4E analysis of a two-stage refrigeration system through surrogate models based on response surface methods and hybrid grey wolf optimizer

Abstract

Refrigeration systems are complex, non-linear, multi-modal, and multi-dimensional. However, traditional methods are based on a trial and error process to optimize these systems, and a global optimum operating point cannot be guaranteed. Therefore, this work aims to study a two-stage vapor compression refrigeration system (VCRS) through a novel and robust hybrid multi-objective grey wolf optimizer (HMOGWO) algorithm. The system is modeled using response surface methods (RSM) to investigate the impacts of design variables on the set responses. Firstly, the interaction between the system components and their cycle behavior is analyzed by building four surrogate models using RSM. The model fit statistics indicate that they are statistically significant and agree with the design data. Three conflicting scenarios in bi-objective optimization are built focusing on the overall system following the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Linear Programming Technique for Multidimensional Analysis of Preference (LINMAP) decision-making methods. The optimal solutions indicate that for the first to third scenarios, the exergetic efficiency (EE) and capital expenditure (CAPEX) are optimized by 33.4% and 7.5%, and the EE and operational expenditure (OPEX) are improved by 27.4% and 19.0%. The EE and global warming potential (GWP) are also optimized by 27.2% and 19.1%, where the proposed HMOGWO outperforms the MOGWO and NSGA-II. Finally, the K-means clustering technique is applied for Pareto characterization. Based on the research outcomes, the combined RSM and HMOGWO techniques have proved an excellent solution to simulate and optimize two-stage VCRS.

Multi-objective optimisation of VCR systems by applying TOPSIS to the single-objective solutions obtained with Excel Solver

“…TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) is a decision making method that has been utilised for similar optimisation studies in the recent years [1,4,14]. According to this method, ideal and non-ideal points should be first obtained.…”

“…The significant share of vapour-compression refrigeration (VCR) system in the energy consumption of residential, commercial, and industrial sectors necessitates improving the efficiency of these systems. One method for increasing the systems' coefficient of performance (COP) is to use multi-stage compression [1,2]. Since the improved systems cost more than the simple systems, their feasibility depends on careful compromises between their electrical energy consumption and cost.…”

“…Ahmed et al [1] analysed a two-stage VCR system by using a novel hybrid multiobjective grey wolf optimizer (HMOGWO) algorithm. The system was modelled using response surface methods (RSM) to investigate the impacts of design variables on the set responses.…”

A generalized disjunctive programming model for multi-stage compression for natural gas liquefaction processes

“…In industrial applications where gas is transported through pipelines, one of the most crucial processes is gas compression. It is commonly employed in internal combustion engines, power generation cycles, domestic gas supply and refrigeration cycles [3][4][5].…”