Title :
Short term load forecasting using Multiple Linear Regression
Author :
Amral, N. ; Özveren, C.S. ; King, D.
Author_Institution :
Univ. of Abertay, Dundee
Abstract :
this paper we present an investigation for the short term (up 24 hours) load forecasting of the demand for the South Sulewesi´s (Sulewesi Island - Indonesia) Power System, using a multiple linear regression (MLR) method. After a brief analytical discussion of the technique, the usage of polynomial terms and the steps to compose the MLR model will be explained. Report on implementation of MLR algorithm using commercially available tool such as Microsoft EXCELTM will also be discussed. As a case study, historical data consisting of hourly load demand and temperatures of South Sulawesi electrical system will be used, to forecast the short term load. The results will be presented and analysed potential for improvement using alternative methods is also discussed.
Keywords :
load forecasting; polynomials; regression analysis; MLR algorithm; South Sulewesi Power System; load demand; multiple linear regression; polynomial terms; short term load forecasting; Autoregressive processes; Economic forecasting; Linear regression; Load forecasting; Load modeling; Polynomials; Power system analysis computing; Power system modeling; Shape; Weather forecasting; Multiple Linear Regression; polynomial terms;
Conference_Titel :
Universities Power Engineering Conference, 2007. UPEC 2007. 42nd International
Conference_Location :
Brighton
Print_ISBN :
978-1-905593-36-1
Electronic_ISBN :
978-1-905593-34-7
DOI :
10.1109/UPEC.2007.4469121