A Critical Review of Wind Power Forecasting Methods-Past, Present and Future

被引:237
作者
Hanifi, Shahram [1 ]
Liu, Xiaolei [1 ]
Lin, Zi [2 ,3 ]
Lotfian, Saeid [2 ]
机构
[1] Univ Glasgow, James Watt Sch Engn, Glasgow G12 8QQ, Lanark, Scotland
[2] Univ Strathclyde, Dept Naval Architecture Ocean & Marine Engn, Glasgow G4 0LZ, Lanark, Scotland
[3] Northumbria Univ, Dept Mech & Construct Engn, Newcastle Upon Tyne NE1 8ST, Tyne & Wear, England
基金
英国工程与自然科学研究理事会;
关键词
wind power forecasting; artificial neural networks; hybrid methods; performance evaluation; ARTIFICIAL NEURAL-NETWORK; ENERGY; SPEED; BENEFITS; SYSTEM;
D O I
10.3390/en13153764
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The largest obstacle that suppresses the increase of wind power penetration within the power grid is uncertainties and fluctuations in wind speeds. Therefore, accurate wind power forecasting is a challenging task, which can significantly impact the effective operation of power systems. Wind power forecasting is also vital for planning unit commitment, maintenance scheduling and profit maximisation of power traders. The current development of cost-effective operation and maintenance methods for modern wind turbines benefits from the advancement of effective and accurate wind power forecasting approaches. This paper systematically reviewed the state-of-the-art approaches of wind power forecasting with regard to physical, statistical (time series and artificial neural networks) and hybrid methods, including factors that affect accuracy and computational time in the predictive modelling efforts. Besides, this study provided a guideline for wind power forecasting process screening, allowing the wind turbine/farm operators to identify the most appropriate predictive methods based on time horizons, input features, computational time, error measurements, etc. More specifically, further recommendations for the research community of wind power forecasting were proposed based on reviewed literature.
引用
收藏
页数:24
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