AND OPTIMISATION OF A DUAL CIRCUIT INDUCED DRAFT COOLING WATER SYSTEM February 2016 CJ Muller Sasol University of Pretoria Under supervision of Prof IK Craig University ID: 580704
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MODELLING, CONTROL AND OPTIMISATION OF A DUAL CIRCUIT INDUCED DRAFT COOLING WATER SYSTEM
February 2016
C.J.
Muller
Sasol
;
University
of
Pretoria
Under supervision of:
Prof. I.K
. Craig
University
of PretoriaSlide2
Overview
Introduction
Process overview
Modelling and validation
Control and optimisationCase comparisonConclusion
2Slide3
Introduction
Process plants make extensive use of
utilities
(auxiliary process variables
) for example steam, electricity, compressed air, nitrogen and cooling water.When it comes to optimisation, the focus is typically on the consumption of the utility and not so much utility
generation
and/or transportation/transmissionUtilities account for a significant portion of fixed cost of a plantThis study covers the modelling, control and optimisation of a dual circuit induced draft cooling water systemThe purpose of the modelling is to provide a platform for simulation and controller/optimiser designThe control and optimisation objectives are to reduce energy consumption/cost while honouring process and equipment constraints
3Slide4
Process overview
Two Circuits:
Tempered
Water (TW) and Cooling Water
(CW)
4Slide5
Process overview
5
Process overview
Dual circuit cooling water system with induced draft counter flow cooling towersSlide6
Process overview
Two Circuits: Tempered Water (TW) and Cooling Water (CW)
TW
used in
plant heat exchanger network where it collects heat
TW
transfers
heat to CW though bank of heat exchangers6Slide7
Process overview
7
Process overview
Dual circuit cooling water system with induced draft counter flow cooling towersSlide8
Process overview
Two Circuits: Tempered Water (TW) and Cooling Water (CW)
TW used in plant heat exchanger network
TW transfers heat to CW though bank of heat exchangers
Heat removed from the CW in the Cooling Towers
(CTs) mainly by means of
partial
evaporation8Slide9
Process overview
9
Process overview
Dual circuit cooling water system with induced draft counter flow cooling towersSlide10
Process overview
Two Circuits: Tempered Water (TW) and Cooling Water (CW)
TW used in plant heat exchanger network
TW transfers heat to CW though bank of heat exchangers
Heat removed in Cooling Towers (CTs) mainly by means of partial evaporationEach circuit is equipped with bank of
pumps
to provide flow
10Slide11
Process overview
11
Process overview
Dual circuit cooling water system with induced draft counter flow cooling towersSlide12
Process overview
Two Circuits: Tempered Water (TW) and Cooling Water (CW)
TW used in plant heat exchanger network
TW transfers heat to CW though bank of heat exchangers
Heat removed in Cooling Towers (CTs) mainly by means of partial evaporationEach circuit is equipped with bank of pumpsA
temperature control valve
is installed to
bypass heat exchangers on TW side to provide a handle for TW supply temperature control12Slide13
Process overview
13
Process overview
Dual circuit cooling water system with induced draft counter flow cooling towersSlide14
Process overview
Two Circuits: Tempered Water (TW) and Cooling Water (CW)
TW used in plant heat exchanger network
TW transfers heat to CW though bank of heat exchangers
Heat removed in Cooling Towers (CTs) mainly by means of partial evaporationEach circuit is equipped with bank of pumpsA temperature control valve is installed to bypass heat exchangers on TW side to provide a handle for TW supply temperature control
Control valves
exist on the
discharges of the CW pumps, originally used for pump overload protection14Slide15
Process overview
15
Process overview
Dual circuit cooling water system with induced draft counter flow cooling towersSlide16
Process overview
Two Circuits: Tempered Water (TW) and Cooling Water (CW)
TW used in plant heat exchanger network
TW transfers heat to CW though bank of heat exchangers
Heat removed in Cooling Towers (CTs) mainly by means of partial evaporationEach circuit is equipped with bank of pumpsA temperature control valve is installed to bypass heat exchangers on TW side to provide a handle for TW supply temperature control
Control valves exist on the discharges of the CW pumps, originally used for pump overload
protection
This is an example of a Hybrid system: contains both discrete and continuous input variables16Slide17
Modelling and Validation
Model derived mathematically:
Pump
calculations:
Polynomial estimation from manufacturer’s pump curves
Receives flow rate, produces discharge pressure
Flow
calculations: Mass balance, system flow coefficients, valve equationsDuty/temperature calculations: Heat exchange equations, enthalpy change, energy balance, evaporative flowEnergy consumption calculations: Rated power (for fans) and polynomial estimations of manufacturer’s curves (pumps)Dynamics added to important variables to convert from steady-state to dynamic model and derive state-space formModel verified
against plant data for a period of 6 days (144 hours) during which significant load changes occurred
Genetic algorithm
used in
parameter estimation
to obtain better accuracy
17Slide18
Modelling Results
Correlation coefficient
and
least square error
approaches applied to gauge model qualityCorrelation between model and plant data:Adequate accuracy
for the purposes of this simplified model
Important to have correct
directionality as verified by the step testing results shown in the thesis18Slide19
Modelling Results (continued)
19
TW temperatures – simulated
vs. plant data
Model response (solid line) vs. plant data (dotted line).Slide20
Control and Optimisation
Four cases were considered:
Base case
Advanced Regulatory Control (ARC
)Hybrid Non-linear Model Predictive Control (HNMPC
)
Economic Hybrid
Non-linear Model Predictive Control (EHNMPC)Two simulations for each case:Simulation 1: Artificial plant input dataSimulation 2: Actual plant input data (same as that used for verification)20
Simulation 1
Simulation 2Slide21
Control and Optimisation (continued)
ARC Design:Aim is to make better use of base layer
: use override selector control, cascade control and rule-based switching logic to manipulate discrete variables
Overall
objective is to minimise energy consumption by switching equipment off when overcooling is providedNo plant model required21Slide22
Control and Optimisation (continued)
22
ARC scheme illustrationSlide23
Control and Optimisation (continued)
ARC Design:Aim is to make better use of base layer
: use override selector control, cascade control and rule-based switching logic to manipulate discrete variables
Overall
objective is to minimise energy consumption by switching equipment off when overcooling is providedNo plant model requiredAPC Design:Use the model of the system to develop a model predictive control strategyModel is non-linear and hybrid which complicates controller designGenetic algorithm used as optimiser: capable of handling this type of system directlyCost function mainly total energy consumption/costIteration time 30 minutes, prediction horizon 12, control horizon 4MVs: pumps, fans, flow controllers, temperature control valveCVs: TW supply and differential temperatures, power/cost23Slide24
Control and Optimisation (continued)
24
APC scheme illustrationSlide25
Control and Optimisation Results
25
Base case (CVs) – Simulation 2
CVsSlide26
Control and
Optimisation
Results (continued)
26
ARC case
– Simulation 2
MVs
CVsSlide27
Control and Optimisation Results (continued)
27
HNMPC case
– Simulation 2
MVs
CVsSlide28
Control and Optimisation Results (continued)
28
EHNMPC case
– Simulation 2
MVs
CVsSlide29
Case Comparison
29
Energy/Power ConsumptionSlide30
Case
Comparison (continued)
30
Energy/Power CostSlide31
Case Comparison (continued)
31
Constraint ViolationsSlide32
Conclusion
Utility optimisation
shows
promising potential
for optimisationBy using ARC techniques, the bulk of the benefit may be realised at a fraction of the cost and effort of APC
APC
allows for a marginal
further optimisation though at the cost of increased complexity and modelling requirementsHybrid systems complicate the control and optimisation design and many utility systems are of a hybrid natureMINLP is still underdeveloped as an industrial option for control and optimisation – GA proved to be an effective option for this studyAlways scope for further investigation and improvement – both utility optimisation and hybrid systems are intriguing fields for further studies32Slide33
Thank
you for
your
time
“The only true wisdom is in knowing you know nothing.”Socrates