DocumentCode :
924028
Title :
Very short-term wind forecasting for Tasmanian power generation
Author :
Potter, Cameron W. ; Negnevitsky, Michael
Author_Institution :
Sch. of Eng., Univ. of Tasmania, Australia
Volume :
21
Issue :
2
fYear :
2006
fDate :
5/1/2006 12:00:00 AM
Firstpage :
965
Lastpage :
972
Abstract :
This paper describes very short-term wind prediction for power generation, utilizing a case study from Tasmania, Australia. Windpower presently is the fastest growing power generation sector in the world. However, windpower is intermittent. To be able to trade efficiently, make the best use of transmission line capability, and address concerns with system frequency in a re-regulated system, accurate very short-term forecasts are essential. The research introduces a novel approach-the application of an adaptive neuro-fuzzy inference system to forecasting a wind time series. Over the very short-term forecast interval, both windspeed and wind direction are important parameters. To be able to be gain the most from a forecast on this time scale, the turbines must be directed toward on oncoming wind. For this reason, this paper forecasts wind vectors, rather than windspeed or power output.
Keywords :
fuzzy neural nets; load forecasting; power engineering computing; power transmission; time series; wind power plants; Tasmanian power generation; adaptive neurofuzzy inference system; short-term wind forecasting; transmission line capability; wind power; wind time series; Australia; Frequency; Hydroelectric power generation; Oceans; Power generation; Power transmission lines; Production; Wind energy generation; Wind forecasting; Wind power generation; Adaptive neuro-fuzzy inference systems (ANFIS); intelligent systems; very short-term forecasting; windpower;
fLanguage :
English
Journal_Title :
Power Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
0885-8950
Type :
jour
DOI :
10.1109/TPWRS.2006.873421
Filename :
1626404
Link To Document :
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