R&D Nester is participating in IEEE ODS competition on building energy consumption forecasting, with its AI.Forecasting tool.

This competition is organized by the IEEE Power & Energy Society Technical Committee on Analytic Methods for Power Systems (IEEE PES AMPS) / Intelligent Systems Subcommittee (ISS). The main objective of this IEEE competition is bringing together the most recent advances in building energy consumption forecasting methods.

Energy consumption forecasting is crucial in current and future power and energy systems. With the increasing penetration of renewable energy sources, with high associated uncertainty due to the dependence on natural conditions, such as wind speed or solar intensity, the need to balance the fluctuation of generation with the flexibility from the consumer side increases considerably. In this way, significant work has been done on the development of energy consumption forecasting methods, able to deal with different forecasting circumstances, e.g., the prediction time horizon, the available data, the frequency of data, or even the quality of data measurements. The main conclusion is that different methods are more suitable for different prediction circumstances, and it is not clear that a certain method can outperform all others in all situations.

Hence, R&D Nester developed the AI.Forecasting tool, an architecture of AI and machine learning methods that enables the automatic learning of energy forecasting models specific for each application. The developed ensemble solution is a combination of different ML methods that perform different non-linear transformations to the same data. The individual methods composing the ensemble are Support vector machines, Extreme gradient boosting and Deep learning using long short-term memory networks. This tool was developed under the scope of the GIFT project, an innovation project funded by the European Commission that aims at decarbonizing the European islands through the application of multiple innovative solutions, such as a virtual power system, energy management systems for harbors, factories and homes, better prediction of supply and demand, visualisation through a GIS platform, as well as innovative storage systems, allowing synergy between electrical, heating and transportation networks.

R&D Nester just received the communication from the organization of the IEEE ODS competition announcing that its performance is one of the Top 3 participants.

The winner of this competition will be announced on July 27^th, during the IEEE Power & Energy Society General Meeting that will be held in Washington, DC next 25-29 July.

For more information:

IEEE ODS Competition website

GIFT Project