Energy reduction for a dual circuit cooling water system using advanced regulatory control

Abstract

Various process utilities are used in the petrochemical industry as auxiliary variables to facilitate the addition/removal of energy to/from the process, power process equipment and inhibit unwanted reaction. Optimisation activities usually focus on the process itself or on the utility consumption though the generation and distribution of these utilities are often overlooked in this regard.Many utilities are prepared or generated far from the process plant and have to be transported or transmitted, giving rise to more losses and potential inefficiencies. To illustrate the potential benefit of utility optimisation, this paper explores the control of a dual circuit cooling water system with focus on energy reduction subject process constraints. This is accomplished through the development of an advanced regulatory control (ARC) and switching strategy which does not require the development of a system model, only rudimentary knowledge of the behaviour of the process and system constraints. The novelty of this manuscript lies in the fact that it demonstrates that significant energy savings can be obtained by applying ARC to a process utility containing both discrete and continuous dynamics. Furthermore, the proposed ARC strategy does not require a plant model, uses only existing plant equipment, and can $ This work is based on research partly supported by the National Research Foundation of South Africa (Grant No. 90533 be implemented on control system hardware commonly used in industry. The simulation results indicate energy saving potential in the region of 30% on the system under investigation.

Economic hybrid non-linear model predictive control of a dual circuit induced draft cooling water system

“…There are also control valves on the discharges of the CW pumps initially intended to prevent pumps from running beyond capacity. A detailed account of the system model is given in [4], [5] and [12].…”

“…The first scenario covers a period of 7 days of artificial plant data during which step-like and ramp-like changes are made to the plant duty and sinusoidal changes are made to the ambient temperature and relative humidity (both influencing the wet-bulb temperature, T wb ). The second scenario uses 6 days of real plant data during a period where significant load disturbances occurred (the same data that was used for the model verification in [4], [5] and [12]). Figures 2 and 3 show the plant duty and wet-bulb temperature for the two scenarios.…”

“…Four cases are considered: the first case illustrates the current system where no optimisation is performed in terms of equipment switching and only the temperature controller is active; the second case represents an Advanced Regulatory Control (ARC) scheme with conditional switching logic as described in [4] and [5]; the third is a Hybrid Non-linear Model Predictive Control (HNMPC) implementation whereas the fourth is an Economic HNMPC (EHNMPC) scheme where Time-of-Use (TOU) tariffs are included in the formulation. Each case was simulated for both the operating scenarios mentioned above.…”

“…The system constraints are: power consumption. For more detail on the switching logic and the results for both simulations, refer to [4] and [5]. A comparison of the results from the ARC scheme to that of the solutions described in this paper is given in Section 4.3.…”

“…In [1], the losses and inefficiencies encountered in typical steam systems are analysed, revealing significant potential for improvement. In [2], [3], [4] and [5], the benefits of control improvements for cooling water systems are illustrated. In [6] and [7], the optimisation of an industrial fuel gas system is presented resulting in a significant reduction in operating cost.…”