Simulation Enhanced Integrated Systems for Model-based Intelligent Control
The objectives of the EINSTEIN project were to formulate and integrate a number of state-of-the-art building control strategies to test their effect on improving the performance of buildings beyond traditional control approaches.
The three control strategies developed in the project relate to: Fault Detection and Diagnosis (FDD), Building Performance Prediction and Building Performance Optimisation.
The algorithms developed in EINSTEIN open up new and real opportunities to advance beyond classical building control approaches by deploying solutions that are “Smarter”. The key benefits of the demonstrated EINSTEIN approach are that it:
- Addresses the complexity of modern buildings in terms of the systems and dynamics involved, as well as external factors such as weather;
- Takes advantage of the current technical evolution and progression in meters/sensors and smart devices to provide more building and user data at lower costs;
- Aims to connect into existing building control infrastructure to reduce the cost and effort of installation of the solution;
- Results in better and more efficient building management on a continuous basis, and greater flexibility for control through Building Management Systems (BMS).
IES R&D led this project in collaboration with Trinity College Dublin (TCD).