The refrigeration industry is essential in today's society but also a significant contributor to global greenhouse gas emissions. A substantial portion of these emissions results from leaks of fluorocarbons—such as chlorofluorocarbons, hydrochlorofluorocarbons and hydrofluorocarbons—from refrigeration systems. In response, regulations are increasingly phasing out these harmful substances in favour of refrigerants with ultra-low global warming potential (GWP). One of the best alternatives for supermarket refrigeration systems is carbon dioxide (R744), which has zero ozone depletion potential and a minimal GWP, resulting in a negligible direct impact on global warming. CO₂ is also non-flammable, non-toxic and possesses excellent heat transfer properties. However, using CO₂ in refrigeration systems presents challenges. The low critical temperature of R744 leads to increased energy consumption at high heat sink temperatures due to transcritical operating conditions. These transcritical modes occur in both cold climates—because of waste heat recovery for district heating purposes—and warm ones, potentially causing a significant indirect contribution to global warming from CO₂ refrigeration systems.
Recently, digitalization is taking centre stage in the refrigeration sector. A key aspect of digitalization is the use of digital twins. In supermarkets, digital twins of refrigeration systems can optimize performance in real-time, reduce energy consumption, and maintain the quality of perishable goods through proactive maintenance and precise control.
The project focuses on developing advanced digitalization solutions to enhance the energy efficiency and sustainability of transcritical CO₂ supermarket refrigeration systems. Central to the research is the creation and validation of a dynamic digital twin model of a generalized supermarket energy system. The digital twin will simulate the real-time behaviour of the refrigeration system, integrating components such as heat recovery systems, cold thermal energy storage and renewable energy sources such as photovoltaic/thermal panels. By designing optimal control structures and developing advanced optimization algorithms for real-time set-point optimization, supermarkets can operate at the highest energy efficiency possible throughout the year. Additionally, the project will develop and demonstrate advanced optimization algorithms to effectively recover waste heat from supermarkets for district heating networks, reducing the need to burn natural gas. The study will also emphasize real-time monitoring, fault detection, and diagnostic techniques.
The project is supervised by Associate Professor Paride Gullo.
Contact information
PhD student Milad Morid Zadeh - email: milad@sdu.dk, phone: +45 6550 3210