AleaSoft developed an energy forecasting methodology that is unique, guaranteeing the highest degree of efficiency and accuracy. This methodology has been in use for more than 22 years in some of the most important companies in the energy sector in Europe. More than 400 models that have been obtained with this methodology are in service in different European markets.
AleaSoft supplies electricity and gas markets prices forecasts in the short, medium and long term in most European markets. Main electricity markets: MIBEL (Spain and Portugal), EPEX SPOT (France, Germany and Austria, Belgium, The Netherlands and Switzerland), IPEX (Italy), Nord Pool Spot (Norway, Sweden, Finland, Denmark, Estonia, Lithuania and Latvia), SEM (Ireland), POLPX (Poland), ROPEX (Romania) and N2EX (United Kingdom), providing services to traders, retailers, large consumers, utilities, renewable energy developers, banks and investment funds.
AleaSoft complements the energy prices forecasts with forecasts of other related variables that are also of interest for those interested in the market, such as forecasts of commodity prices (oil, gas, coal, CO2 emissions), demand, production by technology (wind, hydro and solar), meteorological variables, exchange rate, economic indices, and in general of all the variables that influence the energy price.
For the long‑term prices forecasts, the use of renewable energy production penetration scenarios, especially of wind and photovoltaic energy, is of particular interest.
The prices forecasting reports have as output the expected prices values and the confidence bands with the associated probabilities.
AleaSoft offers the following energy price forecasting products and services:
AleaSoft offers price forecasting services at the long term for European markets. Price forecasts have an hourly granularity and 30 years of horizon. The main variables that are taken into account to generate the price forecasts are:
In addition, plans to increase the interconnection capacity between the main European electricity markets are taken into account and thus the convergence of market prices is taken into account.
Forecasts are generated using all registered data available at that time.
The forecasts take into account the scenarios for the dissemination of new and existing technologies (electric vehicles, batteries, self-consumption, heat pumps, etc.) and their impact on the demand volume and the hourly profile of the price curve.
The forecasts include the maximum and minimum confidence bands with annual granularity. The calculation of the bands is made using a sufficiently large number of price simulations generated from random simulations of the explanatory variables, taking into account the probability associated to each simulation of the variables. The variability and the probability of occurrence of each simulation of the variables is be determined by their past behavior and by the realistic future scenarios of the variable.
In a PPA (Power Purchase Agreement), having reliable price forecasts at the long-term is essential for all parties involved: investors, manufacturers, installers, managers, producers and consumers.