Journal
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
Volume 3, Issue 4, Pages 660-669Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSTE.2012.2200302
Keywords
Decision-making; density estimation; kernel; time-adaptive; uncertainty; wind power forecasting
Categories
Funding
- Fundacao para a Ciencia e Tecnologia (FCT) Ph. D. Scholarship
- U.S. Department of Energy Office of Science laboratory [DE AC02-06CH11357]
Ask authors/readers for more resources
This paper reports the application of a new kernel density estimation model based on the Nadaraya-Watson estimator, for the problem of wind power uncertainty forecasting. The new model is described, including the use of kernels specific to the wind power problem. A novel time-adaptive approach is presented. The quality of the new model is benchmarked against a splines quantile regression model currently in use in the industry. The case studies refer to two distinct wind farms in the United States and show that the new model produces better results, evaluated with suitable quality metrics such as calibration, sharpness, and skill score.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available