Physics-based circuit parameters like series and shunt resistance are essential to provide insights into the degradation status of photovoltaic (PV) arrays. However, calculating these parameters typically requires a full current-voltage characteristic (I-V curve), the acquisition of which involves specific measurement devices and costly methods. Thus, I-V curves of the PV system level are often not available. Here this paper proposes a methodology (PVPRO) to estimate these I-V curve parameters using only operation (string-level DC voltage and current) and weather data (irradiance and temperature). PVPRO first performs multi-stage data pre-processing to remove noisy data. Next, the time-series DC data are used to fit an equivalent circuit single-diode model (SDM) to estimate the circuit parameters by minimizing the differences between the measured and estimated values. In this way, the time evolutions of the SDM parameters are obtained. We evaluate PVPRO on synthetic datasets and find an excellent estimation of both SDM and the key I-V parameters (e.g., open-circuit voltage, short-circuit current, maximum power, etc.) with an average relative error of 0.55%. The performance, especially the extracted degradation rate of parameters, is robust to various measurement noises and the presence of faults. In addition, PVPRO is applied to a 271 kW PV field system. The relative error between the real and estimated operation voltage and current is less than 1%, suggesting that degradation trends are well captured. PVPRO represents a promising open-source tool to extract the time-series degradation trends of key PV parameters from routine operation data.
Li, Baojie, et al. "Determining circuit model parameters from operation data for PV system degradation analysis: $\mathrm{PVPRO}$." Solar Energy, vol. 254, Mar. 2023. https://doi.org/10.1016/j.solener.2023.03.011
Li, Baojie, Karin, Todd, Meyers, Bennet E., Chen, Xin, Jordan, Dirk C., Hansen, Clifford W., King, Bruce H., Deceglie, Michael G., & Jain, Anubhav (2023). Determining circuit model parameters from operation data for PV system degradation analysis: $\mathrm{PVPRO}$. Solar Energy, 254. https://doi.org/10.1016/j.solener.2023.03.011
Li, Baojie, Karin, Todd, Meyers, Bennet E., et al., "Determining circuit model parameters from operation data for PV system degradation analysis: $\mathrm{PVPRO}$," Solar Energy 254 (2023), https://doi.org/10.1016/j.solener.2023.03.011
@article{osti_1968239,
author = {Li, Baojie and Karin, Todd and Meyers, Bennet E. and Chen, Xin and Jordan, Dirk C. and Hansen, Clifford W. and King, Bruce H. and Deceglie, Michael G. and Jain, Anubhav},
title = {Determining circuit model parameters from operation data for PV system degradation analysis: $\mathrm{PVPRO}$},
annote = {Physics-based circuit parameters like series and shunt resistance are essential to provide insights into the degradation status of photovoltaic (PV) arrays. However, calculating these parameters typically requires a full current-voltage characteristic (I-V curve), the acquisition of which involves specific measurement devices and costly methods. Thus, I-V curves of the PV system level are often not available. Here this paper proposes a methodology (PVPRO) to estimate these I-V curve parameters using only operation (string-level DC voltage and current) and weather data (irradiance and temperature). PVPRO first performs multi-stage data pre-processing to remove noisy data. Next, the time-series DC data are used to fit an equivalent circuit single-diode model (SDM) to estimate the circuit parameters by minimizing the differences between the measured and estimated values. In this way, the time evolutions of the SDM parameters are obtained. We evaluate PVPRO on synthetic datasets and find an excellent estimation of both SDM and the key I-V parameters (e.g., open-circuit voltage, short-circuit current, maximum power, etc.) with an average relative error of 0.55%. The performance, especially the extracted degradation rate of parameters, is robust to various measurement noises and the presence of faults. In addition, PVPRO is applied to a 271 kW PV field system. The relative error between the real and estimated operation voltage and current is less than 1%, suggesting that degradation trends are well captured. PVPRO represents a promising open-source tool to extract the time-series degradation trends of key PV parameters from routine operation data.},
doi = {10.1016/j.solener.2023.03.011},
url = {https://www.osti.gov/biblio/1968239},
journal = {Solar Energy},
issn = {ISSN 0038-092X},
volume = {254},
place = {United States},
publisher = {Elsevier},
year = {2023},
month = {03}}
National Renewable Energy Laboratory (NREL), Golden, CO (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States); Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies Office
2018 IEEE 7th World Conference on Photovoltaic Energy Conversion (WCPEC) (A Joint Conference of 45th IEEE PVSC, 28th PVSEC & 34th EU PVSEC)https://doi.org/10.1109/PVSC.2018.8547772
Journal Article
·
Mon Dec 31 23:00:00 EST 2007
· Reliability of Photovoltaic Cells, Modules, Components, and Systems: Proceedings of SPIE Conference, 11-13 August 2008, San Diego, California
·OSTI ID:947877