INESC TEC is the only entity involved in the project “Long_Forecasting: ENTSO-E demand forecasting methodology – Performance assessment and improvement”. The four-month project launched in March focuses on developing and implementing a long-term electricity consumption forecasting system for European countries until 2050.
The European entity ENTSO-E – European Network of Transmission System Operators for Electricity – is preparing to integrate a software to improve the performance of its current forecasting system.
The application is under development since March 17, the date of the project’s kick-off meeting organised by four researchers at INESC TEC’s Centre for Power and Energy Systems (CPES): Nuno Fidalgo, José Paulos, Miguel Ribeiro and Filipe Azevedo.
“The better the quality of the forecast, the more efficient and suited the planning will be, particularly concerning the needs of energy generation and transportation. This leads to savings, which in turn translates into reduced electricity costs and lower tariffs”, explained Nuno Fidalgo, coordinator of the project.
The forecasting systems under development resort to three different technologies: Multi-Linear Regression, Artificial Neural Networks and Generalized Regression Neural Networks. The proposed innovation lies in the methodology developed, which is expected to lead to better forecasting performance and reduced planning costs.
ENTSO-E represents 43 transmission system operators from in 36 European countries, who can integrate the INESC TEC solution into their systems, thus benefiting from it in planning projects, for instance.
The INESC TEC researchers mentioned in this news piece are associated with INESC TEC and UP-FEUP.
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