The compactness and good air-side heat exchange of the microchannel heat exchanger make it widely used in residential and automotive air conditioning systems. However, due to the different properties of refrigerant liquid and vapor, there is phase separation in the header and heat exchange tubes of the microchannel heat exchanger, resulting in uneven distribution of the refrigerant in the parallel microchannel tubes, the heat transfer area utilization rate is reduced, and the system performance is reduced. In addition, the presence of lubricants can also affect refrigerant distribution. The conclusion is that a small amount of lubricating oil will make the refrigerant distribution performance worse, and further adding lubricating oil will change the flow pattern, thereby improving the refrigerant distribution performance. This is because foam is formed after a large amount of oil is introduced to make the flow pattern more uniform. For any given lubricant content, at the same mass flow rate, as the quality increases, the distribution becomes worse because there is less liquid in the top pipe. In the case of the same inlet quality, as the mass flow increases, the high-momentum liquid can reach the top of the header, which is easy to be entrained by the top pipe, and the refrigerant distribution is better. However, although the lubricant improves the distribution of the refrigerant in the parallel microchannel tubes, it also significantly reduces the specific enthalpy difference of the working fluid, which is mainly due to its non-evaporative nature. Therefore, the influence of lubricating oil on the pressure drop and heat transfer characteristics of the microchannel heat exchanger after improving the refrigerant distribution is still an unresolved issue.
In order to study the influence of expander and internal heat exchanger on the performance of the CO2 trans-critical cycle cascade refrigeration system, the effects of evaporation temperature (Te) on discharge temperature of the compressor, recovery power of expander, input power of compressor, COP , exergy efficiency and exergy destruction of the system, and exergy destruction ratio of each component were carried out by thermodynamic analysis. The results show that expander can effectively decrease the optimum condensation temperature of low-temperature cycle (LTC) and optimum high pressure, while high-temperature internal heat exchanger can slightly reduce the optimum condensation temperature and optimum high pressure of LTC and significantly reduce COP and recovery work of the expander. The COP of CE, when R14 is used as refrigerant, is 89.7% ~ 91.4% of that of R23 / R22CT. The biggest exergy destruction component is the gas cooler. The results provide a solution to improve the efficiency of the CO2 trans-critical cascade refrigeration system.
It is difficult to calculate the theoretical line loss of low-voltage distribution transformer area and the evaluation index of transformer line loss is extensive. In this paper, a reasonable interval calculation model of line loss is established based on the convolutional neural network based on the data of electricity information acquisition system. The model can estimate the reasonable line loss interval according to the operation data of different transformers. On this basis, the line loss evaluation system is established and the rectification plan of abnormal line loss is formed. The method in this paper can improve the quality and efficiency of line loss lean management and produce certain effect for saving electric energy and improving economic benefit of power supply.
As a widely utilized phenomenon, condensation heat transfer is deeply related to the efficiency of energy utilization in industry. In recent decades, the condensation of vapor mixture attracted extensive attention, since the possibility to achieve high performance of heat transfer. During the condensation of some binary vapor Marangoni condensation), a special phenomenon was discovered that the spontaneous movement of condensate drop occurred. It was observed that condensate drops moved from the low temperature region to the high temperature region on a heat transfer surface. Therefore, the surface tension gradient induced by the temperature gradient was considered as the driving force. However, another affecting factor on the spontaneous movement of condensate drops, the direction of vapor flow, was also discovered. In this study, the experimental study was performed, and the results showed that the condensate drops tended to move towards the inlet direction of vapor flow.
To make efficient use of natural gas resource and realize carbon-free emission, a solar thermochemical energy storage system with the combined steam and dry methane reforming is proposed in this study. In the system, the methane reforming reaction is driven by concentrated solar energy, which upgrades solar thermal energy into chemical energy in the form of the syngas products. A reactor model that considers multiple reactions system and kinetic rate equations is used for the performance simulation of the thermochemical energy storage system. The results show that the distributions of temperature, mole fraction of components and conversion along reactor axis direction are uneven. The steam methane reforming reaction mainly consumes CH4 at the front part of the reactor, and the dry methane reforming reaction dominates the reaction system at the latter part of the reactor. The highest thermochemical energy storage efficiency can reach 61% under the condition of the stoichiometric feed ratio and 1 bar. The research findings provides an efficient and stable method for the reduction of natural gas consumption and the utilization of solar energy
This work has studied the boiling heat transfer mechanism in a pump driven loop thermosyphon system. The coolant is Freon R134a which flows and boils in a tube with inside diameter of 8.05 mm. The results show that at a constant heat flux, the boiling heat transfer coefficient is not influenced by the coolantâ€™s mass flow rate. In other ward, the boiling mechanism at this situation is the nucleate boiling instead of the convection boiling.
In this paper, we present a novel approach developed through the TABEDE project to scale demand response across all building types. To this end, we propose an intelligent infrastructure that enables buildings to follow various demand-response schemes, that optimises the electricity consumption and generation of the buildings to reduce energy cost and promote RES penetration, and that is capable of connecting and controlling appliances seamlessly and in an interoperable manner. The approach is evaluated via a simulated district based on one of the project pilot sites in Cardiff, UK. The results show potential improvements to varying extents in solar PV self-consumption, energy cost reduction, and adhering to grid constraints.
A comparative life-cycle greenhouse gas (GHG) emission analysis between a proposed integrated sewage sludge (SS) and food waste (FW) management strategy and business-as-usual scenarios in Singapore was performed in this study. The proposed approach was derived based on the design of co-located water reclamation plant and waste-to-energy incineration plant in Tuas, in which the SS and FW are anaerobic co-digested. The ratio of SS and FW was selected to be 1:1 for optimal biogas production. The effects of the power substitution and methane production rate uncertainties were investigated. The life-cycle GHG emission results show that the proposed strategy has a 64.3% reduction when compared to the current SS and FW treatments, or a 2129 tonnes CO2-eq reduction potential per year.
In this paper, the thermodynamic analysis of three kinds of three-stage cascade refrigeration systems (TCRS) with internal heat exchanger (IHX) are studied using R1150/R170/R717 and R50/R170/R717, including TCRS with LTC IHX (TCRSIL), TCRS with MTC IHX (TCRSIM) and TCRS with IHXs in MTC and LTC (TCRSIL-M). The results indicate that when evaporation temperature is -120 oC ~ -80 oC and heat transfer efficiency of IHX is 60%, COP of TCRSs using R1150/R170/R717 is higher than that of TCRSs using R50/R170/R717. Under the same conditions, using IHX in TCRS will reduce the COP for R1150/R170/R717. Compared with TCRS without IHX, the average COP of TCRSIM, TCRSIL and TCRSIL-H decreased by 0.6%, 1.5% and 3.6% respectively. For R50/R170/R717, when evaporation temperature is -115 oC ~ -100 oC and heat transfer efficiency of IHX is 60%, using IHX in LTC is helpful to improve COP, but the increase is less than 1% compared with TCRS without IHX. However, in other temperature range, using IHX will reduce the COP. And the use of IHXs increases the exergy destruction of cascade heat exchangers in MTC and LTC. Therefore, R1150 /R170/R717 is recommended for TCRS, and IHXs are not recommended in TCRS.
The main aim of this paper is to investigate the impact of lighting conditions on the detection accuracy of the vision-based equipment load detection approach. The work will be using artificial intelligence cameras to detect equipment information in different lighting levels, employing deep learning method to analyze and generate real-time equipment usage profiles for offices which can be inputted to the demand-based building controls to increase the efficiency of heating, ventilation, and air-conditioning systems. The performance of the developed approach in various illumination conditions was compared by using a building energy simulation tool. The results showed that as compared with the conventionally-scheduled heating, ventilation, and air-conditioning systems, the system with the use of equipment usage profiles conducted by the proposed approach can achieve up to 15% reduction in energy consumption depending on the setup of the camera in terms of indoor lighting levels. The finding indicates that adequate illumination level contributes to the decrease of building energy demand by achieving an effective deep learning approach.