Date of Award
Doctor of Philosophy
Building energy sector is one of the important sources of energy consumption and especially
in the United States, it accounts for approximately 40% of the total energy consumption.
Besides energy consumption, it also contributes to CO2 emissions due to the combustion of
fossil fuels for building operation. Preventive measures have to be taken in order to limit the
greenhouse gas emission and meet the increasing load demand, energy efficiency and savings
have been the primary objective globally. Heating, Ventilation, and air-conditioning (HVAC)
system is a major source of energy consumption in buildings and is the principal building system
of interest. These energy systems comprising of many subsystems with local information
and heterogeneous preferences demand the need for coordination in order to perform optimally.
The performance required by a typical airside HVAC system involving a large number of zones
are multifaceted, involves attainment of various objectives (such as optimal supply air temperature)
which requires coordination among zones. The required performance demands the need
for accurate models (especially zones), control design at the individual (local-VAV (Variable Air
Volume)) subsystems and a supervisory control (AHU (Air Handling Unit) level) to coordinate
the individual controllers.
In this thesis, an airside HVAC system is studied and the following considerations are addressed:
a) A comparative evaluation among representative methods of different classes of
models, such as physics-based (e.g., lumped parameter autoregressive models using simple
physical relationships), data-driven (e.g., artificial neural networks, Gaussian processes) and
hybrid (e.g., semi-parametric) methods for different physical zone locations; b) A framework
for control of building HVAC systems using a methodology based on power shaping paradigm
that exploits the passivity property of a system. The system dynamics are expressed in the
Brayton-Moser (BM) form which exhibits a gradient structure with the mixed-potential function,
which has the units of power. The power shaping technique is used to synthesize the controller by assigning a desired power function to the closed loop dynamics so as to make the equilibrium point asymptotically stable, and c) The BM framework and the passivity tool are
further utilized for stability analysis of constrained optimization dynamics using the compositional
property of passivity, illustrated with energy management problem in buildings. Also,
distributed optimization (such as subgradient) techniques are used to generate the optimal setpoints
for the individual local controllers and this framework is realized on a distributed control
platform VOLTTRON, developed by the Pacific Northwest National Laboratory (PNNL).
Chinde, Venkatesh, "Modeling and control of complex building energy systems" (2018). Graduate Theses and Dissertations. 16330.