Abstract
Soiling profiles are commonly assumed to have sawtooth shapes, made of alternating cleaning events and soiling deposition periods. The rates at which soiling deposit on the PV modules are considered to be constant for each period. In reality, events such as changes in climatic conditions can lead to a sudden variation in soiling deposition rate. These changes cannot be reproduced if cleanings are the only events modelled to extract soiling profiles directly from PV performance data. For this reason, in this work, the use of change points and segmented regression is proposed to improve the extraction of soiling profiles through the model of up to two deposition rates per period in between cleanings. The results show that the quality of soiling extraction can be enhanced compared to a cleanings-only identification approach if both cleanings and change points are considered.
Original language | American English |
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Pages | 595-598 |
Number of pages | 4 |
DOIs | |
State | Published - 14 Jun 2020 |
Event | 47th IEEE Photovoltaic Specialists Conference, PVSC 2020 - Calgary, Canada Duration: 15 Jun 2020 → 21 Aug 2020 |
Conference
Conference | 47th IEEE Photovoltaic Specialists Conference, PVSC 2020 |
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Country/Territory | Canada |
City | Calgary |
Period | 15/06/20 → 21/08/20 |
Bibliographical note
Publisher Copyright:© 2020 IEEE.
NREL Publication Number
- NREL/CP-5K00-79411
Keywords
- Monitoring
- Photovoltaic Systems
- Regression Analysis
- Soiling
- Time Series Analysis