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