modelElectricReformulatedEIR
Extends from Buildings.Fluid.Chillers.BaseClasses.PartialElectric.
Information
Model of an electric chiller, based on the model by
Hydeman et al. (2002) that has been developed in the CoolTools project
and that is implemented in EnergyPlus as the model
Chiller:Electric:ReformulatedEIR.
This empirical model is similar to
Buildings.Fluid.Chillers.ElectricEIR.
The difference is that to compute the performance, this model
uses the condenser leaving temperature instead of the entering temperature,
and it uses a bicubic polynomial to compute the part load performance.
This model uses three functions to predict capacity and power consumption:
| Function | Description | Formulation | |
|---|---|---|---|
ElectricEIR (this model) |
ElectricReformulatedEIR (this model) |
||
capFunT |
Adjusts cooling capacity for current fluid temperatures | Biquadratic on TConEnt and TEvaLvg |
Biquadratic on TConLvg and TEvaLvg |
EIRFunPLR |
Adjusts EIR for the current PLR | Quadratic on PLR | Bicubic on TConLvg and PLR |
EIRFunT |
Adjusts EIR for current fluid temperatures | Biquadratic on TConEnt and TEvaLvg |
Biquadratic on TConLvg and TEvaLvg |
These curves are stored in the data record per and are available from
Buildings.Fluid.Chillers.Data.ElectricReformulatedEIR.
How they are used to compute the adjusted capacity and compressor power
can be found in the documentation of
Buildings.Fluid.Chillers.BaseClasses.PartialElectric.
Additional performance curves can be developed using
two available techniques (Hydeman and Gillespie, 2002). The first technique is called the
Least-squares Linear Regression method and is used when sufficient performance data exist
to employ standard least-square linear regression techniques. The second technique is called
Reference Curve Method and is used when insufficient performance data exist to apply linear
regression techniques. A detailed description of both techniques can be found in
Hydeman and Gillespie (2002).
The model takes as an input the set point for the leaving chilled water temperature, which is met if the chiller has sufficient capacity. Thus, the model has a built-in, ideal temperature control. The model has three tests on the part load ratio and the cycling ratio:
-
The test
PLR1 =min(QEva_flow_set/QEva_flow_ava, per.PLRMax);
ensures that the chiller capacity does not exceed the chiller capacity specified by the parameterper.PLRMax. -
The test
CR = min(PLR1/per.PRLMin, 1.0);
computes a cycling ratio. This ratio expresses the fraction of time that a chiller would run if it were to cycle because its load is smaller than the minimal load at which it can operate. Note that this model continuously operates even if the part load ratio is below the minimum part load ratio. Its leaving evaporator and condenser temperature can therefore be considered as an average temperature between the modes where the compressor is off and on. -
The test
PLR2 = max(per.PLRMinUnl, PLR1);
computes the part load ratio of the compressor. The assumption is that for a part load ratio belowper.PLRMinUnl, the chiller uses hot gas bypass to reduce the capacity, while the compressor power draw does not change.
The electric power only contains the power for the compressor, but not any power for pumps or fans.
The model can be parametrized to compute a transient or steady-state response. The transient response of the chiller is computed using a first order differential equation for the evaporator and condenser fluid volumes. The chiller outlet temperatures are equal to the temperatures of these lumped volumes.
Optionally, the model can be configured to represent heat recovery chillers with
a switchover option by setting the parameter have_switchover to
true.
In that case an additional Boolean input connector coo is used.
The chiller is tracking a chilled water supply temperature setpoint at the
outlet of the evaporator barrel if coo is true.
Otherwise, if coo is false, the chiller is tracking
a hot water supply temperature setpoint at the outlet of the condenser barrel.
See
Buildings.Fluid.Chillers.Examples.ElectricEIR_HeatRecovery
for an example with a chiller operating in heating mode.
References
- Hydeman, M., N. Webb, P. Sreedharan, and S. Blanc. 2002. Development and Testing of a Reformulated Regression-Based Electric Chiller Model. ASHRAE Transactions, HI-02-18-2.
- Hydeman, M. and K.L. Gillespie. 2002. Tools and Techniques to Calibrate Electric Chiller Component Models. ASHRAE Transactions, AC-02-9-1.
Parameters
| Type | Name | Default | Description |
|---|---|---|---|
| Buildings.Fluid.Chillers.Data.ElectricReformulatedEIR.Generic | per | Performance data |
Revisions
-
March 12, 2015, by Michael Wetter:
Refactored model to make it once continuously differentiable. This is for issue 373. -
Jan. 9, 2011, by Michael Wetter:
Added input signal to switch chiller off. -
September 17, 2010, by Michael Wetter:
First implementation.