Determining circuit model parameters from operation data for PV system degradation analysis: PVPRO Article Swipe
Baojie Li
,
Todd Karin
,
Bennet Meyers
,
Xin Chen
,
Dirk Jordan
,
Clifford Hansen
,
Bruce H. King
,
Michael G. Deceglie
,
Anubhav Jain
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1016/j.solener.2023.03.011
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1016/j.solener.2023.03.011
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. 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.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.solener.2023.03.011
- OA Status
- gold
- Cited By
- 17
- References
- 70
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4327905113
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4327905113Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1016/j.solener.2023.03.011Digital Object Identifier
- Title
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Determining circuit model parameters from operation data for PV system degradation analysis: PVPROWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-03-20Full publication date if available
- Authors
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Baojie Li, Todd Karin, Bennet Meyers, Xin Chen, Dirk Jordan, Clifford Hansen, Bruce H. King, Michael G. Deceglie, Anubhav JainList of authors in order
- Landing page
-
https://doi.org/10.1016/j.solener.2023.03.011Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
- OA URL
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https://escholarship.org/uc/item/6bc933j2Direct OA link when available
- Concepts
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Photovoltaic system, Computer science, Voltage, Irradiance, Short circuit, Equivalent series resistance, Degradation (telecommunications), Open-circuit voltage, Equivalent circuit, Electronic circuit, Electronic engineering, Electrical engineering, Engineering, Physics, Telecommunications, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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17Total citation count in OpenAlex
- Citations by year (recent)
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2025: 7, 2024: 7, 2023: 3Per-year citation counts (last 5 years)
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70Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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