Energy planning in buildings under uncertainty in fuel costs: The case of a hotel unit in Greece

Mavrotas, G; Demertzis, H; Meintani, A; Diakoulaki, D

dc.contributor.author	Mavrotas, G	en
dc.contributor.author	Demertzis, H	en
dc.contributor.author	Meintani, A	en
dc.contributor.author	Diakoulaki, D	en
dc.date.accessioned	2014-03-01T01:18:56Z
dc.date.available	2014-03-01T01:18:56Z
dc.date.issued	2003	en
dc.identifier.issn	0196-8904	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/15272
dc.subject	Energy planning	en
dc.subject	Fuzzy numbers	en
dc.subject	Hotels	en
dc.subject	Multiple objective programming	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	Buildings	en
dc.subject.other	Cost benefit analysis	en
dc.subject.other	Fuzzy sets	en
dc.subject.other	Hotels	en
dc.subject.other	Linear programming	en
dc.subject.other	Energy planning	en
dc.subject.other	Energy policy	en
dc.title	Energy planning in buildings under uncertainty in fuel costs: The case of a hotel unit in Greece	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/S0196-8904(02)00119-X	en
heal.identifier.secondary	http://dx.doi.org/10.1016/S0196-8904(02)00119-X	en
heal.language	English	en
heal.publicationDate	2003	en
heal.abstract	Energy planning for individual large energy consumers becomes increasingly important due to several supply options competing and/or complementing each other and the high uncertainty associated with fuel prices. Hotel units are among the largest energy consumers in the building sector, where energy planning may greatly facilitate investment decisions for efficiently meeting energy demand. The present paper presents a linear programming model, including both continuous and integer variables, which represent energy flows and discrete energy technologies, respectively. Furthermore, the model comprises fuzzy parameters in order to handle adequately the uncertainties regarding energy costs. The obtained fuzzy linear programming model is then translated into the equivalent multiple objective linear programming model, which provides a set of efficient solutions, each one characterized by quantification of the risk associated with the uncertain energy costs. The proposed methodology is illustrated with a case study referring to a large hotel unit located nearby Athens. (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)00119-X	en
dc.identifier.isi	ISI:000180411900008	en
dc.identifier.volume	44	en
dc.identifier.issue	8	en
dc.identifier.spage	1303	en
dc.identifier.epage	1321	en