NDLI: Curve fitting with Mixed Integer Programming: Applications to electricity markets models

Content Provider	IEEE Xplore Digital Library
Author	Campos, F.A. Villar, J. Diaz, C.
Copyright Year	2011
Description	Author affiliation: Instituto de Investigación Tecnológica, Escuela Técnica Superior de Ingenieros-ICAI, Universidad Pontificia Comillas, Alberto Aguilera 23, 28015 Madrid, Spain (Campos, F.A.; Villar, J.; Diaz, C.)
Abstract	Long term electricity markets models tend to use simplified representations of both the demand and the generation units, to reduce the amount of input data and decision variables used, and also to decrease their execution times. On the one hand, hourly demand curves are usually simplified into a reduced set of non-chronological demand levels, each one representing hours with similar demand values. On the other hand, individual generation units are condensed into technologies grouping their costs curves by similarity in different appropriated technological cost mappings. This paper proposes several novel Mixed Integer Programming models to solve these two curve-fitting problems when the approximating function is a Piece-Wise Linear Function. By means of two real cases study it shows that the approximation approach has real applicability since it does not significantly compromise the traditional system representation.
Starting Page	238
Ending Page	243
File Size	740366
Page Count	6
File Format	PDF
ISBN	9781612842851
e-ISBN	9781612842868
e-ISBN	9781612842844
DOI	10.1109/EEM.2011.5953016
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-05-25
Publisher Place	Croatia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Biological system modeling Chebyshev approximation Approximation error Electricity supply industry Mathematical model Curve fitting
Content Type	Text
Resource Type	Article

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