This partial model for a generic grey-box vapour compression machine
(heat pump or chiller) uses empirical data to model the refrigerant
cycle. The modelling of system inertias and heat losses allow the
simulation of transient states.
Resulting in the choosen model structure, several configurations are
possible:
- Compressor type: on/off or inverter controlled
- Reversible operation / only main operation
- Source/Sink: Any combination of mediums is possible
- Generik: Losses and inertias can be switched on or off.
Concept
Using a signal bus as a connector, this model working as a heat pump
can be easily combined with several control or safety blocks from
AixLib.Controls.HeatPump.
The relevant data is aggregated. In order to control both chillers
and heat pumps, both flow and return temperature are aggregated. The
mode signal chooses the operation type of the vapour compression
machine:
- mode = true: Main operation mode (heat pump: heating; chiller:
cooling)
- mode = false: Reversible operation mode (heat pump: cooling;
chiller: heating)
To model both on/off and inverter controlled vapour compression
machines, the compressor speed is normalizd to a relative value
between 0 and 1.
Possible icing of the evaporator is modelled with an input value
between 0 and 1.
The model structure is as follows. To understand each submodel,
please have a look at the corresponding model information:
-
InnerCycle
(Black Box): Here, the user can use between several input models or
just easily create his own, modular black box model. Please look at
the model description for more info.
- Inertia: A n-order element is used to model system inertias (mass
and thermal) of components inside the refrigerant cycle (compressor,
pipes, expansion valve)
-
HeatExchanger: This new model also enable modelling of thermal
interias and heat losses in a heat exchanger. Please look at the
model description for more info.
Parametrization
To simplify the parametrization of the evaporator and condenser
volumes and nominal mass flows there exists an option of automatic
estimation based on the nominal usable power of the vapour
compression machine. This function uses a linear correlation of these
parameters, which was established from the linear regression of more
than 20 data sets of water-to-water heat pumps from different
manufacturers (e.g. Carrier, Trane, Lennox) ranging from about 25kW
to 1MW nominal power. The linear regressions with coefficients of
determination above 91% give a good approximation of these
parameters. Nevertheless, estimates for machines outside the given
range should be checked for plausibility during simulation.
Assumptions
Several assumptions where made in order to model the vapour
compression machine. For a detailed description see the corresponding
model.
-
Performance data 2D: In order to model inverter controlled
machines, the compressor speed is scaled linearly
-
Performance data 2D: Reduced evaporator power as a result of
icing. The icing factor is multiplied with the evaporator power.
-
Inertia: The default value of the n-th order element is set
to 3. This follows comparisons with experimental data. Previous
heat pump models are using n = 1 as a default. However, it was
pointed out that a higher order element fits a real heat pump
better in
-
Scaling factor: A scaling facor is implemented for scaling
of the thermal power and capacity. The factor scales the parameters
V, m_flow_nominal, C, GIns, GOut and dp_nominal. As a result, the
vapour compression machine can supply more heat with the COP
staying nearly constant. However, one has to make sure that the
supplied pressure difference or mass flow is also scaled with this
factor, as the nominal values do not increase said mass flow.
Known Limitations
- The n-th order element has a big influence on computational time.
Reducing the order or disabling it completly will decrease
computational time.
- Reversing the mode: A normal 4-way-exchange valve suffers from
heat losses and irreversibilities due to switching from one mode to
another. Theses losses are not taken into account.
Contents
-
May 22, 2019 by Julian Matthes:
Rebuild due to the introducion of the thermal machine partial model
(see issue #715)
-
November 26, 2018 by Fabian Wüllhorst:
First implementation (see issue #577)
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