Author
Listed:
- Sahana L.
(TERI School of Advanced Studies, India)
- Naveen Kumaar
(National Institute of Wind Energy (NIWE), India)
- Hans Peter Waldl
(Overspeed GmbH & Co. KG, Germany)
- Prasun Kumar Das
(National Institute of Wind Energy (NIWE), India)
- Karthik Ramanathan
(National Institute of Wind Energy (NIWE), India)
- K. Balaraman
(National Institute of Wind Energy (NIWE), India)
- Indradip Mitra
(Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ), India)
Abstract
Across the world, the geographical conditions are varied, and the characteristics of dust depend on the local environmental conditions. The solar power generators must incorporate the soiling losses in their estimation for power output and therefore a methodology was developed to estimate the soiling correction factor. After extensive research, a comprehensive review was presented on the effect of soiling on performance of PV plants along with case studies of soiling experiments around the world. A soiling experiment was designed to develop the soiling correction factor. A methodology to calculate the soiling correction factor, which can be implemented in any location, was developed by analyzing the data from the soiling experiment. The effect of rainfall, humidity and wind on soiling was analyzed and documented. The performance of one 20 kWp PV plant was monitored to study the effect of weather-related parameters on the performance. The soiling correction factor varied from -1.36% to 3.67% during the period between June 2018 and June 2019 in Chennai. It was observed that the average PV conversion efficiency of the 20-kW plant was 11.75% and the average PR was 75%. It was observed that the correlation between module temperature and DC power; between humidity and DC power; between GTI and DC power varied every month. The soiling factor developed could be incorporated into the short-term day ahead solar forecasting model. The developed methodology could be applied at the any large-scale solar power plant around the world for yield assessment, designing as well as operational forecasting purposes.
Suggested Citation
Handle:
RePEc:epw:energy:v:1:y:2021:i:2:id:7007
DOI: 10.24018/ejenergy.2021.1.2.7
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