Bi-Multiperiod Optimization of Industrial Cooling Systems

Abstract

In many chemical plants, a variety of cooling systems, including circulating cooling water systems and air coolers, are widely used to remove industrial waste heat. Current approaches for the design and optimization of these systems have focused on the use of constant parameters, including fixed temperature and energy price. Moreover, the ever-changing weather conditions play a major role in the design of cooler water systems and air coolers, leading to an unbalanced problem formulation that attempts to solve a complex problem with minimum rigor. Therefore, the concept of bi-multiperiod optimization is proposed to describe the daily/monthly change of weather conditions, as well as the fluctuation of electricity price during peak and off-peak periods within a day. The aim of this work is to obtain an economically optimal cooling system design under bi-multiperiod conditions by reasonably configuring both water coolers and air coolers. A mixed integer nonlinear programming (MINLP) model was established to obtain the optimal configuration. A case study derived from the literature shows that the optimized cooling network configuration using the proposed method is more economic than the deterministic design, the cooling water consumption is reduced by 5%, and the total cost is reduced by more than 9%.