Energy forecasting is a broad term that refers to “forecasting in the energy industry”. It is not limited to forecasting demand (load) and price of electricity, fossil fuel (natural gas, oil, coal) and renewable energy sources (RES, hydro, wind, solar). The term is used to describe both point and probabilistic (ie, interval and density).
When electricity has been regulated, utility monopolies has been used to predict the reliability of supply and demand. However, since the early 1990s, the process of deregulation and the introduction of competitive electricity markets have been reshaping the landscape of the traditionally monopolistic and government-controlled power sectors. In many countries worldwide, electricity is now traded under the market rules. At the corporate level, electricity load and price forecasts have become a fundamental input to energy companies’ decision making mechanisms. The costs of over- or undercontracting and selling can be so high that they can lead to huge financial losses and bankruptcy in the extreme case. In this respect, the utilities are the most vulnerable, since they can not afford their costs. Whereas there have been a variety of empirical studies on point forecasts (ie, the “best guess” or expected value of the spot price), probabilistic – ie, interval and density – forecasts have been investigated extensively to date. However, this is changing and nowadays both researchers and practitioners are focusing on the latter. While the Global Energy Forecasting Competition in 2012
Extreme volatility of wholesale price, which has forced market participants to hedge not only against volume risk but also against price movements. A generator, utility company or large industrial consumer who is able to forecast a price with a reasonable level of accuracy. trading. Yet, since they have been quoted by the industry, they are very hard to quantify the benefits of improving them. A rough estimate of savings from a 1% reduction in the mean absolute percentage error (MAPE) for a utility with 1GW peak load is:
The most popular subfields of energy forecasting include:
It is customary to talk about short-, medium- and long-term forecasting, but there is no consensus in the literature as to what the thresholds should actually be:
* IEEE Working Group on Energy Forecasting