Case 3
1. Overview
This case is to design a decoupled multiple-chiller plant that consists of a primary chilled water
production loop and a secondary chilled water distribution system. Fig.4 illustrates the structure of
typical multiple-chiller plant. Chillers are arranged in parallel and each chiller is coupled with a
constant-speed pump. When a chiller is staged on, the coupled pump will be switched on
accordingly to maintain a constant water flow rate through the chiller. Two temperature sensors
(one for chilled water supply and one for chilled water return) and one flow meter are installed at
the head pipes for supervising the operating condition and generating signal for sequencing
controller when using the total cooling load based sequencing control strategy. Normally, the
chilled water supply temperature is controlled to a set point, say 7 oC, and the return temperature is
determined by load demand. When the load is higher, the return temperature is higher.
The chilled water supply will be sent to chilled water distribution system, including a secondary
pump and air-handling units (AHU). The secondary water pump circulates the chilled water to the
AHUs and the flow rate is determined by the demand from AHUs. The AHUs are used to
condition supply air to a desired temperature and humidity, which will then be sent to indoor space
for thermal comfort.
Fig. 4 Multiple-chiller plant
A simulation platform will be constructed for a typical multiple-chiller plant. Figure 5 shows the
basic functional blocks and main connects among them. The platform will be open for editing and
users can configure the platform according to their requirement. Currently, this platform can be
used for




Energy performance evaluation of multiple-chiller plant
Components (AHUs, pumps, valves) performance evaluation
Chiller sequencing control
Chilled water supply temperature optimization
Fig. 5 Simulation platform (TRNSYS)
2.
Simulation Platform
This project is constructed on TRNSYS 17 and the chiller sequencing control strategy is coded in
Matlab 2010.
Figure 1 Simulation platform in TRNSYS 17
3.
Mode Used:
Type
Name
Functions
Route
Type 9c
Cooling load
To read the load profile
from .txt documents
Utility->Data readers->Genetic
Data files-> Free format
Equation
Air Flow rate
Calculate air flow rate with
thermal balance equation
Manu-> Assembly-> Insert new
equation
Type 744
Variable speed fan
To supplying return air to
the coils
Hydronic Library[TESS]
->Fans-> input the flow rate
Type 646
Return air diverter
To divert return air to
different coils
Hydronic Library[TESS]
->Valves->Diverting valve->air
Type 648
Supply air mixer
To mix supply air from
different coils
Hydronic Library[TESS]
->Valves->mixing valve->air
Type 52a
coil
To cool the return air
HVAC->cooling coils-> detailed
Type 23
Tempt controller
/DP controller
To control the supply air at
the setpoint
Controllers->PID controller
Type 741
Variable speed
pump
To distribute chilled water
to coils
Hydronic Library [TESS]
->Pumps -> variable speed->
Power from efficiency and
pressure drop
Type 155
Chiller sequencing
controller
To implement a link with
Matlab (.m).
Utility-> Calling external
programs ->Matlab
Type 654
Constant pump
To provide constant
flowrate to chillers
Hydronic Library [TESS]
->Pumps-> sets the mass
flowrate -> single speed
->constant power
Type 666
chiller
To provide cooling and
maintain the chilled water
supply temperature at
setpoint
HVAC library[TESS] ->chillers
-> water-cooled chiller
Type 65c
Outputs
To online plot and output
the required data
Output->Online plotter with file
-> not units
Please Note that:
 All the parameters setting can be seen when double click the component in the simulation
platform. Therefore, no parameters setting will be introduced in this guidebook.
 The design of this platform is based on a typical system with real cooling load. For different
cases, the configuration can be modified and tests for different chiller plants are flexible.
 All the parameters of the used components can be modified and the performances of the
components can be evaluated according to the parameter setting.
 The input documents for Data reader and Matlab linker should be put in the same folder of the
project.
4.
Examples
 1) PID controller performance evaluation
The temperature controller tends to control the supply air to its setpoint, 16oC. But the control
performance is determined by the tuning conditions of the PI controller. When the parameters
of the PI controller are changed, the tracking setpoint responses are different. As shown in
Figure 2, the red curve illustrates the controlled supply air temperature and the blue curve is
the load condition in a week. It is clear that when the gain constant is set to be -0.03, the
control result is much better than that when the gain constant is -0.01.
Figure 2. a) Supply air temperature when the PI gain constant is -0.03; b) Supply air
temperature when the PI gain constant is -0.01.
 2) Chiller sequencing control
The control performance of chiller sequencing control strategies can be evaluated in this
simulation platform. For instance, the total cooling load-based control strategy was coded
in Matlab with an “.m” document (Q_basedControl.m) and link to the simulation platform.
Figure 3 shows that this control strategy can stage chiller on or off according to the cooling
load condition.
Figure 3. Chiller sequencing control results