Summary:
This paper presents a fuel prices scenario generator in the frame of a simulation tool developed to support risk analysis in a competitive electricity environment. The tool feeds different exogenous risk factors to a wholesale electricity market model to perform a statistical analysis of the results. As the different fuel series that are studied, such as the oil or gas ones, present stochastic volatility and strong correlation among them, a multivariate Generalized Autoregressive Conditional Heteroskedastic model has been designed in order to allow the generation of future fuel prices paths. The model makes use of a decomposition method to simplify the consideration of the multidimensional conditional covariance. An example of its application with real data is also presented.
Keywords: Fuels; Monte Carlo methods; Power system modeling; Risk analysis; Stochastic processes
JCR Impact Factor and WoS quartile: 0,238 (2004); 5,200 - Q1 (2022)
DOI reference:
https://doi.org/10.1016/j.ijepes.2003.10.007
Published on paper: May 2004.
Published on-line: December 2003.
Citation:
C. Batlle, J. Barquín, Fuel prices scenario generation based on a multivariate GARCH model for risk analysis in a wholesale electricity market. International Journal of Electrical Power & Energy Systems. Vol. 26, nº. 4, pp. 273 - 280, May 2004. [Online: December 2003]
