better together... we deliver 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 Pretoria

better together... we deliver Overview Introduction Process overview Modelling and validation Control and optimisation Case comparison Conclusion 2

better together... we deliver 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/transmission Utilities account for a significant portion of fixed cost of a plant This study covers the modelling, control and optimisation of a dual circuit induced draft cooling water system The purpose of the modelling is to provide a platform for simulation and controller/optimiser design The control and optimisation objectives are to reduce energy consumption/cost while honouring process and equipment constraints 3

better together... we deliver Process overview Two Circuits: Tempered Water (TW) and Cooling Water (CW) 4

better together... we deliver Process overview 5 Dual circuit cooling water system with induced draft counter flow cooling towers

better together... we deliver 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 exchangers 6

better together... we deliver Process overview 7 Dual circuit cooling water system with induced draft counter flow cooling towers

better together... we deliver 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 evaporation 8

better together... we deliver Process overview 9 Dual circuit cooling water system with induced draft counter flow cooling towers

better together... we deliver 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 evaporation Each circuit is equipped with bank of pumps to provide flow 10

better together... we deliver Process overview 11 Process overview Dual circuit cooling water system with induced draft counter flow cooling towers

better together... we deliver 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 evaporation Each circuit is equipped with bank of pumps A temperature control valve is installed to bypass heat exchangers on TW side to provide a handle for TW supply temperature control 12

better together... we deliver Process overview 13 Process overview Dual circuit cooling water system with induced draft counter flow cooling towers

better together... we deliver 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 evaporation Each circuit is equipped with bank of pumps A 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 14

better together... we deliver Process overview 15 Process overview Dual circuit cooling water system with induced draft counter flow cooling towers

better together... we deliver 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 evaporation Each circuit is equipped with bank of pumps A 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 variables 16

better together... we deliver 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 equations Duty/temperature calculations: Heat exchange equations, enthalpy change, energy balance, evaporative flow Energy 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 form Model 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 17

better together... we deliver Modelling Results Correlation coefficient and least square error approaches applied to gauge model quality Correlation 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 thesis 18

better together... we deliver Modelling Results (continued) 19 TW temperatures – simulated vs. plant data Model response (solid line) vs. plant data (dotted line).

better together... we deliver 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 data Simulation 2: Actual plant input data (same as that used for verification) 20 Simulation 1Simulation 2

better together... we deliver 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 provided No plant model required 21

better together... we deliver Control and Optimisation (continued) 22 ARC scheme illustration

better together... we deliver 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 provided No plant model required APC Design: Use the model of the system to develop a model predictive control strategy Model is non-linear and hybrid which complicates controller design Genetic algorithm used as optimiser: capable of handling this type of system directly Cost function mainly total energy consumption/cost Iteration time 30 minutes, prediction horizon 12, control horizon 4 MVs: pumps, fans, flow controllers, temperature control valve CVs: TW supply and differential temperatures, power/cost 23

better together... we deliver Control and Optimisation (continued) 24 APC scheme illustration

better together... we deliver Control and Optimisation Results 25 Base case (CVs) – Simulation 2 CVs

better together... we deliver Control and Optimisation Results (continued) 26 ARC case – Simulation 2 MVsCVs

better together... we deliver Control and Optimisation Results (continued) 27 HNMPC case – Simulation 2 MVsCVs

better together... we deliver Control and Optimisation Results (continued) 28 EHNMPC case – Simulation 2 MVsCVs

better together... we deliver Case Comparison 29 Energy/Power Consumption

better together... we deliver Case Comparison (continued) 30 Energy/Power Cost

better together... we deliver Case Comparison (continued) 31 Constraint Violations

better together... we deliver Conclusion Utility optimisation shows promising potential for optimisation By 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 requirements Hybrid systems complicate the control and optimisation design and many utility systems are of a hybrid nature MINLP is still underdeveloped as an industrial option for control and optimisation – GA proved to be an effective option for this study Always scope for further investigation and improvement – both utility optimisation and hybrid systems are intriguing fields for further studies 32

Confidential Document better together... we deliver THANK YOU FOR YOUR TIME “The only true wisdom is in knowing you know nothing.” Socrates