Application of Markov chain models for short term generation assets valuation

• Type: Article in International Conference Proceedings Book
• Date: 2004

Authors

Wang Yu (Author) Other; Gerald B. Sheblé (Author) FEUP; Manuel António Matos (Author) FEUP

Conference proceedings International

Title: 2004 International Conference on Probabilistic Methods Applied to Power Systems

Pages: 343-348

Indexing

ISI Proceedings

ISI Web of Science

Scopus - 2 Citations

INSPEC

Scientific classification

FOS: Engineering and technology > Electrical engineering, Electronic engineering, Information engineering

CORDIS: Technological sciences > Engineering > Electrical engineering

Other information

Authenticus ID: P-007-CH5

Abstract (EN): This paper demonstrates the application of Markov chain models to valuate generation assets within deregulated electricity markets. A new framework for modeling electricity markets with Markov chain model is proposed. The advantage of the Markov chain model is that it deploys fundamental approaches to identify the key economic forces underlying the electricity markets such as demand on electricity and supplied online generation capacity. Based on this new model, real option calculations are used to valuate generation assets. Markov chain model is combined with 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 capability to analyze the impacts of demand growth patterns, competition strategies of competitors and other key economic forces.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 6