M. Cornec and H. Harari-Kermadec (France)
Semiparametric and Nonparametric Methods, Time-Series Models, Simulation Tools, Electric Utilities, Statistical Modelling, Electricity Market Modelling
In the early 90’s, electricity production has moved from state monopolies to competitive markets, with a new ele ment of risk: the wholesale price uncertainty. Thus, mod elling electricity-prices together with exogenous variables is crucially needed for plant scheduling, generation asset management and option pricing. Recent literature on em pirical time-series has revealed the difficulty for traditional financial parametric models to catch up with the complex features of electricity prices: mean-reversion, multi-scale seasonality, erratic extreme behaviour with fast reverting spikes. We propose to consider an empirical approach, in spired from the Bootstrap literature. We make use of the re generative structure of time-series seen as Markov chains to construct almost independent data blocks. Eventually, this approach is applied to the simulation of Powernext electric ity prices conditionnaly on temperature.
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