DEMMORA project aims to develop and implement new optimal energy management strategies for the residential sector based on predictive controllers to improve energy efficiency, reduce energy costs, and maintain household comfort. These strategies must consider
1) the presence of uncertainty, both in the household’s thermal and electrical demands and in energy generation from renewable sources,
2) the simultaneous optimization of the different objectives to be considered,
3) the computational cost, ensuring real-time implementation of these strategies.
To achieve this, several specific scientific and technological objectives emerge.
Scientific objectives:
1. To develop energy management strategies using economic MPCs to obtain algorithms that can be implemented in real-time. For this purpose, bi-level MPC strategies with both economic levels and Move-Blocking MPCs will be developed and compared.
2. To incorporate the simultaneous optimization of several objectives using the global PP strategy in the MPC-based EMS, transforming the optimization problem into a MILP problem.
3. To address uncertainty in the EMS to be developed, both in demand and energy generation from renewable sources, using a conditional scenario approach and robust dominance methodologies.
Technological objectives (linked to the study cases of micro-CHP and Aerothermal homes):
1. To develop and implement techno-economic models of micro-CHP and Aerothermal systems. It must be possible to efficiently simulate the models against the entire year’s electrical and thermal energy demand profiles.
2. To implement EMS strategies developed on real-time platforms such as NI-CRio, PLCNext, Siemens Industrial Edge devices, etc.
3. To develop Hardware-In-the-Loop (HIL) platforms for micro-CHP and aerothermal configurations.
4. To test and validate the EMS implemented using the HIL platforms.
5. To test and validate the EMS implemented on the actual house with aerothermal and solar panels and on the test bench simulating a micro-CHP system.