HEAL DSpace

Artificial intelligence in short term electric load forecasting: A state-of-the-art survey for the researcher

DSpace/Manakin Repository

Show simple item record

dc.contributor.author Metaxiotis, K en
dc.contributor.author Kagiannas, A en
dc.contributor.author Askounis, D en
dc.contributor.author Psarras, J en
dc.date.accessioned 2014-03-01T01:18:41Z
dc.date.available 2014-03-01T01:18:41Z
dc.date.issued 2003 en
dc.identifier.issn 0196-8904 en
dc.identifier.uri https://dspace.lib.ntua.gr/xmlui/handle/123456789/15155
dc.subject Artificial intelligence en
dc.subject Electric load forecasting en
dc.subject Energy en
dc.subject.classification Thermodynamics en
dc.subject.classification Energy & Fuels en
dc.subject.classification Mechanics en
dc.subject.classification Physics, Nuclear en
dc.subject.other Artificial intelligence en
dc.subject.other Energy conservation en
dc.subject.other Problem solving en
dc.subject.other Research en
dc.subject.other Short term electric load forecasting (STELF) en
dc.subject.other Electric load forecasting en
dc.title Artificial intelligence in short term electric load forecasting: A state-of-the-art survey for the researcher en
heal.type journalArticle en
heal.identifier.primary 10.1016/S0196-8904(02)00148-6 en
heal.identifier.secondary http://dx.doi.org/10.1016/S0196-8904(02)00148-6 en
heal.language English en
heal.publicationDate 2003 en
heal.abstract Intelligent solutions, based on artificial intelligence (AI) technologies, to solve complicated practical problems in various sectors are becoming more and more widespread nowadays. AI-based systems are being developed and deployed worldwide in myriad applications, mainly because of their symbolic reasoning, flexibility and explanation capabilities. This paper provides an overview for the researcher of AI technologies, as well as their current use in the field of short term electric load forecasting (STELF). The history of AI in STELF is outlined, leading to a discussion of the various approaches as well as the current research directions. The paper concludes by sharing thoughts and estimations on AI future prospects in this area. This review reveals that although still regarded as a novel methodology, AI technologies are shown to have matured to the point of offering real practical benefits in many of their applications. (C) 2002 Elsevier Science Ltd. All rights reserved. en
heal.publisher PERGAMON-ELSEVIER SCIENCE LTD en
heal.journalName Energy Conversion and Management en
dc.identifier.doi 10.1016/S0196-8904(02)00148-6 en
dc.identifier.isi ISI:000180612100012 en
dc.identifier.volume 44 en
dc.identifier.issue 9 en
dc.identifier.spage 1525 en
dc.identifier.epage 1534 en


Files in this item

Files Size Format View

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record