China’s growing demand for oil is significantly changing the international geopolitics of energy, especially in the Asian Pacific region. The recent growth in oil consumption, combined with forecasts of increased oil imports (especially from the Middle East), have led to deep concern among...

In this paper we study simple time series models and assess their forecasting performance. In particular we calibrate ARMA and ARMAX (where the exogenous variable is the system load) processes. Models are tested on a time series of California power market system prices and loads from the period...

We give the reader a tour of good energy optimization models that explicitly deal with uncertainty. The uncertainty usually stems from unpredictability of demand and/or prices of energy, or from resource availability and prices. Since most energy investments or operations involve irreversible...

For many economic problems standard statistical analysis, based on the notion of stationarity, is not adequate. These include modeling seasonal decisions of consumers, forecasting business cycles and - as we show in the present article - modeling wholesale power market prices. We apply standard...

OIL AS AN ENERGY PROPELLER, IS THE LARGEST INTERNATIONALLY TRADED COMMODITY THAT SHOWS HIGHLY VISIBLE INTERPLAY OF POLITICS AND ECONOMICS IN THE DETERMINATION OF ITS INVESTMENT, PRODUCTION, TRADE AND PRICING POLICIES. THIS UNIQUENESS, NO DOUBT DEMANDS A WELL ARTICULATED OIL POLICY FOR AN OIL...

The value of a gas fired power depends on the spark spread, defined as the difference between the price of electricity and the cost of gas used for the generation of electricity. We model the spark spread using a two-factor model, allowing mean-reversion in short-term variations and uncertainty...

We address the issue of modeling spot electricity prices with regime switching models. After reviewing the stylized facts about power markets we propose and fit various models to spot prices from the Nordic power exchange. Afterwards we assess their performance by comparing simulated and market...

In this paper we study two statistical approaches to load forecasting. Both of them model electricity load as a sum of two components – a deterministic (representing seasonalities) and a stochastic (representing noise). They differ in the choice of the seasonality reduction method. Model A...