In the United States, the energy consumption of commercial and
residential buildings exceeds 40% and it is responsible for 45% of
greenhouse gas emission. Consequently, saving related energy and costs,
improving energy consumption efficiency and reducing greenhouse emissions
are becoming key initiatives in many cities and municipalities. For that
reason it also plays an important role in IBM smarter planet initiative.
In order to reduce energy consumption in buildings, one needs to
understand and be capable of modeling the underlying heat transfer
mechanisms, characteristics of building structures, operations and
occupant energy consumption behaviors.
Often, some of the crucial building envelope parameters are not known. In
order to infer thermal parameters associated with building’s envelope,
sensor data is utilized within an inversion procedure. The forward
problem involves a system of ODEs capturing the governing heat transfer
model. Our formulation also involves derivation of adjoints for efficient
gradient computation. Through sensitivity analysis, we assess the impact
of potential energy saving retrofits and their quantitative impact upon
energy consumption of commercial buildings.