Subsystems and Disturbance Models - Comfort Control in Buildings - page 80

such as temperature (Sodja and Zupancic 2009 ; Wu and Sun 2012 ), humidity (Diasty
et al. 1992 ; Tenwolde and Pilon 2007 ), CO 2 concentration (Emmerich and Persily
2001 ; Lawrence and Braun 2006 ), or even indoor daylighting (Fakra et al. 2011 ).
In general, the development of models of a dynamic system is a complex
process that depends on the characteristics of the dynamics of the system object
of study (Rodríguez and Berenguel 2002 ). More specifically, the dynamic behav-
iour of a climate room, from temperature, humidity and CO 2 concentration points
of view, is a combination of physical processes involving energy transfer and mass
balance. These processes can be expressed as a function of the outside environmen-
tal conditions, the main characteristic of the modelled room, such as its structure
and orientation, the number of people inside the room and the effect of the control
actuators.
Therefore, the main aim of this chapter is to develop dynamic models of a room
climate. More specifically, three different approximations are presented: a linear
model based on empirical data in order to look for a tradeoff between simplicity
and performance, a nonlinear model based on empirical data and ANN, and finally,
a nonlinear model based on first principles which allows to obtain the dynamic of
the climate in the room as a function of the environmental conditions and possi-
ble disturbances. Moreover, three different methodologies to estimate disturbances
model are also proposed. In addition, a methodology to calibrate and validate the
first principles model is presented. The developed models have been validated inside
a typical room of the CDdI-CIESOL-ARFRISOL building and the obtained results
are included and discussed.
This chapter is organised as follows: a detailed description of a characteristic
office room of the building which is used to validate the presented models is given
in Sect. 4.2 . This room can be representative of a typical room with four or five
occupants. Section 4.2.1 is devoted to Linear-Time Invariant (LTI) models and their
associated identification techniques. In addition, an LTI model which relates indoor
air temperature to the Heating, Ventilation, and Air Conditioning (HVAC) system is
obtained for the room presented in Sect. 4.2 . Section 4.2.2 presents an ANN room-
level model and the methodology used to obtain it. In Sect. 4.2.3 a first principles
formulation of the dynamic model of a room is carried out. In Sect. 4.3 , the method-
ology used to calibrate and validate the model formulated in Sect. 4.2.3 is described,
and the obtained results are explained. Finally, Sect. 4.4 is devoted to disturbances
models.
4.2 A Typical Office Room Modeling
From a modelling point of view a room can be considered as a complex system
composed of different kind of elements, such as walls, floor and ceil, windows,
HVAC systems, the outside meteorological conditions, the environment of the adja-
cent spaces and so on. Therefore, a room model can be established as a system that
is characterised by thermal and optical properties of each of its components, and by
the surrounding conditions around the building.