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MẠCH ĐIỀU KHIỂN CỦA HỆ THỐNG CHILLER

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CLEANROOM

Chiller plant optimization
Terrence Morris & Steve Blaine PE, CH2M HILL, Oregon, USA

ABSTRACT

Outside of the process tools themselves, the chilled water plant is typically the single largest consumer of electrical energy in a
semiconductor facility [1]. This load includes not just chillers but also cooling tower fans, primary pumps, secondary pumps and
condenser pumps. In order to meet the cooling requirements for any particular heat load, many different combinations of this
equipment can be run. However, electricity consumption varies considerably depending on the combination of equipment used
and the operating levels of the individual components. Selecting the optimal mix of equipment and operating levels presents a
substantial challenge for an automatic control system and plant operators. Typically, no method is available to predict the effect
of interactions and variations in load demand and outside air. This makes it challenging, if not impossible, to find an equipment
mix that achieves optimal energy use. In response to this challenge, we set out to create a model/tool that would allow operators
to automatically determine the optimal equipment mix to satisfy cooling requirements and minimize energy use. This paper
describes how this model was created and how it works.

Introduction
A recent ASHRAE article by Mark
Hydeman and Guo Zhou describes the
use of a chiller plant optimization model
based on parametric modeling [2].
Thomas Hartman has published several
articles describing his patented LOOP
chiller plant design [3] and [4]. Ben
Erpelding describes implementation of
a system based on this work [5]. Our
model performs a similar optimizing
function but is accomplished using only
a standard Microsoft Excel spreadsheet.
The model can calculate the
predicted energy consumption for
any valid combination of equipment
serving a range of cooling loads at any
outside air condition. The type and
quantity of equipment modeled is based
on an actual semiconductor facility
chilled water plant. The model’s loaddetermining inputs include outside air
(wet bulb) temperature, distribution
system flow and distribution system
return water temperature. Based on
vendor data for chillers, cooling towers
and pumps, the model calculates
outputs for each component of the
system, including system bypass and
condenser water flow, entering and
leaving chiller condenser and cooling
tower temperatures, entering evaporator
temperature and leaving evaporator
temperatu...
W W W .FABTECH.ORG
CLEANROOM
Chiller plant optimization
Terrence Morris & Steve Blaine PE, CH2M HILL, Oregon, USA
Introduction
A recent ASHRAE article by Mark
Hydeman and Guo Zhou describes the
use of a chiller plant optimization model
based on parametric modeling [2].
Thomas Hartman has published several
articles describing his patented LOOP
chiller plant design [3] and [4]. Ben
Erpelding describes implementation of
a system based on this work [5]. Our
model performs a similar optimizing
function but is accomplished using only
a standard Microsoft Excel spreadsheet.
The model can cal cu la te the
predicted energy consumption for
any valid combination of equipment
serving a range of cooling loads at any
outside air condition. The type and
quantity of equipment modeled is based
on an actual semiconductor facility
chilled water plant. The models load-
determining inputs include outside air
(wet bulb) temperature, distribution
system flow and distribution system
return water temperature. Based on
vendor data for chillers, cooling towers
and pumps, the model calculates
outputs for each component of the
system, including system bypass and
condenser water flow, entering and
leaving chiller condenser and cooling
tower temperatures, entering evaporator
temperature and leaving evaporator
temperature (assumed constant @ 44ºF
(6.7ºC)). Based on these flows and
temperatures, the individual and total
system energy usage is computed.
The model also includes another
powerf ul f ea t ure : a s pre ads he et
function that optimizes the selection of
equipment. The results from this exercise
show the optimal choice of equipment
at any outside air condition and system
load. Further investigations will seek to
automate this optimization so that it can
be used in a control algorithm.
ABSTRACT
Outside of the process tools themselves, the chilled water plant is typically the single largest consumer of electrical energy in a
semiconductor facility [1]. This load includes not just chillers but also cooling tower fans, primary pumps, secondary pumps and
condenser pumps. In order to meet the cooling requirements for any particular heat load, many different combinations of this
equipment can be run. However, electricity consumption varies considerably depending on the combination of equipment used
and the operating levels of the individual components. Selecting the optimal mix of equipment and operating levels presents a
substantial challenge for an automatic control system and plant operators. Typically, no method is available to predict the effect
of interactions and variations in load demand and outside air. This makes it challenging, if not impossible, to find an equipment
mix that achieves optimal energy use. In response to this challenge, we set out to create a model/tool that would allow operators
to automatically determine the optimal equipment mix to satisfy cooling requirements and minimize energy use. This paper
describes how this model was created and how it works.
Figure 1b. Condenser water system schematic.
Figure 1a. Evaporator water system schematic.
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