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    Wind speed and direction forecasting for wind power generation using ARIMA model

    Access Status
    Fulltext not available
    Authors
    Yatiyana, E.
    Rajakaruna, Sumedha
    Ghosh, Arindam
    Date
    2018
    Type
    Conference Paper
    
    Metadata
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    Citation
    Yatiyana, E. and Rajakaruna, S. and Ghosh, A. 2018. Wind speed and direction forecasting for wind power generation using ARIMA model, Australasian Universities Power Engineering Conference, AUPEC 2017, pp. 1-6: IEEE.
    Source Title
    2017 Australasian Universities Power Engineering Conference, AUPEC 2017
    Source Conference
    Australasian Universities Power Engineering Conference, AUPEC 2017
    DOI
    10.1109/AUPEC.2017.8282494
    ISBN
    9781538626474
    School
    School of Electrical Engineering, Computing and Mathematical Science (EECMS)
    URI
    http://hdl.handle.net/20.500.11937/72615
    Collection
    • Curtin Research Publications
    Abstract

    © 2017 IEEE. Wind Power plays a major role in both large utility grids and small microgrids due to a wide range of socio-economic benefits. Due to this reason, current research has an emerging trend to enhance its reliability and usability. Highly random nature of the wind speed and direction leads to having a poor accuracy of wind power forecasting and thereby poor reliability, increased cost and reduced efficiency of electrical systems. Most updated studies are focused mainly on wind speed, and their prediction errors are above the industry expectations. In this paper, both the wind speed and wind direction are analyzed to develop a statistical model based forecasting technique. This paper uses an Autoregressive Integrated Moving Average method to build the estimating model for wind measured in Western Australia to yield the forecasted values. The resultant model can be used to improve the system reliability, quality of the wind power generation system.

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