An industrial application using mixed-integer programming technique: A multi-period utility system model

Abstract

This paper addresses the application of Mixed Integer Programming (MIP) techniques for the optimization of site utility systems. Linear Programming (LP) and Non-Linear Programming (NLP) methods are often used in industry for optimizing the operating conditions of plant utility systems. These techniques are efficient and robust making them suitable for on-line optimization. However, on-line optimization of this type normally considers only current operating conditions and therefore minimum operating costs over a longer period cannot be guaranteed. In addition, LP and NLP methods cannot easily be used to make discrete decisions such as turning equipment on and off. These difficulties can be resolved by employing a multi-period mixed-integer utility plant model. Moreover, other important topics can be investigated with the models such as boiler and maintenance schedules, new equipment selection for utility system debottlenecking, fuel balance optimization and storage, electricity import or export profile optimization, inter-sites electricity backup, etc. In this paper, an industrial example is used to demonstrate MIP techniques for the optimization of plant utility systems.