
8. Valevich S., Asimov R., Kruse I., Asipovich V. (2020) Digital Twin For PV Module Fault Detection. Journal of Engineering Science. XXVII (4), 80–87.
9. Vаlevich S. V., Kruse I., Asimov R. M., Asipovich V. S. (2020) Information Support for Monitoring of Solar Power Station’s Technical State. Information Technologies. 26 (10), 594–601 (in Russian).
10. Pei Tingting, Hao Xiaohong (2019) A Fault Detection Method for Photovoltaic Systems Based on Voltage and Current Observation and Evaluation. Energies. 12 (9), 1712.
11. Vаlevich S. V., Dzik C. S., Pilecki I. I., Kruse I., Asimov R. M., Asipovich V. S. (2023) Methods and Programs for Searching for Anomalies in the Telemetry Data of a Solar Power Plant. Informatics. 20 (2), 96–110 (in Russian).
Review
For citations:
Dzik K.S. A Method for Searching for Defective Solar Panels in Telemetry Data of a Power Plant Based on the Results of a Digital Twin. Doklady BGUIR. 2023;21(6):113-120. (In Russ.) https://doi.org/10.35596/1729-7648-2023-21-6-113-120