Market Clearing Price Forecasting in Deregulated Electricity Markets Using Adaptively Trained Neural Networks

Georgilakis, P

dc.contributor.author	Georgilakis, P	en
dc.date.accessioned	2014-03-01T02:50:16Z
dc.date.available	2014-03-01T02:50:16Z
dc.date.issued	2006	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/35002
dc.subject	Artificial Neural Network	en
dc.subject	Bidding Strategies	en
dc.subject	Electricity Market	en
dc.subject	Market Participation	en
dc.subject	Power Market	en
dc.subject	Profitability	en
dc.subject	Neural Network	en
dc.title	Market Clearing Price Forecasting in Deregulated Electricity Markets Using Adaptively Trained Neural Networks	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1007/11752912_8	en
heal.identifier.secondary	http://dx.doi.org/10.1007/11752912_8	en
heal.publicationDate	2006	en
heal.abstract	The market clearing prices in deregulated electricity markets are volatile. Good market clearing price forecasting will help producers and consumers to prepare their corresponding bidding strategies so as to maximize their profits. Market clearing price prediction is a difficult task since bidding strategies used by market participants are complicated and various uncertainties interact in an intricate way. This paper proposes	en
heal.journalName	Hellenic Conference on Artificial Intelligence	en
dc.identifier.doi	10.1007/11752912_8	en