Energy efficient climate control is an important current task, hence there has been a growing
rethinking in energy savings. The building sector accounts for about 40% of the total energy
consumption. In order to guarantee user comfort while minimizing energy consumption in
residential buildings an intelligent automation system has to be implemented. Such
controversial optimization problems, as minimizing energy cost while maximizing user
comfort, are suitable for model predictive control (MPC). Furthermore, occupancy and
external disturbances in buildings as weather (ambient temperature and radiance) can be
explicitly handled by MPCs.
Structural modifications are not needed to reduce energy consumption and CO2-emission for
heating and cooling in existing and new buildings, with an intelligent energy-efficient home
automation system (energy reduction up to 40%). In this project proposal an intelligent MPC
for home automation shall be designed. To get the highest possible performance with the
least effort, beside the MPC concept, a self-adaptive model for buildings and userbehaviour
is proposed. This self-adaptive model is able to correct model-errors because of adapting the
userbehaviour. Moreover the model is able to manage a new parametrization during on-line
operation. Furthermore another keyaspect is the choice of a suitable data mining and
processing algorithm.
By reason of adaptive MPC the thermal comfort in the building increases while energy
consumption is reduced effectively. Furthermore a flexible use of green energy is easy
realizeable. The easiest way to profit from green energy is the intelligent control of the blinds.
Because of the smart usability with smart phones or tablets, the system is easy and clear to
handle and the concept is userfriendly as well. Moreover, the opportunity for smart grids is
given.
For the industrial partner evon automation GmbH a unique selling point in the building sector
and home automation area is created, because of the combination: MPC with a self-adaptive
model. On account of cost-efficient implementing the number of possible users is given, both
new buildings and retrofitting in existing buildings. Because of the multiplier effect the
potential for CO2 reduction in the building sector is realizable.