Mixed Integer Nonlinear Programming (MINLP) Based Optimization of Refrigeration Systems

MOROSUK, TATIANA; MUSSATI, SERGIO F.; MUSSATI, MIGUEL C.

Congreso; IMECE2021 - International Mechanical Engineering Congress and Exposition 2021; 2021

ASME - The American Society of Mechanical Engineers

This paper addresses the optimization of refrigeration systems by proposing a deterministic model involving both discrete and continuous decisions. The superstructure-based representation of vapor compression-absorption cascade refrigeration system, recently presented by the authors, is properly extended to include more candidate configurations as well as a cost model considering capital and operation expenditures. The proposed superstructure representation is then formulated as a mixed- integer nonlinear programming (MINLP) model and solved using an optimization algorithm based on the generalized reduced gradient method. The mass flowrate, pressure, temperature, composition of all streams, and the energy transferred with the associated heat transfer area and driving force of all process units are simultaneously optimized. The optimal configuration is selected from the proposed superstructure. The resulting optimization model is inherently combinatorial in nature and involves more than 20 candidate combinations. A study case is presented in order to show the utility of the proposed model. Given the desired design specifications (refrigeration temperature and capacity) the model allows obtaining the optimal configuration, process-unit sizes, and operating conditions that minimize the total annual cost. As a result of the model, the optimal configuration consisting of a stand-alone compression cycle with R717 is selected from the proposed superstructure to achieve 100 kW at -20 ºC. Then, this optimal solution is compared with a solution obtained with a fixed configuration consisting of a vapor compression-absorption cascade refrigeration system which is a sub-optimal solution compared to the stand-alone compression cycle.