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MODELLING, CONTROL - PPT Presentation

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

cooling control heat water control cooling water heat process overview optimisation plant circuit towers system model continued flow bank

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Slide1

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