Economic hybrid non-linear model predictive control of a dual circuit induced draft cooling water system. (May 2017)

• Record Type: Journal Article
• Authors: Muller, C.J.; Craig, I.K.
• Is Part Of: Journal of process control. Volume 53(2017)
• Page Start: 37
• Page End: 45
• Publication Date: 2017-05
• Subjects: Modelling -- Optimisation -- Energy -- Hybrid systems -- Model predictive control -- Economic; Process control -- Periodicals; Fabrication -- Contrôle -- Périodiques; Process control; Periodicals; Electronic journals; 660.281
• DOI: 10.1016/j.jprocont.2017.02.009
• Languages: English
• ISSNs: 0959-1524

Abstract

Abstract : Highlights: Illustrate the potential benefits of utility optimisation on a petrochemical plant. A dual circuit cooling water system is used as an example. Main objective is the reduction of electrical energy consumption and cost. The system is both non-linear and hybrid. Objective is achieved via hybrid non-linear model predictive control (HNMPC) and economic HNMPC. Abstract: Petrochemical plants require the addition and removal of energy to and from the process and the movement of material to, from, and within the process piping and vessels. These fundamental mass and energy transfer requirements are typically achieved through the use of process utilities, which include electricity, steam, fuel gas, cooling water and compressed air. Utilities are responsible for a significant portion of the operating cost of a plant. Therefore, reduction in the consumption of utilities is a common process optimisation area. The situation is different when it comes to the generation and transportation of these utilities, which are often overlooked with regard to optimisation. In this paper, the potential benefits of utility optimisation are illustrated with particular focus on the generation and transportation areas. The main objectives are reductions in electrical energy consumption and cost and are illustrated for a dual circuit cooling water system. This system is non-linear and also hybrid in the sense that it contains both continuous and discrete input variables, which significantly complicates the design and implementation of control and optimisation solutions. This paper illustrates how the cost and energy consumption of a hybrid system can be reduced through the implementation of hybrid non-linear model predictive control (HNMPC) and economic HNMPC (EHNMPC). The results are compared to that of a base case and an Advanced Regulatory Control (ARC) case, showing that significant additional benefit may be achieved through the implementation of these advanced control and optimisation techniques. The paper further illustrates that additional capital is not necessarily required for the implementation of these techniques.