Electricity demand load forecasting of the Hellenic power system using an ARMA model

Pappas, S; Ekonomou, L; Karampelas, P; Karamousantas, D; Katsikas, S; Chatzarakis, G; Skafidas, P

dc.contributor.author	Pappas, S	en
dc.contributor.author	Ekonomou, L	en
dc.contributor.author	Karampelas, P	en
dc.contributor.author	Karamousantas, D	en
dc.contributor.author	Katsikas, S	en
dc.contributor.author	Chatzarakis, G	en
dc.contributor.author	Skafidas, P	en
dc.date.accessioned	2014-03-01T01:59:17Z
dc.date.available	2014-03-01T01:59:17Z
dc.date.issued	2010	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/28888
dc.subject	akaike information criterion	en
dc.subject	arma model	en
dc.subject	bayesian information criterion	en
dc.subject	Electricity Consumption	en
dc.subject	Electricity Prices	en
dc.subject	Information Criterion	en
dc.subject	Load Forecasting	en
dc.subject	Model Specification	en
dc.subject	Modeling and Forecasting	en
dc.subject	Order Selection	en
dc.subject	Parameter Estimation	en
dc.subject	Power System	en
dc.subject	Time Series Analysis	en
dc.subject	kalman filter	en
dc.title	Electricity demand load forecasting of the Hellenic power system using an ARMA model	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.epsr.2009.09.006	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.epsr.2009.09.006	en
heal.publicationDate	2010	en
heal.abstract	Effective modeling and forecasting requires the efficient use of the information contained in the available data so that essential data properties can be extracted and projected into the future. As far as electricity demand load forecasting is concerned time series analysis has the advantage of being statistically adaptive to data characteristics compared to econometric methods which quite often are subject	en
heal.journalName	Electric Power Systems Research	en
dc.identifier.doi	10.1016/j.epsr.2009.09.006	en