A data-driven approach to automate cleaning event detection in PV systems for accurate quantification of soiling loss across varying installation capacities
Authors:
- Shoubhik DeSDShoubhik De
- Bipasha GhoshBGBipasha Ghosh
- Narendra ShiradkarNSNarendra Shiradkar
- Anil KottantharayilAKAnil Kottantharayil
- 5 February 2026
- journal article
- Published by Elsevier in Solar Energy
- Vol. 308
Abstract
No abstract availableFunding Information
- Ministry of New and Renewable Energy India (313-21/1112022-SolarR)
- National Centre for Photovoltaic Research and Education
This publication has 55 references indexed in Scilit:
- Trend‐Based Predictive Maintenance and Fault Detection Analytics for Photovoltaic Power PlantsSolar RRL, 2024
- Automated detection of photovoltaic cleaning events: A performance comparison of techniques as applied to a broad set of labeled photovoltaic data setsProgress in Photovoltaics: Research and Applications, 2022
- Analysis and mitigation of nonuniform soiling distribution on utility‐scale photovoltaic systemsProgress in Photovoltaics: Research and Applications, 2021
- Monitoring photovoltaic soiling: assessment, challenges, and perspectives of current and potential strategiesiScience, 2021
- Economics of seasonal photovoltaic soiling and cleaning optimization scenariosEnergy, 2021
- Electrostatic force distribution on an electrodynamic screenJournal of Electrostatics, 2016
- Dust effects on PV array performance: in‐field observations with non‐uniform patternsProgress in Photovoltaics: Research and Applications, 2013
- Performance ratio revisited: is PR > 90% realistic?Progress in Photovoltaics: Research and Applications, 2012
- Soiling and other optical losses in solar‐tracking PV plants in navarraProgress in Photovoltaics: Research and Applications, 2011
- A Rank-Invariant Method of Linear and Polynomial Regression Analysis1992