12 research outputs found
Modeling electricity loads in California: a continuous-time approach
In this paper we address the issue of modeling electricity loads and prices
with diffusion processes. More specifically, we study models which belong to
the class of generalized Ornstein-Uhlenbeck processes. After comparing
properties of simulated paths with those of deseasonalized data from the
California power market and performing out-of-sample forecasts we conclude
that, despite certain advantages, the analyzed continuous-time processes are
not adequate models of electricity load and price dynamics.Comment: To be published in Physica A (2001): Proceedings of the NATO ARW on
Application of Physics in Economic Modelling, Prague, Feb. 8-10, 200
Modeling electricity loads in California: ARMA models with hyperbolic noise
In this paper we address the issue of modeling and forecasting electricity loads. We apply a two-step procedure to a series of system-wide loads from the California power market. First, we remove the weekly and annual seasonalities. Then, after analyzing properties of the deseasonalized data we fit an autoregressive moving average model. The obtained residuals seem to be independent but with tails heavier than Gaussian. It turns out that the hyperbolic distribution provides an excellent fit. As a justification for our approach we supply out-of-sample forecasts. As it turns out, our method performs significantly better than the one used by the California System Operator.Electricity load; ARMA model; Heavy tails; Hyperbolic distribution; Forecast;