A non-linear multivariable regression model for midterm energy forecasting of power systems

Tsekouras, GJ; Dialynas, EN; Hatziargyriou, ND; Kavatza, S

dc.contributor.author	Tsekouras, GJ	en
dc.contributor.author	Dialynas, EN	en
dc.contributor.author	Hatziargyriou, ND	en
dc.contributor.author	Kavatza, S	en
dc.date.accessioned	2014-03-01T01:25:43Z
dc.date.available	2014-03-01T01:25:43Z
dc.date.issued	2007	en
dc.identifier.issn	0378-7796	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/17744
dc.subject	Energy forecasting	en
dc.subject	Non-linear multivariable regression model	en
dc.subject.classification	Engineering, Electrical & Electronic	en
dc.subject.other	Electric power systems	en
dc.subject.other	Mathematical models	en
dc.subject.other	Regression analysis	en
dc.subject.other	Energy forecasting	en
dc.subject.other	Non-linear multivariable regression model	en
dc.subject.other	Electric load forecasting	en
dc.title	A non-linear multivariable regression model for midterm energy forecasting of power systems	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.epsr.2006.11.003	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.epsr.2006.11.003	en
heal.language	English	en
heal.publicationDate	2007	en
heal.abstract	The objective of this paper is to describe a non-linear multivariable regression method for midterm energy forecasting of power systems in annual time base. This method performs an extensive search in order to select the appropriate transformation functions of input variables, the weighting factors and the training periods to be used, by taking into consideration the correlation analysis of the selected input variables. With this procedure the best forecasting model is formed. Results are presented that are obtained applying the described method for the Greek power system and for different categories of low voltage customers. These results are also compared to those obtained from the application of standard regression methods. (C) 2006 Elsevier B.V. All rights reserved.	en
heal.publisher	ELSEVIER SCIENCE SA	en
heal.journalName	Electric Power Systems Research	en
dc.identifier.doi	10.1016/j.epsr.2006.11.003	en
dc.identifier.isi	ISI:000250134200005	en
dc.identifier.volume	77	en
dc.identifier.issue	12	en
dc.identifier.spage	1560	en
dc.identifier.epage	1568	en