Very short-term wind forecasting for Tasmanian power generation

被引:253
作者
Potter, CW [1 ]
Negnevitsky, M [1 ]
机构
[1] Univ Tasmania, Sch Engn, Hobart, Tas 7001, Australia
关键词
adaptive neuro-fuzzy inference systems (ANFIS); intelligent systems; very short-term forecasting; windpower;
D O I
10.1109/TPWRS.2006.873421
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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.
引用
收藏
页码:965 / 972
页数:8
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