TY - JOUR
T1 - A transferable turbidity estimation method for estimating clear-sky solar irradiance
AU - Chen, Shanlin
AU - Liang, Zhaojian
AU - Dong, Peixin
AU - Guo, Su
AU - Li, Mengying
N1 - Funding Information:
The authors gratefully acknowledge the partial support from The Hong Kong Polytechnic University Grants P0035016 and P0038816 , and the partial support from Jiangsu Province Science and Technology Department Grant BZ2021057 .
Publisher Copyright:
© 2023 Elsevier Ltd
PY - 2023/4
Y1 - 2023/4
N2 - A transferable turbidity estimation method is proposed for estimating the turbidity and clear-sky solar irradiance. Instead of using on-site irradiance measurements (i.e., the local model), a transferable model is developed involving stations with sufficient information, and then applied at locations with limited data availability. Compared with the local method, the transferable model yields results with slightly higher discrepancies regrading normalized root mean squared error (nRMSE, 2.80% vs 2.75%). When compared with the Ineichen–Perez (PVLIB) model, the nRMSE of clear-sky global horizontal irradiance (GHIcs) estimation is reduced from 4.99% to 2.44%, and the normalized mean bias error (nMBE) is improved from -3.37% to 0.57%. The GHIcs estimation is comparable with physical models (i.e., McClear and REST2), where the McClear produces a nRMSE of 3.32% and the nMBE is 2.10%, while the REST2 generates results with an nRMSE of 2.55% and an nMBE of 1.30%. We further compare aforementioned models for day-ahead GHIcs forecasts using a day persistent way. GHIcs forecast from the transferable method has slightly lower discrepancies of nRMSE and nMBE than the physical models. Considering the complexity of physical models, the transferable turbidity estimation method with comparable performance demonstrates valuable potential for solar resourcing and forecasting applications.
AB - A transferable turbidity estimation method is proposed for estimating the turbidity and clear-sky solar irradiance. Instead of using on-site irradiance measurements (i.e., the local model), a transferable model is developed involving stations with sufficient information, and then applied at locations with limited data availability. Compared with the local method, the transferable model yields results with slightly higher discrepancies regrading normalized root mean squared error (nRMSE, 2.80% vs 2.75%). When compared with the Ineichen–Perez (PVLIB) model, the nRMSE of clear-sky global horizontal irradiance (GHIcs) estimation is reduced from 4.99% to 2.44%, and the normalized mean bias error (nMBE) is improved from -3.37% to 0.57%. The GHIcs estimation is comparable with physical models (i.e., McClear and REST2), where the McClear produces a nRMSE of 3.32% and the nMBE is 2.10%, while the REST2 generates results with an nRMSE of 2.55% and an nMBE of 1.30%. We further compare aforementioned models for day-ahead GHIcs forecasts using a day persistent way. GHIcs forecast from the transferable method has slightly lower discrepancies of nRMSE and nMBE than the physical models. Considering the complexity of physical models, the transferable turbidity estimation method with comparable performance demonstrates valuable potential for solar resourcing and forecasting applications.
KW - Clear-sky irradiance
KW - Solar resourcing and forecasting
KW - Transferable model
KW - Turbidity estimation
UR - http://www.scopus.com/inward/record.url?scp=85148746955&partnerID=8YFLogxK
U2 - 10.1016/j.renene.2023.02.096
DO - 10.1016/j.renene.2023.02.096
M3 - Journal article
AN - SCOPUS:85148746955
SN - 0960-1481
VL - 206
SP - 635
EP - 644
JO - Renewable Energy
JF - Renewable Energy
ER -