Localized Theoretical Analysis of Thermal Performance of Individually Finned Heat Pipe Heat Exchanger for Air Conditioning with Freon R404A as Working Fluid

This work contributes to the improvement of energy-saving in air conditioning systems. The objective is to apply the thermal efficiency of heat exchangers for localized determination of the thermal performance of heat exchangers with individually finned heat pipes. The fundamental parameters used for performance analysis were the number of fins per heat pipe, the number of heat pipes, the inlet temperatures, and the flow rates of hot and cold fluids. The heat exchanger under analysis uses Freon 404A as a working fluid in an air conditioning system for cooling in the Evaporator and energy recovery in the Condenser. The theoretical model is localized and applied individually to the Evaporator, Condenser, and heat exchanger regions. The results obtained through the simulation are compared with experimental results that use a global approach for the heat exchanger. The thermal quantities obtained through the theoretical model in the mentioned regions are air velocity, Nusselt number, thermal effectiveness, heat transfer rate, and outlet temperature. The comparisons made with global experimental results are in excellent agreement, demonstrating that the localized theoretical approach developed is consistent and can be used as a comprehensive analysis tool for heat exchangers using heat pipes.

Localized Theoretical Analysis of Thermal Performance of Individually Finned Heat Pipe Heat Exchanger for Air Conditioning with Freon R404A as Working Fluid

This work contributes to the improvement of energy-saving in air conditioning systems. The objective is to apply the thermal efficiency of heat exchangers for localized determination of the thermal performance of heat exchangers with individually finned heat pipes. The fundamental parameters used for performance analysis were the number of fins per heat pipe, the number of heat pipes, the inlet temperatures, and the flow rates of hot and cold fluids. The heat exchanger under analysis uses Freon 404A as a working fluid in an air conditioning system for cooling in the Evaporator and energy recovery in the Condenser. The theoretical model is localized and applied individually to the Evaporator, Condenser, and heat exchanger regions. The results obtained through the simulation are compared with experimental results that use a global approach for the heat exchanger. The thermal quantities obtained through the theoretical model in the mentioned regions are air velocity, Nusselt number, thermal effectiveness, heat transfer rate, and outlet temperature. The comparisons made with global experimental results are in excellent agreement, demonstrating that the localized theoretical approach developed is consistent and can be used as a comprehensive analysis tool for heat exchangers using heat pipes.

Effect of Two Kinds of Similarity Factors on Principal Component Analysis Fault Detection in Air Conditioning Systems

Screening similar historical fault-free candidate data would greatly affect the effectiveness of fault detection results based on principal component analysis(PCA).In order to find out the candidate data,this study compares unweighted and weighted similarity factors(SFs),which measure the similarity of the principal component subspace corresponding to the first k main components of two datasets.The fault detection employs the principal component subspace corresponding to the current measured data and the historical fault-free data.From the historical fault-free database,the load parameters are employed to locate the candidate data similar to the current operating data.Fault detection method for air conditioning systems is based on principal component.The results show that the weighted principal component SF can improve the effects of the fault-free detection and the fault detection.Compared with the unweighted SF,the average fault-free detection rate of the weighted SF is 17.33%higher than that of the unweighted,and the average fault detection rate is 7.51%higher than unweighted.

Influence of Three Sizes of Sliding Windows on Principle Component Analysis Fault Detection of Air Conditioning Systems

Principal component analysis(PCA)has been already employed for fault detection of air conditioning systems.The sliding window,which is composed of some parameters satisfying with thermal load balance,can select the target historical fault-free reference data as the template which is similar to the current snapshot data.The size of sliding window is usually given according to empirical values,while the influence of different sizes of sliding windows on fault detection of an air conditioning system is not further studied.The air conditioning system is a dynamic response process,and the operating parameters change with the change of the load,while the response of the controller is delayed.In a variable air volume(VAV)air conditioning system controlled by the total air volume method,in order to ensure sufficient response time,30 data points are selected first,and then their multiples are selected.Three different sizes of sliding windows with 30,60 and 90 data points are applied to compare the fault detection effect in this paper.The results show that if the size of the sliding window is 60 data points,the average fault-free detection ratio is 80.17%in fault-free testing days,and the average fault detection ratio is 88.47%in faulty testing days.

Energy Efficient Air Conditioning System Using Geothermal Cooling-Solar Heating in Gujarat, India

It is well known that one unit of electrical energy saved is equal to more than two units produced. One way of economizing the power is utilization of energy efficient systems at all locations. In the present study, the air conditioning system is analysed and an innovative way is suggested. We use natural low temperature of shallow sub surface (1 - 3 m) of the earth—geothermal cooling system. It is known that majority of the households and the apartment complexes in India have two tanks for water storage. One is the underground water sump and the other is the overhead water tank. In our study, we use these two water storage systems for space cooling during summer and also for heating during winter. The main aim of our paper is air-conditioning of the space in an economic way to save electricity. It is based on a simple idea of transferring the low temperature from underground water sump to the room in the house using water as a mode of transport. Since India is a tropical country located at low latitude, most of the year, the air temperature is high and demands space cooling. However, for a couple of months during severe winter months (Dec.-Jan.) at Ahmedabad, heating of the space is required. For heating the space, we suggest to use the well-known solar water heater. Effective use of heat exchanger is shown through computation, modelling schemes and lab experiment. We recommend geothermal cooling for 10 months in a year and solar hot water system during 2 months of winter. It is observed that the ambient air temperature of 35°C - 40°C in the room can be brought down to 26°C without much consumption of electricity. In a similar manner, the room temperature at night (13°C) during winter in Ahmedabad can be increased to 27°C through circulation of water from solar water heater in the heat exchanger.

Modelling, Transient Simulation and Economic Analysis of Solar Thermal Based Air Conditioning System in Gujarat

Commercial building sector accounts for 8% of the total electricity consumption in India. Cooling activities (HVAC) in commercial buildings consume 55% of the total energy utilized. Consequently, CO2 emissions from conventional buildings in India were estimated to be 98 metric tonnes of CO2 per million ft2 in 2014. Solar thermal air conditioning can be the solution to these demands and can contribute to about 15% to 20% of India’s total oil consumption thereby reducing the dependence on fossil fuels. Hence, the main objective of the work is to model and simulate a solar absorption cooling system for GERMI office building located in Gandhinagar, Gujarat, India, using the transient simulation software ‘TRNSYS’. Cooling load estimation and comfort conditions required for the building were determined based on ASHRAE standards. Evacuated tube collectors were selected because of its market availability, ease of manufacturing and proven technology. Single effect absorption chiller was used because of its commercial availability. The effects of storage tank volume, collector area and collector slope were also investigated for parametric optimization. The results of the simulation and parametric analysis are analyzed and presented in the paper.

Operating Parameters of the District Heating Substation Cooperating With the Installation of Technological Air Conditioning With High Efficiency of Heat Recovery

The article analyses the problem of determining the operating parameters of the district heating substation cooperating with the air heating system in technological air conditioning systems equipped with heat exchangers with high efficiency of heat recovery.Attention was paid to the correct selection of heat exchangers for the heat output balance depending on the heat recovery protection algorithms against a drop in the temperature of the heat transfer surface below 0℃.Critical parameters were determined in Polish climatic conditions,at which the operation of the heat recovery exchanger in the air conditioning system is switched off or limited.It has been proven that the proper functioning of the district heating substation cooperating with the installation of air conditioning with high heat recovery efficiency requires the use of two heat exchangers with different characteristics,equipped with properly selected temperature control systems.The optimal model of cooperation between the technological air conditioning system and the heating substation was also indicated.

Optimization and comparative performance analysis of conventional and desiccant air conditioning systems regenerated by two different modes for hot and humid climates:Experimental investigation

A desiccant air conditioning system is considered a capable alternative to a conventional air conditioning system because of its independent control of temperature,humidity and being eco-friendly.Also,to resolve the problem of more energy consumption for the restoration of a desiccant,structures comprising of desiccant can utilize thermal energy or complete waste heat to revive desiccant material.Therefore,this research work executes an experimental,optimization and comparative examination for conventional and desiccant air conditioning sys-tems regenerated by two different modes,i.e.firstly using(Mode-I)complete waste heat from condenser and secondly using(Mode-II)rod(electric heater)heat for regeneration at different process air inlet temperatures,i.e.(28,29.5,31,32.5,34,35.5 and 37°C),at different process air inlet velocities,i.e.(1.5,2.5,3.5 and 4.5 m/s)and a fix(2.5 m/s)regeneration air inlet velocity.Thus,optimization of performance parameters,i.e.VCOP,ECOP,dehumidification effectiveness,moisture removal capacity(kg/hr),DCOP,regeneration effectiveness and regeneration rate(kg/hr),is identified for achieving maximum efficiency of conventional and desiccant air con-ditioning systems under the above operating conditions.

Model predictive control of indoor thermal environment conditioned by a direct expansion air conditioning system

Temperature and humidity are two important factors that influence both indoor thermal comfort and air quality.Through varying compressor and supply fan speeds of a direct expansion(DX)air conditioning(A/C)unit,the air temperature and humidity in the conditioned space can be regulated simultaneously.However,most existing controllers are designed to minimize the tracking errors between the system outputs with their corresponding settings as quickly as possible.The energy consumption,which is directly influenced by the compressor and supply fan speeds,is not considered in the relevant controller formulations,and thus the system may not operate with the highest possible energy efficiency.To effectively control temperature and humidity while minimizing the system energy consumption,a model predictive control(MPC)strategy was developed for a DX A/C system,and the development results are presented in this paper.A physically-based dynamic model for the DX A/C system with both sensible and latent heat transfers being considered was established and validated by experiments.To facilitate the design of MPC,the physical model was further linearized.The MPC scheme was then developed by formulating the objective function which sought to minimize the tracking errors of temperature and moisture content while saving energy consumption.Based on the results of command following and disturbance rejection tests,the proposed MPC scheme was capable of controlling temperature and humidity with adequate control accuracy and sensitivity.In comparison to linear-quadratic-Gaussian(LQG)controller,better control accuracy and lower energy consumption could be realized when using the proposed MPC strategy to simultaneously control temperature and humidity.

Optimal Scheduling of Residential Heating, Ventilation and Air Conditioning Based on Deep Reinforcement Learning

Residential heating, ventilation and air conditioning(HVAC) provides important demand response resources for the new power system with high proportion of renewable energy. Residential HAVC scheduling strategies that adapt to realtime electricity price signals formulated by demand response program and ambient temperature can significantly reduce electricity costs while ensuring occupants' comfort. However, since the pricing process and weather conditions are affected by many factors, conventional model-based method is difficult to meet the scheduling requirements in complex environments. To solve this problem, we propose an adaptive optimal scheduling strategy for residential HVAC based on deep reinforcement learning(DRL) method. The scheduling problem can be regarded as a Markov decision process(MDP). The proposed method can adaptively learn the state transition probability to make economical decision under the tolerance violations. Specifically, the residential thermal parameters obtained by the leastsquares parameter estimation(LSPE) can provide a basis for the state transition probability of MDP. Daily simulations are verified under the electricity prices and temperature data sets, and numerous experimental results demonstrate the effectiveness of the proposed method.

Aircraft air conditioning system health state estimation and prediction for predictive maintenance

The vast potential of system health monitoring and condition based maintenance on modern commercial aircraft is being realized through the innovative use of Airplane Condition Monitoring System(ACMS) data.However there are few methods addressing the issues of failure prognostics and predictive maintenance for commercial aircraft Air Conditioning System(ACS).This study developed a Bayesian failure prognostics approach using ACMS data for predictive maintenance of ACS.First, a health index characterizing the ACS health state is inferred from a multiple sensor signals using a data driven method.Then a dynamic linear model is proposed to describe the degradation process for failure prognostics.Bayesian inference formulas are carried out for degradation estimation and prediction.The developed approach is applied on a passenger aircraft fleet with ACMS data recorded for one year.The analysis of the case study shows that the developed method can produce satisfactory prognostics results, where all the ACS failure precursors are identified in advance, and the relative errors for the failure time prediction made when just entering the degradation warning stage are less than 8%.This would allow operators to proactively plan future maintenance.

Energy Storage Modeling of Inverter Air Conditioning for Output Optimizing of Wind Generation in the Electricity Market

In order to achieve the compatibility of the air conditioning(AC)loads with the current dispatch models,this pa-per utilizes demand response(DR)technology as energy storage resources to optimize the aggregator’s behaviors in the real-time market for less economic loss caused by the fluctuations of wind power.The inverter AC,as a typical demand response resource,is constructed as a power type battery model(PTBM)and a capacity type battery model(CTBM)according to the different control methods,which are expressed through a circuit model and mathematical model to describe the energy storage characteristics of ACs.Moreover,the comparisons between the PTBM and CTBM are given analytically by their response speed,power&energy capacity and the cost of control,which will be helpful to guide the associated operators to choose the appropriate models to take part in demand response.Considering that the wind generation fluctuates frequently and greatly,the PTBM is chosen to take part of the demand response for output optimizing of the wind generation.The simulation results demonstrate that PTBMs can work in the way of conventional batteries(CBs)to optimize wind generation in the real-time market.

Strategy of constructing virtual peaking unit by public buildings’central air conditioning loads for day-ahead power dispatching

With the gradually widely usage of the air conditioning(AC) loads in developing countries, the urban power grid load has swiftly increased over the past decade.Especially in China, the AC load has accounted for over30% of the maximum load in many cities during summer.This paper proposes a scheme of constructing a virtual peaking unit(VPU) by public buildings’ cool storage central AC(CSCAC) systems and non-CSCAC(NCSCAC)systems for the day-ahead power network dispatching(DAPND). Considering the accumulation effect of different meteorological parameters, a short term load forecasting method of public building’s central AC(CAC) baseline load is firstly discussed. Then, a second-order equivalent thermal parameters model is established for the public building’s CAC load. Moreover, the novel load reduction control strategies for the public building’s CSCAC system and the public building’s NCSCAC system are respectively presented. Furthermore, based on the multiple-rank control strategy, the model of the DAPND with the participation of a VPU is set up. The VPU is composed of large-scale regulated public building’s CAC loads. To demonstrate the effectiveness of the proposed strategy, results of a sample study on a region in Nanjing which involves 22 public buildings’ CAC loads are described in this paper. Simulated results show that, by adopting the proposed DAPND scheme, the power network peak load in the region obviously decreases with a small enough deviation between the regulated load value and the dispatching instruction of the VPU. The total electricity-saving amount accounts for7.78% of total electricity consumption of the VPU before regulation.

Optimal Frequency Regulation Based on Characterizing the Air Conditioning Cluster by Online Deep Learning

The air conditioning cluster(ACC)is a potential candidate to provide frequency regulation reserves.However,the effective assessment of the ACC willing reserve capacity is often an obstacle for existing demand response(DR)programs,influenced by incentive prices,temperatures,etc.In this paper,the complex relationship between the ACC willing reserve capacity and its key influence factors is defined as a demand response characteristic(DRC).To learn about DRC along with real-time frequency regulation,an online deep learning-based DRC(ODLDRC)modeling methodology is designed to continuously retrain the deep neural network-based model.The ODL-DRC model trained by incoming new data does not require massive historical training data,which makes it more time-efficient.Then,the coordinate operation between ODL-DRC modeling and optimal frequency regulation(OFR)is presented.A robust decentralized sliding mode controller(DSMC)is designed to manage the ACC response power in primary frequency regulation against any ACC response uncertainty.An ODL-DRC model-based OFR scheme is formulated by taking the learning error into consideration.Thereby,the ODL-DRC model can be applied to minimize the total operational cost while maintaining frequency stability,without waiting for a well-trained model.The simulation cases validate the superiority of the OFR based on characterizing the ACC by online learning,which can capture the real DRC and simultaneously optimize the regulation performance with strong robustness against any ACC response uncertainty and learning error.

Experimental Research and Optimization on the Environmental Friendly R1234yf Refrigerant in Automobile Air Conditioning System

Currently, the refrigerant used in the automotive air conditioning system is R134 a which has a high global warming potential(GWP) value, so people are eager to find a good replacement for it. According to recent studies, R1234 yf is considered as one of the top candidates to replace R134 a. In this article, the performances of R1234 yf "drop-in" system and the optimization to the R1234 yf system are experimentally studied and investigated.The expansion valve used for the R1234 yf system is optimized by changing the charged fluid and adjusting the spring force. The results indicate that it can improve the performance of R1234 yf system significantly through adjusting the thermostatic expansion valve. For the thermostatic expansion valves(TEVs) charged with R134 a in thermal bulb, the system performance is optimal. Compared to the original expansion valve, for the R1234 yf system applying the adjusted expansion valves, under different working conditions the cooling capacity increases by 11.3% averagely and the coefficient of performance(COP) increases by 8% averagely.

Control Strategies of Large-scale Residential Air Conditioning Loads Participating in Demand Response Programs

Residential air conditioning(RAC)loads have great potential to be included in demand response(DR)programs.This paper studies large-scale RAC loads participating in DR programs,such as modeling,parameters identification,DR characteristics and control strategies.First,an aggregate model of large-scale RAC loads are established based on the buildings’performance with heat storage and insulation,avoiding the calculation of a single RAC model.Then,parameters of the aggregate model are identified based on the RACs’power and outdoor temperatures.Based on the aggregate model,DR characteristics of RAC loads are analyzed,including the dynamic relationship between power,outdoor and indoor temperature,and the potential of DR combined with the users’comfort.Next,the DR control strategies adapted for large-scale RAC loads are established by adjusting the temperature set-points.The DR strategies consider users’comfort and calculate the control signals of each RAC load according to the DR power,including adjustment temperature and adjustment time,which are sent to each RAC load for execution.In the DR process,the control center does not need to obtain the users’indoor temperature,which is conducive to protecting the users’privacy.DR strategies of RAC loads when the control degree within/beyond the DR potential are both proposed,and a load recovery control strategy is also introduced.Finally,the effectiveness and accuracy of the proposed model and DR control strategies are verified by simulation results.

A new ventilation mode of air conditioning in subway vehicles and its air distribution performance

The traditional ventilation mode of subway vehicles adopts the form that the inlets and outlets are placed on the upper part of the cabin.The air distribution formed in this mode often cause serious problems of thermal comfort and energy consumption.In order to solve these problems caused by the traditional ventilation mode,a new hybrid ventilation mode was proposed.The hybrid ventilation mode uses both upper and underside air supply inlets.A method for evaluating the air distribution performance of subway air conditioning was developed.The method applies non-uniformity coefficients,maximum temperature difference,air diffusion performance index,modified energy utilization coefficient and Air short-circuit comprehensive coefficient.Air short-circuit comprehensive coefficient was a new index to evaluate the degree of air short-circuit of supply air.Based on the airflow simulation,the air distribution performance for the hybrid ventilation mode was evaluated using these indexes,and compared with the traditional ventilation mode.The results show that compared with the traditional ventilation mode,the hybrid ventilation mode has more uniform temperature distribution,better thermal comfort,higher energy utilization efficiency and lower degree of air short-circuit of supply air.

Modelling of a Two-Phase Thermosyphon Loop for Passive Air-Conditioning of a House in Hot and Dry Climate Countries

The two-phase thermosyphon loop is an efficient solution for space cooling. This paper presents the simulation results of numerical studies on the heat transfer and thermal performance of a two-phase thermosiphon loop for passive air-conditioning of a house. The fluid considered in this study is methanol, which is compatible with copper and is environmentally friendly. These numerical results show that the temperature at the evaporator wall drops from 23°C to 13°C and increases at the condenser. The solar flux density has a strong influence on the condenser temperature. The mass flow rates and masses at the evaporator and condenser increase with temperature. The variation of evaporating and condensing temperature affects the performance of the system. For a constant evaporating and condensing temperature of 2°C and 29°C, the COP is 0.77 and 0.84 respectively. With these results, the use of the two-phase thermosyphon loop in air conditioning is possible to obtain a thermal comfort of the occupants acceptable by the standards but with a large exchange surface of the evaporator.

Characteristic studies of heat sources and performance analysis of free-cooling assisted air conditioning and ventilation systems for working faces of mineral mines

High temperature heat hazard at mineral mine becomes more and more serious as the increase of mining depth.Heat sources at working faces of mineral mines are complex and are of different characteristics,presenting new challenges for air conditioning systems.In this paper,heat sources at four types of working faces are summarized and their characteristics are investigated.Based on this,simplified equations,which are linear with length of working faces,are proposed to calculate heat dissipation rates.So that the main heat sources of different working faces can be found,and cooling load of air conditioning systems can be calculated.Then,considering main heat sources of coal mines,a typical working face is designed to investigate performances of different ventilation systems and air conditioning systems.Simulation results show that segmented ventilation systems(SC)and heat shield assisted centralized ventilation systems(CCHS)can realize much better temperature distributions at working faces.However,cooling load can be greatly reduced for CCHS,when untreated air is supplied to the coal seam side.Based on this,free cooling assisted air conditioning systems are designed,and annual average energy efficiency ratio(EERann)of the systems are investigated and compared between direct evaporate cooling and indirect evaporate cooling(IEC).For SC,as compared with scenarios without free-cooling,IEC can increase EERann by 15%-23%and 22%-32%under Benxi and Datong ambient conditions,respectively.Besides,to ensure high EERann,CCHS is preferred and it is essential to increase thermal insulation of air ducts.

A Lightweight Compact Lithium-Ion Battery Thermal Management System Integratable Directly with EV Air Conditioning Systems

This paper discusses an improved thermal management system to ameliorate the performance of lithium-ion battery storage systems for electric vehicles(EVs) applications. A compact and lightweight cold plate is designed and fabricated to fit 18650-type lithium-ion batteries, using aluminum-finned copper tubes. A dynamic temperature PID(proportional, integral, differential) control algorithm for electronic expansion valves is developed to study using EV air conditioning refrigerant, R134a, to control battery modules’ temperature with this compact and lightweight thermal management system. The experimental results show that the proposed battery thermal management system can effectively control the battery module’s temperature. In addition, during 1C discharge, when the PID temperature algorithm control scheme is used, the maximum temperature difference across the battery module peaks at less than 4℃, and the maximum temperature within the battery module is less than 36℃.