4. WHAT DO YOU
KNOW ABOUT
MPC?
Model Predictive Control (MPC) is a promising
approach for managing energy consumption in smart
buildings and providing demand-side flexibility in
multi-carrier energy systems. In this context, MPC can
optimize energy usage across multiple carriers (such
as electricity, heating, cooling, and even electric
vehicles) to enhance energy efficiency, reduce costs,
and support grid stability.
Description Here
5. Elaborations (+)
• can take into account stochastic properties of random
disturbance variables (eg. weather forecast, occupancy
profiles); thus it adjusts control actions appropriately.
• can deal with variable energy price that can be easily
included into the formulation of the optimization
problem.
• can realize the load shifting within certain time frame for
dispatch and operation
• can be formulated in a distributed manner and thus the
computational load can be split among several solvers.
Argumen Point
MPC is used to utilize renewable energy
6. Elaborations(-)
• Challenges for non-technical users, and they require
specific background knowledge of the methods.
• Time consuming for data analysis and modelling.
• MPC strategies require significantly higher
investments which may not be compensated by
additional savings in a short time.
Argumen Point
the difficulty of installing the MPC
7. CONCLUSION
In conclusion, flexible consumption and smart energy
systems are crucial for managing renewable energy
sources. Buildings with large thermal storage capacity
are important. Implementing EMPC for BEMS is effective,
but challenges remain. Experimental studies are needed
to validate ideas and confirm optimal temperature set
points. The proposed hierarchical controller setup is
reliable but less robust than a distributed controller
structure. Further research is needed to evaluate system
optimality and robustness.
