Modeling bidding curves: the linear hinges model versus the sigmo model

Author

Mateo, A. ; Sánchez-Ubeda, E.F. ; Munoz, A. ; García-González, J. ; Villar, J. ; Casado, M. ; Sáiz, A. ; García, E.J. ; González, R.

Author_Institution

Instituto de Investigacion Tecnologica, Univ. Pontificia Comillas, Madrid, Spain

Volume

1

fYear

2001

fDate

2001

Abstract

In this paper, we present and compare two approaches to model supply and demand curves of a sealed-bid auction market. Both the linear hinges model and the sigmo model are able to extract the relevant information from these bidding curves, without losing significant market information. We discuss their main similarities and important differences using a unified framework, to highlight their main strengths and weakness. A practical comparative study based on real supply functions from the Californian electricity market has been included to derive practical conclusions

Keywords

curve fitting; electricity supply industry; power system economics; Californian electricity market; automatic learning; bidding curves modeling; curve fitting; data mining; demand curves; linear hinges model; market information; neural networks; sealed-bid auction market; sigmo model; supply curves; Communication industry; Curve fitting; Data mining; Electricity supply industry; Fasteners; Gas industry; Neural networks; Samarium; Sampling methods; Supply and demand;

fLanguage

English

Publisher

ieee

Conference_Titel

Power Tech Proceedings, 2001 IEEE Porto

Conference_Location

Porto

Print_ISBN

0-7803-7139-9

Type

conf

DOI

10.1109/PTC.2001.964635

Filename

964635