An advanced model for the short-term forecast （一个先进的短期预测模型）.pdf

An advanced model for the short-term forecast of wind energy a b a b a b a S. Mathew , J. Hazra , S. A. Husain , C. Basu , L. C. DeSilva , D. Seetharam , N. Y. Voo , S. Kalyanaraman b and Z. Sulaiman a a UBD|IBM Centre, University of Brunei Darussalam, Jalan Tungku Link, Gadong BE 1410, Brunei Darussalam b Next Gen Systems Smarter Planet Solutions Department IBM Research – India, Nagawara, Bangalore - 560045, India Email: sathyajith.mathew@ubd.edu.bn Abstract: A novel short-term wind energy forecasting method, which is being developed under the UBD- IBM renewable energy modeling initiative, is described in this paper. The paper starts with a brief review on the existing forecasting methods. Prediction models based on the physical (derived from Numerical Whether Prediction models) and Time Series approaches are discussed. The prediction errors under these methods are described and the need for a reliable forecasting system is emphasized. This is followed by a detailed discussion on the UBD-IBM approach. The baseline of the proposed forecasting system is the IBM Deep Thunder. Deep thunder is a highly modified version of RAMS . This high resolution whether forecasting system can predict the local whether variations on a ‘day ahead’ basis, at high accuracy levels. For a given wind farm site, specific Deep Thunder models could be developed and calibrated using the surface measured wind data. This enables the Deep Thunder to predict the wind profile at the wind farm locations o