3E Optimal Control Services – Increasing system performance through data

October 6, 2016


Client:  3E – internal product (software) development
Period:  2014 – 2016


3E is developing software for optimal control of dynamic systems. Our focus is twofold: the building energy sector and the hybrid energy systems. Our approach is Model Predictive Control combined with greybox system identification. The combination of these powerful techniques optimizes the high level control set points of the system. It can be used both in the design and in the operational stage.

Beginning 2015, we have proven enhanced thermal comfort and a 30% energy cost savings compared to state-of-the art control of the hybrid heat pump system in our own office building in Brussels.

We have tested our software on 5 other buildings: 3 large office buildings and 2 elderly homes, to validate the value of the technology.

Our ambition is to offer an optimization layer on top of the existing controller to increase the performance of your building portfolio and hybrid systems.

Model Predictive Control optimizes the system operation over a certain period in time (eg 24 hours) by anticipating the impact of future disturbances on the system. It does so by means of:

  • forecasts of the exogenous disturbances (eg solar irradiation, temperatures, spot market prices…),
  • forecasts of the internal disturbances (eg occupancy, internal gains…),
  • a dynamic system model (eg dynamic building model, battery model),
  • feedback of the actual state (eg indoor air temperatures, battery state-of-charge),
  • knowledge of the constraints (eg maximum power rates, safety operation conditions)
  • and the user-defined objectives (eg maximize auto consumption over the next 24 hours)

This R&D project has been partly financed by SPW-DGO6 within the BATTERIE project.