Multi-Objective Optimization of a Small-Scale ORC-VCC System Using Low-GWP Refrigerants

Łukasz Witanowski ()
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Łukasz Witanowski: Institute of Fluid-Flow Machinery, Polish Academy of Sciences, 80-231 Gdańsk, Poland

Energies, 2024, vol. 17, issue 21, 1-18

Abstract: The increasing global demand for energy-efficient cooling systems, combined with the need to reduce greenhouse gas emissions, has led to growing interest in using low-GWP (global warming potential) refrigerants. This study conducts a multi-objective optimization of a small-scale organic Rankine cycle–vapor compression cycle (ORC-VCC) system, utilizing refrigerants R1233zd, R1244yd, and R1336mzz, both individually and in combination within ORC and VCC systems. The optimization was performed for nine distinct cases, with the goals of maximizing the coefficient of performance (COP), maximizing cooling power, and minimizing the pressure ratio in the compressor to enhance efficiency, cooling capacity, and mechanical reliability. The optimization employed the Non-dominated Sorting Genetic Algorithm III (NSGA-III), a robust multi-objective optimization technique that is well-suited for exploring complex, non-linear solution spaces. This approach effectively navigated trade-offs between competing objectives and identified optimal system configurations. Using this multi-objective approach, the system achieved a COP of 0.57, a pressure ratio around 3, and a cooling capacity exceeding 33 kW under the specified boundary conditions, leading to improved mechanical reliability, system simplicity, and longevity. Additionally, the system was optimized for operation with a cooling water temperature of 25 °C, reflecting realistic conditions for contemporary cooling applications.

Keywords: waste heat; multi-objective optimization; organic Rankine cycle; vapor compression cycle; Non-dominated Sorting Genetic Algorithm III (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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