Paper Details

As we know that, the wind energy provides opportunities to generate power cheaply and cleanly without affectingthe environment. But due to rapid growth of wind power generation in the recent years, accurate wind power prediction isnecessary for reliable power system operation. This paper introduced a method of short term wind power prediction for awind power plant by using matrix factorization technique based on historical data of wind speed. We have taken ten years ofhistorical wind speed data of Rotterdam, Netherland and Schiphol, Netherlands. From this wind speed data one to nine yearof data has taken as training data set and last one year (10th year) of data has taken as test data set. The test data set hastaken as fix and the training data set has taken as different (changing the size of training data set) for measured results. Thetest results of the prediction are presented and analyzed in this thesis. The prediction proposed is shown to achieve a highaccuracy with respect to the measured data.

Tusharkumar K. Vaghasiya, Nikunj Bhatt, Francois Vallee, Fabian Lecron, Zacharie de Greve, “Wind Power Prediction by using Matrix Factorization Technique”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 4, Issue 7, pp. 351-362, July 2017.