TY - GEN
T1 - Solar radiation forecast with machine learning
AU - Shao, Xiaoyan
AU - Lu, Siyuan
AU - Hamann, Hendrik F.
N1 - Publisher Copyright:
© 2016 FTFMD.
PY - 2016/8/15
Y1 - 2016/8/15
N2 - Renewable energy forecasting becomes increasingly important as the contribution of solar/wind power production to the electrical power grid constantly increases. Significant improvement in forecasting accuracy has been demonstrated by developing more sophisticated solar irradiance forecasting models using statistics and/or numerical weather predictions. In this presentation, we report the development of a machine-learning based multi-model blending approach for statistically combing multiple meteorological models to improve the accuracy of solar power forecasting. The system leverages upon multiple existing physical models for prediction including numerous atmospheric and cloud prediction models based on satellite imagery as well as numerical weather prediction (NWP) products.
AB - Renewable energy forecasting becomes increasingly important as the contribution of solar/wind power production to the electrical power grid constantly increases. Significant improvement in forecasting accuracy has been demonstrated by developing more sophisticated solar irradiance forecasting models using statistics and/or numerical weather predictions. In this presentation, we report the development of a machine-learning based multi-model blending approach for statistically combing multiple meteorological models to improve the accuracy of solar power forecasting. The system leverages upon multiple existing physical models for prediction including numerous atmospheric and cloud prediction models based on satellite imagery as well as numerical weather prediction (NWP) products.
UR - https://www.scopus.com/pages/publications/84987653149
U2 - 10.1109/AM-FPD.2016.7543604
DO - 10.1109/AM-FPD.2016.7543604
M3 - Conference contribution
AN - SCOPUS:84987653149
T3 - Proceedings of AM-FPD 2016 - 23rd International Workshop on Active-Matrix Flatpanel Displays and Devices: TFT Technologies and FPD Materials
SP - 19
EP - 22
BT - Proceedings of AM-FPD 2016 - 23rd International Workshop on Active-Matrix Flatpanel Displays and Devices
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 23rd International Workshop on Active-Matrix Flatpanel Displays and Devices, AM-FPD 2016
Y2 - 6 July 2016 through 8 July 2016
ER -