Title :
A Method for Short-Term Wind Power Prediction With Multiple Observation Points
Author :
Khalid, Muhammad ; Savkin, Andrey V.
Author_Institution :
Sch. of Electr. Eng. & Telecommun., Univ. of New South Wales, Sydney, NSW, Australia
fDate :
5/1/2012 12:00:00 AM
Abstract :
This paper presents a method to improve the short-term wind power prediction at a given turbine using information from numerical weather prediction and from multiple observation points, which correspond to the locations of nearby turbines at a particular wind farm site. The prediction of wind power is achieved in two stages; in the first stage wind speed is predicted using our proposed method. In the second stage, the wind speed to output power conversion is accomplished using power curve model. The proposed wind power prediction method is tested using real measurements and NWP data from one of the wind farm sites in Australia. The performance is compared with the persistence and Grey predictor model in terms of Mean Absolute Error and Root Mean Square Error.
Keywords :
mean square error methods; power conversion; wind power plants; wind turbines; Australia; grey predictor; mean absolute error; multiple observation points; numerical weather prediction; power conversion; power curve; root mean square error; short-term wind power prediction; turbine; wind farm; wind speed; Data models; Mathematical model; Predictive models; Wind farms; Wind forecasting; Wind power generation; Wind turbines; Adaptive filtering; networked systems; prediction; renewable energy; wind power;
Journal_Title :
Power Systems, IEEE Transactions on
DOI :
10.1109/TPWRS.2011.2160295