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APPLICATION OF MARKOV CHAIN MODELS FOR SHORT-TERM GENERATION ASSETS VALUATION

Published online by Cambridge University Press:  12 December 2005

Wang Yu ,
Gerald B. Sheblé  and
Manuel António Matos
Wang Yu
Affiliation:
Department of Electrical Engineering, Iowa State University, Ames, IA, 50011, E-mail: wangy@iastate.edu
Gerald B. Sheblé
Affiliation:
Department of Electrical Engineering, Iowa State University, Ames, IA, 50011, E-mail: gsheble@iastate.edu
Manuel António Matos
Affiliation:
Department of Electrical and Computer Engineering, Faculdade de Engenharia, Universidade do Porto, Porto, 4200-465, Portugal, E-mail: mmato@inescporto.pt
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Abstract

This paper valuates generation assets within deregulated electricity markets. A new framework for modeling electricity markets with a Markov chain model is proposed. The Markov chain model captures the fundamental economic forces underlying the electricity markets such as demand on electricity and supplied online generation capacity. Based on this new model, a real option analysis is adopted to valuate generation assets. The Markov chain model is combined with a binomial tree to approximate the stochastic movement of prices on both electric energy and ancillary services, which are driven by the market forces. A detailed example is presented. This method is shown to provide optimal operation policies and market values of generation assets. This method also provides means to analyze the impacts of demand growth patterns, competition strategies of competitors, and other key economic forces.

Type
Research Article
Information
Probability in the Engineering and Informational Sciences , Volume 20 , Issue 1 , January 2006 , pp. 127 - 141
Copyright
© 2006 Cambridge University Press

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References

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