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    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
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