Forecasting Of Short Term Wind Power Using ARIMA Method
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2016, Vol 4, Issue 3
Abstract
Wind power, i.e., electrical energy produced making use of the wind resource, is being nowadays constantly connected to the electrical system. This has a non-negligible impact, raising issues like network stability and security of the supply. An accurate forecast of the available wind energy for the forthcoming hours is crucial, so that proper planning and scheduling of the conventional generation units can be performed. Also, with the liberalization of the electrical markets worldwide, the wind power forecasting reveals itself critical to assure that the bids are placed with a minimum possible risk. The main application for wind power forecasting is to reduce the need for balancing energy and reserve power, which are needed to integrate wind power within the balancing of supply and demand in the electricity supply system. At times of maintenance it is required to know how much power would have been generated and should be supplied by other source. This work addresses the issue of forecasting wind power with statistical model, the Autoregressive Integrated Moving Average (ARIMA). The basic theory and the respective application of these models to perform wind power prediction are presented in this paper. Furthermore, their forecasting abilities are shown with the help of graphs.
Authors and Affiliations
Prashant Pant, Achal Garg
Keywords
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