Application of support vector machine and similar day method for load forecasting

Authors:
Xunming Li;Changyin Sun;Dengcai Gong
Affiliations:
College of Electrical Engineering, Hohai University, Nanjing, China;College of Electrical Engineering, Hohai University, Nanjing, China;College of Electrical Engineering, Hohai University, Nanjing, China
Venue:
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
Year:
2005

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Abstract

Support Vector Machine (SVM) is a precise and fast method for the prediction of short-term electrical load and the similar day method is a simple and direct method for load forecasting. This paper tries to combine SVM model and similar day method for next day load forecasting. The proposed method forecasts the load of next day using SVM. Then, the load curve of a similar day is selected to correct the curve forecasted by SVM, which can avoid the appearance of large forecasting error effectively. Corresponding software was developed and used to forecast the next day load in a practical power system, and the final forecasting result is accurate and reliable.