On the importance of the long-term seasonal component in day-ahead electricity price forecasting
Abstract
In day-ahead electricity price forecasting (EPF) the daily and weekly seasonalities are always taken into account, but the long-term seasonal component (LTSC) is believed to add unnecessary complexity to the already parameter-rich models and is generally ignored. Conducting an extensive empirical study involving state-of-the-art time series models we show that (i) decomposing a series of electricity prices into a LTSC and a stochastic component, (ii) modeling them independently and (iii) combining their forecasts can bring - contrary to a common belief - an accuracy gain compared to an approach in which a given time series model is calibrated to the prices themselves.
- Publication:
-
Energy Economics
- Pub Date:
- June 2016
- DOI:
- 10.1016/j.eneco.2016.05.009
- Bibcode:
- 2016EneEc..57..228N
- Keywords:
-
- Electricity spot price;
- Forecasting;
- Day-ahead market;
- Long-term seasonal component