Abstract
Being able to quantify energy production losses in photovoltaic (PV) systems is important in order to reduce the risk associated with investing in PV. Two such loss components are degradation rates and soiling losses. However, in systems where both these phenomena exist, quantifying them is not straightforward because of their combined effect on the power output. In this article, we propose an algorithm that iteratively decomposes a performance index time series of a PV system into a soiling component, a degradation component, and a seasonal component. This makes it possible to simultaneously estimate soiling losses and degradation rates of PV systems. Bootstrapping is used to estimate confidence intervals so that both data uncertainty and model uncertainty is taken into account. Based on simulated data we show that this method makes more accurate estimates of soiling losses and degradation rates than relevant state-of-the-art methods.
Original language | American English |
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Article number | 9186286 |
Pages (from-to) | 1788-1796 |
Number of pages | 9 |
Journal | IEEE Journal of Photovoltaics |
Volume | 10 |
Issue number | 6 |
DOIs | |
State | Published - Nov 2020 |
Bibliographical note
Publisher Copyright:© 2011-2012 IEEE.
NREL Publication Number
- NREL/JA-5K00-76066
Keywords
- Data analysis
- monitoring
- photovoltaics (PV)
- PV systems
- solar power generation
- time series analysis