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Power generation expansion planning in an autonomous island system using multi-objective programming: The case of Milos island

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dc.contributor.author Kourempele, M en
dc.contributor.author Mavrotas, G en
dc.contributor.author Geronikolou, L en
dc.contributor.author Rozakis, S en
dc.date.accessioned 2014-03-01T01:34:20Z
dc.date.available 2014-03-01T01:34:20Z
dc.date.issued 2010 en
dc.identifier.issn 11092858 en
dc.identifier.uri https://dspace.lib.ntua.gr/xmlui/handle/123456789/20698
dc.subject Augmented ε-constraint method en
dc.subject Energy regional planning en
dc.subject Fuzzy demand en
dc.subject Multi-objective mixed integer linear programming en
dc.subject Reference point en
dc.title Power generation expansion planning in an autonomous island system using multi-objective programming: The case of Milos island en
heal.type journalArticle en
heal.identifier.primary 10.1007/s12351-009-0063-5 en
heal.identifier.secondary http://dx.doi.org/10.1007/s12351-009-0063-5 en
heal.publicationDate 2010 en
heal.abstract This paper presents the application of multiple objective linear programming for power generation expansion planning on Milos island. The model considers those economic and environmental objectives which typically conflict (cost minimization vs. CO2 emission reduction maximization) subject to a number of constraints. Due to uncertainties in future power demand, the latter is handled as a fuzzy parameter. Fuzziness is dealt with by the addition of a third objective function, the maximization of the degree of demand satisfaction. The MOLP model developed is solved in two ways. First, the use of the augmented ε-constraint method which produces the trade offs between cost and CO2 for different values of the degree of demand satisfaction, and second the reference point framework, a generation and an interactive method, respectively. In the second approach decision makers set their aspiration levels concerning the different criteria, converging after a number of iterations in a compromise solution, whereas in the augmented ε-constraint generation method the decision makers have to choose their preferred solution between all the efficient points depicted in the trade-offs. A comparative analysis of the above methods concludes the paper, highlighting advantages and shortcomings. © Springer-Verlag 2009. en
heal.journalName Operational Research en
dc.identifier.doi 10.1007/s12351-009-0063-5 en
dc.identifier.volume 10 en
dc.identifier.issue 1 en
dc.identifier.spage 109 en
dc.identifier.epage 132 en


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