Integrated Wind Power Forecasting Methodology: Interval Estimation Of Wind Speed, Operation Probability Of Wind Turbine, And Conditional Expected Wind Power Output Of A Wind Farm

The article presents a novel quantitative methodology for wind farm management. The methodology starts by forecasting the time series mean and volatility of wind speed. The forecasting of wind speed mean and its volatility is built on an autoregressive moving average model with a generalized autoreg...

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Bibliographic Details
Published in:International journal of green energy Vol. 10; no. 2; pp. 151 - 176
Main Authors: Liu, Heping, Shi, Jing, Erdem, Ergin
Format: Journal Article
Language:English
Published: Philadelphia, PA Taylor & Francis Group 2013
Taylor & Francis
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ISSN:1543-5083, 1543-5075, 1543-5083
Online Access:Get full text
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Summary:The article presents a novel quantitative methodology for wind farm management. The methodology starts by forecasting the time series mean and volatility of wind speed. The forecasting of wind speed mean and its volatility is built on an autoregressive moving average model with a generalized autoregressive conditional heteroscedasticity process, namely an ARMA-GARCH model. With the prediction of wind speed mean and its volatility, the article establishes the interval estimation of wind speed which makes the prediction of wind speed more accurate and reliable. To facilitate the quantitative management of wind farm, the operation probability (OP) of wind turbine is formulated according to the interval estimation of wind speed. Based on the characteristics power curve of wind turbine, the article develops the conditional expected wind power output equation (CEWPOE). The interval estimation of wind speed, the OP of wind turbine, and the CEWPOE thus comprise an integrated methodology for the quantitative management of wind farm operations.
Bibliography:http://dx.doi.org/10.1080/15435075.2011.647170
ObjectType-Article-1
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content type line 23
ISSN:1543-5083
1543-5075
1543-5083
DOI:10.1080/15435075.2011.647170