A digital twin for the energy system of Instituto Superior Técnico (Alameda Campus)

Digital twins were born 20 years ago but have only now matured enough, being strongly supported by the advancements of Industry 4.0. By integrating sensors, internet of things, cloud computing, and machine learning, digital twins are endowed with strong capabilities of monitoring, prediction, and diagnosis.

This in turn assures a more efficient and optimized management of power grids, promoting, amongst others services, demand-response strategies, renewable energy sources and prosumers integration in the grid, fault prediction, and maintenance routines scheduling. Digital twins bring integration and intelligence to operations management, highly supporting decision making. The path paved by this technology is just beginning. In the following years, digital twins will further penetrate into different industries and will soon become an essential tool in every control room.

The objective of this work will be to implement a digital twin of the energy consumption of Instituto Superior Técnico. To achieve this, robust forecasting models will be created, supported by real-time data provided by the smart meters already installed on campus. A framework will be designed to independently and automatically update the models as new data is collected, ensuring they remain faithful to the real process. The collected data and the resulting predictions will be integrated into a novel visualization tool permeated with important visual elements, whose collective added value will ultimately support a better management of the electricity service in Instituto Superior Técnico.