Open Science Research Excellence
%0 Journal Article
%A Vinko Lešić and  Mario Vašak and  Anita Martinčević and  Marko Gulin and  Antonio Starčić and  Hrvoje Novak
%D 2015 
%J  International Journal of Computer, Electrical, Automation, Control and Information Engineering
%B World Academy of Science, Engineering and Technology
%I International Science Index 106, 2015
%T Computer-Assisted Management of Building Climate and Microgrid with Model Predictive Control
%U http://waset.org/publications/10003400
%V 106
%X With 40% of total world energy consumption,
building systems are developing into technically complex large
energy consumers suitable for application of sophisticated power
management approaches to largely increase the energy efficiency
and even make them active energy market participants. Centralized
control system of building heating and cooling managed by
economically-optimal model predictive control shows promising
results with estimated 30% of energy efficiency increase. The research
is focused on implementation of such a method on a case study
performed on two floors of our faculty building with corresponding
sensors wireless data acquisition, remote heating/cooling units and
central climate controller. Building walls are mathematically modeled
with corresponding material types, surface shapes and sizes. Models
are then exploited to predict thermal characteristics and changes in
different building zones. Exterior influences such as environmental
conditions and weather forecast, people behavior and comfort
demands are all taken into account for deriving price-optimal climate
control. Finally, a DC microgrid with photovoltaics, wind turbine,
supercapacitor, batteries and fuel cell stacks is added to make the
building a unit capable of active participation in a price-varying
energy market. Computational burden of applying model predictive
control on such a complex system is relaxed through a hierarchical
decomposition of the microgrid and climate control, where the
former is designed as higher hierarchical level with pre-calculated
price-optimal power flows control, and latter is designed as lower
level control responsible to ensure thermal comfort and exploit
the optimal supply conditions enabled by microgrid energy flows
management. Such an approach is expected to enable the inclusion
of more complex building subsystems into consideration in order to
further increase the energy efficiency.
%P 2276 - 2287