| Resumo: | Electricity is a very special commodity since it is economically non-storable, and thus requiring a constant balance between production and consumption. At the corporate level, electricity price forecasts have become a fundamental input to energy companies’ decision making mechanisms [22, 45]. Electric utilities are higly vulnerable to economical crisis, since they generally cannot pass their excess costs on the wholesale market to the retail consumers [77] and, since the price depends on variables like weather (temperature, wind speed, precipitation, etc.) and the intensity of business and everyday activities (on-peak vs. off-peak hours, weekdays vs. weekends, holidays and near-holidays, etc.) it shows specific dynamics not observed in any other market, exhibiting seasonality at the daily, weekly and annual levels, and abrupt, short-lived and generally unanticipated price spikes. These extreme price volatility make price forecasts from a few hours to a few months ahead to become of particular interest to power portfolio managers. An utility company or large industrial consumer who is able to accurately forecast the wholesale prices and it’s volatility, can adjust its bidding strategy and its own production/consumption schedule in order to reduce the risk or maximize the profits in day-ahead trading. In this work I discuss the dynamics of the Iberian electricity day-ahead market (OMIE), review the state-of-the-art forecasting techniques and introduce a new approach to Electricity Price Forecasting, by forecasting the underlying dynamics, the market demand/supply curves. With this method it is possible to predict not only the electricity prices for the next hours, but also the market curves, which can then be used for risk management and a more accurate schedule of generation units. I analyze the model results and benchmark them against other models in the industry.
|
|---|