Analysis of Solar Direct-Driven Organic Rankine Cycle Powered Vapor Compression Cooling System Combined with Electric Motor for Office Building Air-Conditioning

Solar energy powered organic Rankine cycle vapor compression cycle(ORC-VCC)is a good alternative to convert solar heat into a cooling effect.In this study,an ORC-VCC system driven by solar energy combined with electric motor is proposed to ensure smooth operation under the conditions that solar radiation is unstable and discontinuous,and an office building located in Guangzhou,China is selected as a case study.The results show that beam solar radiation and generation temperature have considerable effects on the system performance.There is an optimal generation temperature at which the system achieves optimum performance.Also,as a key indicator,the cooling power per square meter collector should be considered in the hybrid solar cooling system in design process.Compared to the vapor compression cooling system,the hybrid cooling system can save almost 68.23%of electricity consumption.

Energy Efficient Predictive Control for Vapor Compression Refrigeration Cycle Systems

Abstract--Vapor compression refrigeration cycle （VCC） system is a high dimensional coupling thermodynamic system for which the controller design is a great challenge. In this paper, a model predictive control based energy efficient control strategy which aims at maximizing the system efficiency is proposed. Firstly, according to the mass and energy conservation law, an analysis on the nonlinear relationship between superheat and cooling load is carried out, which can produce the maximal effect on the system performance. Then a model predictive control （MPC） based controller is developed for tracking the calculated setting curve of superheat degree and pressure difference based on model identified from data which can be obtained from an experimental rig. The proposed control strategy maximizes the coefficient of performance （COP） which depends on operating conditions, in the meantime, it meets the changing demands of cooling capacity. The effectiveness of the control performance is validated on the experimental rig. Index Terms--Cooling load, model predictive control （MPC）, superheat, vapor compression refrigeration cycle （VCC）.

Model Predictive Control for Vapor Compression Cycle of Refrigeration Process

A model predictive controller based on a novel structure selection criterion for the vapor compression cycle （VCC） of refrigeration process is proposed in this paper. Firstly, those system variables are analyzed which exert significant influences on the system performance. Then the structure selection criterion, a trade-off between computation complexity and model performance, is applied to different model structures, and the results are utilized to determine the optimized model structure for controller design. The controller based on multivariable model predictive control （MPC） strategy is designed, and the optimization problem for the reduced order models is formulated as a constrained minimization problem. The effectiveness of the proposed MPC controller is verified on the experimental rig.

Cooling High Power Dissipating Artificial Intelligence (AI) Chips Using Refrigerant

High power dissipating artificial intelligence (AI) chips require significant cooling to operate at maximum performance. Current trends regarding the integration of AI, as well as the power/cooling demands of high-performing server systems pose an immense thermal challenge for cooling. The use of refrigerants as a direct-to-chip cooling method is investigated as a potential cooling solution for cooling AI chips. Using a vapor compression refrigeration system (VCRS), the coolant temperature will be sub-ambient thereby increasing the total cooling capacity. Coupled with the implementation of a direct-to-chip boiler, using refrigerants to cool AI server systems can materialize as a potential solution for current AI server cooling demands. In this study, a comparison of 8 different refrigerants: R-134a, R-153a, R-717, R-508B, R-22, R-12, R-410a, and R-1234yf is analyzed for optimal performance. A control theoretical VCRS model is created to assess variable refrigerants under the same operational conditions. From this model, the coefficient of performance (COP), required mass flow rate of refrigerant, work required by the compressor, and overall heat transfer coefficient is determined for all 8 refrigerants. Lastly, a comprehensive analysis is provided to determine the most optimal refrigerants for cooling applications. R-717, commonly known as Ammonia, was found to have the highest COP value thus proving to be the optimal refrigerant for cooling AI chips and high-performing server applications.

Multivariable fuzzy control of residential inverter-driven air conditionings

A model free intelligent muhivariable fuzzy controller （MFC） designed for modulating the vapor compression cycles in a residential inverter-driven air conditioning is proposed. The novel controller combines a traditional fuzzy controller （TFC） and an additional coupling fuzzy controller, the coupling fuzzy controller is introduced to compensate for the unknown cross-coupling effects of this muhivariable system. In order to evaluate the control performance of the MFC, it is digitally implemented in terms of regulating the desired evaporating temperature and superheat. The experimental results show the effectiveness of the MFC for improvement of system performance and energy efficiency.

Critical assessment of R410A alternatives for mini-split air conditioners in the Egyptian market

In this study,the potential implementation of three different low-GWP refrigerants(R32,R452B,and R454B)as replacements for R410A was investigated.The study was performed using a simulation tool developed by the authors called RACHP-Lab,which is a vapor compression system simulation tool developed based on physics-based simulation for typical mini-split air conditioners.The simulation study was carried out and validated using experimental performance data of 10 different air conditioning units available in the Egyptian market.The units included fixed-speed or variable-speed compressors and operated in cooling or heating modes.Drop-in replace-ment with the new refrigerants was carried out.For R32,the capacity increased between 4.9%and 13%for cooling cases,and 6.3%and 12.4%for heating cases.However,COP did not improve in all cases.For R452B and R454B with direct replacement,the capacity nearly remained the same,with an increase of COP between 1.6%and 8.0%.Soft optimization was also conducted on cooling cases where compressor suction superheat,condenser subcooling,and compressor volumetric speed were optimized to maximize COP while maintaining the original capacity of R410A.R32 showed an improvement of COP over R410A between 4.6%and 15.5%,while for R452B and R454B between 2.2%and 13.2%.

Energetic Analysis and Working Fluids Selection for a New Power and Refrigeration Combined Ecological System

The main purpose of this study is to analyze the performance of a new system that combines organic Rankine Cycle(ORC) and vapor compression refrigeration cycle(VCRC) for refrigeration and cogeneration. This system uses low-temperature heat sources such as solar energy, geothermal, industrial waste heat and biomass. The novelty of the proposed system manifests itself essentially in: the development of new ORC-VCRC combination architecture, lowering the ORC condensing temperature, the possibility of refrigeration production by the ORC upstream of the pumping phase, preheating of ORC using VCRC fluid and new configurations based on the integration of heat recovery systems to improve the overall system performance. The first part of this study presents the energetic analysis for the basic system using different working fluids and investigation of the operating parameters effect on the system performance(The system performance is described by the ORC thermal efficiency, the VCRC coefficient of performance and the system overall efficiency). Ten working fluids have been selected in order to provide the most adequate candidates for the proposed system. The results showed that the heating temperature and the cooling temperature have a significant effect on the system performance. The choice of fluid was also mentioned;the obtained results confirmed that the best combination for the basic system is R236fa-acetone. Four system configurations are developed and analyzed in the second part of the study. Also in the same part of the study, we will compare these configurations in terms of the performance rate retained. In the last part, we will make a comparison of this new system with another system.