Direction Dependent Power Curves for Wind Power Prediction: A Case Study

Muhammad Khalid, Andrey V. Savkin

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


This paper describes the significance of empirical direction dependent power curves for wind power prediction at a wind farm site. The results, based on empirical studies, demonstrate that use of directional power curves for wind farm power prediction can lead to an accuracy improvement in the final power prediction of the wind farm. In general, the influence of wind direction on power output is less significant as compared with wind speed due to the fact that turbines are directed to face the wind during its operation. However, maximum wind power potential could not be achieved due to the specific site conditions and important factors like wake effects, environmental effects, hysteresis, and curtailments in the wind farms. Therefore, it is important to model the local conditions of the wind farm; directional power curves are one of the techniques to maximize the expected power production. This case study is based on real-world measurements from a selected wind farm site in Australia.

Original languageEnglish
Title of host publicationSustainability in Energy and Buildings
Subtitle of host publicationResults of the Second International Conference onSustainability in Energy and Buildings (SEB'10)
EditorsJain Lakhmi, Howlett Robert, Lee Shaun
Number of pages7
StatePublished - 2011
Externally publishedYes

Publication series

NameSmart Innovation, Systems and Technologies
ISSN (Print)2190-3018
ISSN (Electronic)2190-3026

ASJC Scopus subject areas

  • General Decision Sciences
  • General Computer Science


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