MULTI-OBJECTIVE OPTIMIZATION OF GAS BLEND ALTERNATIVE REFRIGERANTS FOR VAPOR-COMPRESSION REFRIGERATION SYSTEMS

摘要

This paper presents a theoretical study on optimizing the mixing ratios of hydrocarbon blends to be used as refrigerants in existing refrigeration equipment. The primary objective is to maximize the coefficient of performance. The gas blending optimization problem is posed in a multi-objective framework, where the optimization seeks to generate Pareto optimal solutions that span the trade-off frontier between coefficient of performance versus deviation from a desired volumetric refrigeration capacity, while adhering to a maximum compression ratio. Design variables in the optimization are the mass fractions of hydrocarbon gases in the blend. A domain reduction scheme is introduced, which allows for efficient conduction of exhaustive search, with up to three hydrocarbon gases in the blend. While exhaustive search guarantees that the obtained solutions are global optima, the computational resources it requires scale poorly as the number of design variables increase. Two alternative approaches, (multi-start SQP) and (NSGA-II) are also tested for solving the optimization problem. Numerical simulation case studies for replacement of R12, R22 and R134a with hydrocarbon blends of isobutane, propane and propylene show agreement between solution methods that good compromises are possible to achieve, but a small loss in coefficient of performance is inevitable.