Wind speed and direction forecasting for wind power generation using ARIMA model
|dc.identifier.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.|
© 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.
|dc.title||Wind speed and direction forecasting for wind power generation using ARIMA model|
|dcterms.source.title||2017 Australasian Universities Power Engineering Conference, AUPEC 2017|
|dcterms.source.series||2017 Australasian Universities Power Engineering Conference, AUPEC 2017|
|dcterms.source.conference||Australasian Universities Power Engineering Conference, AUPEC 2017|
|curtin.department||School of Electrical Engineering, Computing and Mathematical Science (EECMS)|
|curtin.accessStatus||Fulltext not available|
Files in this item
There are no files associated with this item.