| Title |
The Development of the Short-Term Wind Power Forecasting System using Support Vector Regression |
| DOI |
http://dx.doi.org/10.5207/JIEIE.2017.31.9.104 |
| Keywords |
Support Vector Machine(SVM) ; Support Vector Regression(SVR) ; Wind Power Forecasting ; Short-Term Forecasting ; Machine Learning |
| Abstract |
Short-term wind power forecasting is a technique which informs system operators of how much wind power can be expected at a specific time. Due to the increasing penetration of wind generating resource into power grids, short-term wind power forecasting is becoming an important issue for grid integration analysis. Generally, regression model is used to forecast short-term wind generation. Regression method is an approach for modeling the relevance between a dependent variable and one or more independent variables. In order to enhance wind power forecasting errors, we propose the short-term wind power forecasting using support vector machine based on linear regression. |