Abstract
The IEA estimates energy demand for refrigeration by 2050 could triple. Models that allow discovery of energy saving opportunities are a must. Models for cooling systems emphasize the thermal domain leaving in the background the relationships among other energy domains and the power input source consumption. This article fills a gap in the scientific literature presenting a comprehensive model of a VCRS based on experimental measurements and catalog data. The model starts from the empirical identification of the thermal part of a commercial fridge, followed by theoretical models based on catalog data for the electrical, mechanical, and hydraulic parts. The model can be used as a benchmarking for energy activity, performances, controller effectiveness, and impact of new technologies. The VCRS is simulated for both traditional on-off discrete operation and a continuous operation using new technologies such as variable speed compressors and adjustable valves. Strategies facilitating a better use of the energy while fulfilling a desired behavior are possible through the comprehensive model.
TopIntroduction
VCRS are the most used cold production method worldwide. Approximately 30% of the energy is consumed in applications related to air conditioning (Jahangeer et al., 2011). VCRS integrate elements from multiple energy domains using the reverse Rankine cycle to subtract heat from a lower temperature tank to a higher temperature tank, figure 1. Much energy is required for such tasks. Energy comes from the power injection of an external source of electromechanical work (Wcomp) to compress and circulate a refrigerant, which undergoes phase changes as it absorbs and delivers heat. The refrigeration cycle to obtain the desired temperature inside a chamber begins when the refrigerant enters the compressor as saturated vapor (state 1) to be isentropically compressed until reaching a certain pressure and temperature in the superheated region (state 2). The compressed refrigerant enters the condenser to transfer heat (Qs) to the environment. The refrigerant leaves the condenser as saturated liquid (state 3). To low the refrigerant temperature, an expansion valve applies adiabatic throttling. in state 4, so it absorbs heat (Qe) in the evaporator space. The refrigerant is heated to recover its saturated vapor state repeating the cycle. Figure 1 represents the heat transfer in case of reversible processes. The area under the curve for process 4-1 represents the heat absorbed (Qe) by the refrigerant in the evaporator and the area under the curve for process 2-3 represents the heat rejected (Qs) in the condenser.
Figure 1. Temperature-entropy for the thermal cycle of a VCSR
There is a growing interest in improving the energy efficiency of VCRS. Refrigerators accounts for a substantial portion of the annual energy consumption in the average home. The report (United Nations Environment Programme, 2018) on potentials to improve energy efficiency of refrigeration, air conditioning and heat pumps, highlights among the main measures with the greatest impact on energy saving: 1.- minimize the load of cooling, 2.- minimize temperature rise, 3.- consider variable operating conditions, 4.- select the most efficient refrigeration cycle and components, and, 5.- design effective control systems and verify operational performance correcting faults in existing systems. Given the need to improve the design, operation and use of energy in cold production, are necessary models that characterize in the most approximate way the real behavior of the installation (Belman Flores, 2008). A VCRS is a machine that from the electrical domain (motor) makes a conversion to the rotational mechanical domain (torque and RPM) acting on the hydraulic domain (pressure and flow) to finally reach the thermal domain, figure 2.
Figure 2. a) Diagram of a VCRS, b) Elements in a domestic fridge
This chapter illustrates the multidomain modeling of a VCRS to offer a holistic and unified representation that facilitates energy saving strategies and behaviors characterization of its components. The VCRS modeling starts from experimental data in the thermal domain on a commercial fridge (Schné et al., 2015) and is complemented with catalog data from other domains. This VCRS multi-domain model is not limited to the current state but includes recent advances in variable-speed compressors and adjustable-expansion valves. This approach allows exploring into the impact the new technologies that are projected as future solutions in intelligent control that affect the dynamics of the VCRS process. There are difficulties in achieving a priori a comprehensive visualization of the coupled behavior of a multidomain system. In VCRS, the thermal part has been studied in-depth but if the aim is to increase energy efficiency, the electromechanical excitation that drives the internal dynamics of the compressor must be considered.
Key Terms in this Chapter
Energy Efficiency: The process of using less energy to get the same job done. Efficient energy use results in energy bills and pollution reducing.
Bond Graph: A graphical representation of a physical dynamic system which is regarded as composed of components with a port transferring energy among them by flow and potential variables.
Vapor Compression Refrigeration: A system which circulates a liquid refrigerant alternately compressing and expanding it, changing it from liquid to vapor. As this change happens, heat is either absorbed or expelled by the system, resulting in a change in temperature of the surrounding air.
Evolutionary Algorithms: Heuristic search methods inspired by evolution and living organisms to solving problems that cannot be easily work out in polynomial time.
Data Catalog: A data set, created by the manufacturer, summarizing the performance and other characteristics of a machine or component in sufficient detail that allows a user, installation technician or design engineer to understand the behavior of a specific product.
Multidomain Modeling: A model characterized by having components belonging to different engineering disciplines assembled into a larger simulation system.
Empirical Modeling: Process of building a mathematical representation that reflects the behavior of a system observed on data from a specific experiment made on that system.