tools for real-time optimization of system performance [21,22], but
models of a building and its systems need to be well calibrated [23].In
general, well calibrated first-principle models can be used [24], but
simpler and precise empirical (e.g. neural network models) models
can be used as well [16].
3. Modeling approaches
3.1. Modeling approaches for HVAC components
According to Zeigler [25], the majority of models in building and
system performance simulation are:
• Continuous in state, as the range of model variables is represented
by real numbers or intervals. However, some models assume a
discrete set of values and are thus discrete state models.
• Discrete in time, as time is specified to proceed in discrete steps. If
the model is continuous in state and discrete in time, it is then
described by a (system of) difference equation(s).
• Deterministic. However, stochastic models are used as well, e.g. in
predictive control applications [20].
• Time varying, since the rules of interaction are different at different
times.
• Both steady state and dynamic.
• Forward, as they are used to predict the response of output variables
based on a known structure and known parameters when subjected
to input and forcing variables. Backward (data-driven)models
1
tend
to be much simpler but are relevant only for cases when system-
specific and accurate models of specific building components are
required, e.g. for fault detection and diagnosis [16].
There is a distinction between primary and secondary HVAC
system components. The former are sometimes referred to as plant,
and the latter are referred to as system. A primary system converts
fuel and electricity and delivers heating and cooling to a building
through secondary systems. Examples are: chillers, boiler, cooling
towers, thermal storage systems, etc. Secondary systems include air-
handling equipment, air distribution system and liquid distribution
system between the primary system and the building interior.
In both primary and secondary systems there are two types of
components: distribution components and heat and mass balance
components. The distribution components are: pumps, fans, dampers,
valves,ductsandpipes.Theyaffecttheenergy flowin buildings by [26]:
• consuming electrical energy which drives pumps and fans, and
• transferring thermal energy to/from the working fluid in all
distribution components.
The distribution componentmodels should satisfy energy and mass
balance equations.Most of the BPS toolsmodel distribution components
in a simplified way [26], which eliminates the need to calculate the
pressure drop through distribution system at off-design conditions. In
general, this approach is sufficiently accurate for studying temperatures
in the system. For detailedanalysis of e.g. fan/pump control loops and for
answering questions related to the placement of the return/exhaust fan,
type and size of dampers/pipes, flow and pressure balancing between
the components is necessary [18].
The above heat and mass transfer components are usually
described by fundamental engineering principles — first-principle
1
In data-driven models the input and the output variables are known and
measured, and the objective is to determine the mathematical description and to
estimate the system parameters.models (if equations are derived from fundamental principles but
require some empirical input these models are also referred to as
quasi-first-principle models [27], e.g. most of the component models
in [28] and [29]), or by empirically obtained equations, i.e. by using
regression analysis of design data published by a manufacturer, or by 自动化暖通空调系统仿真英文文献和中文翻译(3):http://www.751com.cn/fanyi/lunwen_9006.html