AleaSoft developed an energy forecasting methodology that is unique, guaranteeing the highest degree of efficiency and accuracy. AleaSoft is leader in the field of energy demand forecasting, principally focusing on electricity and gas. AleaSoft´s energy demand forecast products are available at short, medium and long term. AleaSoft supplies a great number of European markets with energy demand forecasting, and its goal is to cater all European markets. Its products have satisfied the necessities of all actors involved in the European energy market, specifically Transmission System Operator, distributors and electricity companies. AleaSoft’s ambition is to expand its global outreach, by providing energy demand forecasts in the American and Asian markets. The AleaSoft team has developed an exclusive technology, merging statistical methodologies and artificial intelligence. AleaSoft´s energy forecasting models are unique, guaranteeing the highest degree of efficiency and accuracy.
AleaSoft offers the following energy demand forecasting products and services:
The AleaSoft’s short‑term energy demand forecasts have a 10‑day horizon with an hourly interval. The forecasts are offered in product format and in service format.
The product format consists of the installation of an application that works automatically, both for updating the data and for obtaining the forecasts.
The service format consists of the daily sending of the updated forecasts of the demand and of the main explanatory variables.
The main explanatory variables used in short‑term demand forecasts are the climatological data, such as temperature and thermal sensation, and the labour.
The AleaSoft’s mid‑term energy demand forecasts have a horizon of up to 3 years with an hourly interval. The forecasts are offered in product format and service format.
The product format consists of the installation of an application that works automatically, both for updating the data and for obtaining the forecasts.
The service format consists of the fortnightly or monthly sending of the updated demand forecasts.
The main explanatory variables used in mid‑term demand forecasts are climatological data, such as temperature, economic indicators such as economic growth (GDP) and industrial activity (IPI), and labour.
The AleaSoft’s long‑term energy demand forecasts have a horizon of up to 20 years with a monthly or yearly interval. AleaSoft offers different types of long‑term energy demand forecasts: total demand, minimum and maximum hourly demand for the month or year and high and low voltage demand. The forecasts are offered in product format and in service format.
The product format consists of the installation of an application that works automatically, both for updating the data and for obtaining the forecasts. The application includes tools for obtaining the confidence bands, for defining temperature and socioeconomic scenarios and for the analysis of the sensitivity of the demand with respect to the temperature and the economic evolution.
The service format consists of the sending of the demand forecasts and of the main explanatory variables. The service may also include the sending of the forecast confidence bands.
The main explanatory variables used in the long‑term demand forecasts are the climatological data, such as temperature, economic indicators such as economic growth (GDP) and industrial activity (IPI), the demographic evolution (population) and the labour. Furthermore, the forecasts take into account the scenarios for the diffusion of new and existing technologies such as electric vehicles, batteries, self‑consumption, among others, and their impact on the volume of the demand.
AleaRetail is an Aleasoft solution for generating forecasts of demand for the short and medium term supply point portfolio. The forecasts have an hourly interval and a horizon of up to 7 days in the short term and up to 1 year in the medium term. The solution generates forecasts of each supply point, of the totals per tariff, of the totals per portfolio and of the general total.
AleaRetail includes the automatic data import processes, which detect the supply points that are registered or unregistered, in addition to the forecast generation and export of results processes.
The forecasts are made using the AleaModel model or the BOE model, depending on which one achieves the best results.
The AleaModel model uses labour as an explanatory variable. In the medium term, it also uses temperature and economic indicators such as the economic growth (GDP) and the industrial activity (IPI).
With the BOE model, the profiling calculations are carried out as indicated in the BOE.
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