A Comparison of Methods to Verify Energy-Saving Benefits for Chillers

The simulation model for performance of chiller (ASHRAE model in this study) disclosed in ASHRAE Guideline 14 in 2002 is implemented in Taiwan to verify the efficiency of energy-saving methods adopted by energy service companies (ESCO). Since the accuracy of the simulation model for performance of chillers has influenced on the promotion of the ESCO business, the author used practical measurement data to compare the accuracy between the ASHRAE model and the commonly used energy consumption model of chillers (XY model in this study) and concluded that the XY model had much higher accuracy than the ASHRAE model.

Modelling of Chillers for Energy Performance Assessment of HVAC Systems

The reliable assessment of the annual energy demand has become necessary in view of building energy performance certification. Accurate models must be used to simulate the behaviour of HVAC （heating, ventilation and air conditioning） components in real operation, usually characterized by a wide variation of building loads. In this context, this paper deals with the development and validation of an algorithm aimed at the assessment of part load performance of various kinds of controls for vapour compresion based heat pumps and chillers, in particular referring to on-off, inverter-driven and multi-stage vapour compression. The reliability of this algorithm in the calculation of seasonal performances is checked against monitoring of heat pumps and chillers operating under real conditions.

A performance prediction method for on-site chillers based on dynamic graph convolutional network enhanced by association rules

Accurately predicting the chiller coefficient of performance(COP)is essential for improving the energy efficiency of heating,ventilation,and air conditioning(HVAC)systems,significantly contributing to energy conservation in buildings.Traditional performance prediction methods often overlook the dynamic interaction among sensor variables and face challenges in using extensive historical data efficiently,which impedes accurate predictions.To overcome these challenges,this paper proposes an innovative on-site chiller performance prediction method employing a dynamic graph convolutional network(GCN)enhanced by association rules.The distinctive feature of this method is constructing an association graph bank containing static graphs in each operating mode by mining the association rules between various sensor variables in historical operating data.A real-time graph is created by analyzing the correlation between various sensor variables in the current operating data.This graph is fused online with the static graph in the current operating mode to obtain a dynamic graph used for feature extraction and training of GCN.The effectiveness of this method has been empirically confirmed through the operational data of an actual building chiller system.Comparative analysis with state-of-the-art methods highlights the superior performance of the proposed method.

Fault detection for centrifugal chillers using a Kernel Entropy Component Analysis (KECA) method

Fault detection is beneficial for chiller routine operation management in building automation systems.Considering the limitations of traditional principal component analysis(PCA)algorithm for chiller fault detection,a so-called kernel entropy component analysis(KECA)method has been developed and the development results are reported in this paper.Unlike traditional PCA,in KECA,the feature extraction or dimensionality reduction is implemented in a new space,called kernel feature space.The new space is nonlinearly related to the input space.The data set in the kernel feature space is projected onto a principal component subspace constructed by the feature space principal axes determined by the maximum Rényi entropy rather than the top eigenvalues.The proposed KECA is more suitable to deal with nonlinear process without Gaussian assumption.Using the available experimental data from ASHRAE RP-1043,seven typical chiller faults were tested by the proposed KECA method,and the results were compared to that of PCA.Two statistics,i.e.T2 and squared prediction error(SPE),were employed for fault detection monitoring.The fault detection results showed that the proposed KECA method had a better performance in terms of a higher detection accuracy in comparison to the traditional PCA.For the seven typical faults,the fault detection ratios were over 55%,even at their corresponding least severity level when using the proposed KECA based chiller fault detection method.

A statistical-based online cross-system fault detection method for building chillers

Practical applications of data-driven fault detection(FD)are limited by their portability.The costs of model training and validation are extremely high when each system requires a model retrained on its own fault and fault-free data.Therefore,this paper proposes a statistical-based online cross-system FD method to address the problem of model portability.The proposed FD model can be cross-utilized between building chillers with various specifications while it only needs to update the original fault detection model by the normal operation data of the new chiller system,thus saving huge fault experimental costs for the fault detection of new chiller.First,a theoretical basis for the proposed cross-system fault detection method is presented.Then,experiments were conducted on three building chillers with different specifications.Both fault and fault-free data were collected from the three chillers.The development and validation of the proposed cross-system fault detection method are then conducted.Results show that the cross-system fault detection models perform well when used with different chillers.For instance,when the fault detection model of system#1 was cross-utilized to system#2,the detection accuracies of refrigerant leakage,refrigerant overcharge,and reduced evaporator water flow were 99.73%,90.17%,and 96.94%,respectively.Compared with original models,the detection accuracies were improved by 33.78%,84.07%,and 65.56%,respectively.Therefore,the proposed cross-system fault detection method has potential for online application to practical engineering FD.

Impact of Numerous Beds Operating Conditions for Enhancing the Performance of a Solar Heat-Supported Adsorption Chiller

Thermal adsorption cooling systems have gained significant attention due to their potential for energy savings and eco-environmental impact. An analytic investigation of the heat transfer inside an adsorption chiller with various bed silica gel-water pairs is presented. A comprehensive model has been designed to accurately predict the correlation between the overall performance of the proposed chiller system and the functional and structural condition of the building. This model takes into account various factors such as temperature, humidity, and air quality to provide a detailed analysis of the system’s efficiency. At least 20 collectors consisting of a 34.4 m area (each) with a full-cycle time of 480 seconds are essential to improper run conditions. It is necessary to adjust the optimum cycle time for optimal performance. During the investigation, the base condition shows that the cooling capacity is 14 kw, 0.6 COPcycle, and 0.35 COPsolar at noon. Also, conduct a thorough investigation into the chiller’s performance under varying cooling water supply temperatures and various chilled water flow rates.

Performance of a Solar-Biomass Adsorption Chiller

A dynamic model is presented for a chiller working with a composite adsorbent(silica activated carbon/CaCl2)–water pair in a solar-biomass cooling installation.The main objective is determining a link between two possible evaporator configurations and the refrigerator’s performances.The two considered evaporators work at different pressure levels.The related time evolution profiles of temperature,pressure and water content are studied.Moreover,the effects of hot water inlet temperature and cooling water inlet temperature on the specific cooling capacity(SCP)and coefficient of performance(COP)are predicted by means of numerical simulations.The results show that an increase in the temperature of hot water and a decrease in the temperature of the cooling water allow an increase in COP and SCP.In particular,for a hot water inlet temperature of 85°C and a cooling water inlet temperature of 40°C,the COP and Qev are 0.67 and 4.3 kW,respectively.

Optimization of Chiller Loading Problem Using Improved Golden Jackal Optimization Algorithm Leads to Reduction in Energy Consumption

This paper proposes a modified golden jackal optimization(IGJO)algorithm to solve the OCL(which stands for optimal cooling load)problem to minimize energy consumption.In this algorithm,many tools have been developed,such as numerical visualization,local field method,competitive selectionmethod,and iterative strategy.The IGJO algorithm is used to improve the research capabilities of the algorithm in terms of global tuning and rotation speed.In order to fully utilize the effectiveness of the proposed algorithm,three famous examples of OCL problems in basic ventilation systems were studied and compared with some previously published works.The results show that the IGJO algorithm can find solutions equal to or better than other methods.Underpinning these studies is the need to reduce energy consumption in air conditioning systems,which is a critical business and environmental decision.The Optimal Chiller Load(OCL)problem is well-known in the industry.It is the best method of operation for the refrigeration plant to satisfy the requirement of cooling.In order to solve the OCL problem,an improved Golden Jackal optimization algorithm(IGJO)was proposed.The IGJO algorithm consists of a number of parts to improve the global optimization and rotation speed.These studies are intended to address more effectively the issue of OCL,which results in energy savings in air-conditioning systems.The performance of the proposed IGJO algorithm is evaluated,and the results are compared with the results of three known OCL problems in the ventilation system.The results indicate that the IGJO method has the same or better optimization ability as other methods and can improve the energy efficiency of the system’s cold air.

Possibilities of Using Solar Energy in District Cooling Systems in the Mediterranean Region

Use of district heating and cooling systems has many environmental advantages compared to individual heating and cooling. Recent advances in solar energy technologies for heat and power generation have reduced their cost and promoted their use instead of fossil fuels. Solar-PV energy for electricity generation and solar thermal energy for hot water production are broadly used today. Solar energy resources in the Mediterranean region are abundant while space cooling in buildings is required when solar irradiance is high. The possibility of using solar energy for fuelling water chillers providing cold water in district cooling systems in the Mediterranean basin has been investigated. Existing literature and studies concerning the use of district cooling systems globally as well as the energy sources used in them have been examined. Solar-PV energy combined with compression chillers and solar thermal energy combined with thermally driven chillers can be used for cold water production. Their overall efficiencies, converting solar energy to cold water, vary between 22% and 56% compared with 45% for compression chillers using grid electricity. It is concluded that various solar energy technologies could be used with different types of water chillers for fuelling district cooling networks in the future in the Mediterranean region.

燃气热泵(GHP)水系统中央空调的应用探讨

天然气作为一种清洁、高效、方便、燃烧充分的能源,应用越来越广泛。随着我国经济的快速发展、环境保护政策的加强和一系列天然气工程基础设施建设的完成,天然气用量在我国的能源结构中所占比例将逐步提高,以燃气为能源的空调设备也将有良好的发展前景。本文主要介绍了燃气热泵(GHP)水系统中央空调(简称GHPchiller机组)的工作原理、特点、系统设计注意事项及对其发展前景进行探讨。

Performance analysis on a novel water chiller using liquid desiccant

A new type of liquid desiccant water chiller for applications on air-conditioning and refrigeration is introduced.The system can be driven by low-grade heat sources with temperatures of 60 to 80 ℃,which can be easily obtained by a flat plat solar collector,waste heat,etc.A numerical model is developed to study the system performance.The effects of different parameters on performance are discussed,including evaporating temperature,regenerating temperature,ambient condition,and mass flow rates of closed moist air and regenerating air.The results show that an acceptable performance of a cooling capacity of 2.5 kW and a coefficient of performance of 0.37 can be achieved in a reference case.The regenerating temperature and the humidity ratios of ambient air are two main factors affecting system performance,while the temperature of ambient air functions less.In addition,the mass flow rate of regenerating air and closed moist air should be carefully determined for economical operation.

Economical Evaluation of a Low-Enthalpy Geothermal Resource Located in an Arid-Zone Area

In this work an economical evaluation that established the viability of a low enthalpy geothermal resource as an energy source in north Africa is presented. The factors considered included the payback period, average rate of return, net present value, and net benefit-cost ratio. The model was based on utilising the energy source to energise four models that comprised thermal equipment consisting of water/air cooled single/half effect lithium bromide water mixture absorption chillers and an R-245fa organic Rankine cycle. These modelled cycles were based on the energy demand for Waddan city a community in southern Libya which has a demand for combined cooling/electricity only or cooling/electricity with district hot water supply. The results revealed that all of the proposed simulated stand-alone models, except the water-cooled half effect chiller, are not economically viable unless they are heavily subsidized or combined with the district hot water supply at least in the winter season.

Development of Blast Chilling Method for Cooked Meat Dishes

In order to ensure hygienic end-product realization, it is necessary as soon as possible to chill it by using efficient methods, such as blast chilling. Blast chill equipment provides food chilling optimum for 90-120 min to ＋3 ℃, reaching an internal temperature of food particularly for the perishable ready-to-eat product groups, including meat dishes, which are used as a reference model in this study. The aim of the research is to reduce duration of the chilling process at the same time providing equipollent microbiological indices of the product to be chilled, which could enable carrying out its storage in a chilled condition for several days. For this study, two types of meat dishes were used---pork goulash and minced meat sauce. Research results show that by combining the food safety standards and cost-efficiency, chilling final temperature of blast chilling was in the range of ＋3 ℃-＋1 1 ℃, followed by further storage in refrigerator. It was recommended to stop the blast chilling at ＋7 ℃＋1 1 ℃ temperature range, depending on the required shelf life for the ready-to-eat product. It is therefore essential to encourage the blast chilling process, reducing its duration and enabling to optimize the overall process.

The “All in One”Smart Solar Cooling System

The need for moving away from traditional energy sources and to find alternate energy sources is undoubtedly one of the primary objectives for a sustainable progress to humankind. The design and construction of buildings in hot-humid climates requires high energy consumption typically for air conditioning due to higher thermal loads. In the Gulf Region, there is a rising concern on the current rate of energy consumption due to air conditioning, i.e. two thirds of domestic electrical loads. Considering the wider impacts of carbon emissions on our climate, and the need to reduce these emissions, effective energy efficiency solutions are necessary in order to achieve the overall goal of reducing carbon emissions. This paper presents the performance of the “All in One” fully integrated solar desiccant air conditioning system. The superefficient air conditioning system can provide 1,000 to 2,000 litre/s treated fresh air at supply temperature of 16 °C with 60% reduction in energy consumption compared to conventional systems. The system is locally manufactured and installed.

Optimum control strategy for all-variable speed chiller plant

The optimum control strategy and the saving potential of all variable chiller plant under the conditions of changing building cooling load and cooling water supply temperature were investigated. Based on a simulation model of water source chiller plant established in dynamic transient simulation program (TRNSYS),the four-variable quadratic orthogonal regression experiments were carried out by taking cooling load,cooling water supply temperature,cooling water flow rate and chilled water flow rate as variables,and the fitting formulas expressing the relationships between the total energy consumption of chiller plant with the four selected parameters was obtained. With the SAS statistical software and MATHEMATICA mathematical software,the optimal chilled water flow rate and cooling water flow rate which result in the minimum total energy consumption were determined under continuously varying cooling load and cooling water supply temperature. With regard to a chiller plant serving an office building in Shanghai,the total energy consumptions under different control strategies were computed in terms of the forecasting function of cooling load and water source temperature. The results show that applying the optimal control strategy to the chiller plant can bring a saving of 23.27% in power compared with the corresponding conventional variable speed plant,indicating that the optimal control strategy can improve the energy efficiency of chiller plant.

Chiller faults detection and diagnosis with sensor network and adaptive 1D CNN

Computer-empowered detection of possible faults for Heating,Ventilation and Air-Conditioning(HVAC)subsystems,e.g.,chillers,is one of the most important applications in Artificial Intelligence(AI)integrated Internet of Things(IoT).The cyber-physical system greatly enhances the safety and security of the working facilities,reducing time,saving energy and protecting humans’health.Under the current trends of smart building design and energy management optimization,Automated Fault Detection and Diagnosis(AFDD)of chillers integrated with IoT is highly demanded.Recent studies show that standard machine learning techniques,such as Principal Component Analysis(PCA),Support Vector Machine(SVM)and tree-structure-based algorithms,are useful in capturing various chiller faults with high accuracy rates.With the fast development of deep learning technology,Convolutional Neural Networks(CNNs)have been widely and successfully applied to various fields.However,for chiller AFDD,few existing works are adopting CNN and its extensions in the feature extraction and classification processes.In this study,we propose to perform chiller FDD using a CNN-based approach.The proposed approach has two distinct advantages over existing machine learning-based chiller AFDD methods.First,the CNN-based approach does not require the feature selection/extraction process.Since CNN is reputable with its feature extraction capability,the feature extraction and classification processes are merged,leading to a more neat AFDD framework compared to traditional approaches.Second,the classification accuracy is significantly improved compared to traditional methods using the CNN-based approach.

Study on Buildings CCHP System Based on SOFC

The relationship among the working temperature,pressure and current density of a Solid oxide fuel cell(SOFC)and its output power and efficiency are analyzed in the framework of a theoretical model able to provide,among other things,the volt ampere characteristic curve.In particular,following the principle of temperature matching and cascade utilization,we consider a gas turbine(GT)and a LiBr absorption chiller to recycle the high-grade exhaust heat produced by the considered SOFC.This distributed total energy system is set up with the intent to meet typical needs of buildings for cooling,heating and power(CCHP).The total power generated by the considered SOFC and gas turbine is about 222 kW and the total power generation efficiency by low heat value of fuel(LHV)is 63.7%.In the CCHP system,the high temperature exhaust of GT is further used to drive LiBr absorption unit,which can produce about 34.8 kW cooling capacity or 84.5 kW of heat(the total energy utilization 78.03%).

Thermodynamic and Experimental Analysis of an Ammonia-Water Absorption Chiller

A single stage ammonia-water absorption chiller with complete condensation is designed, built and tested. The apparatus is designed for a cooling capacity of 2814 W, which is obtained using electric heater as heating source. The thermodynamic models have been derived using the First and Second Laws. Calculated results are compared with experimental data. The results show that the cooling capacity of experimental apparatus is found between 1900 and 2200 W with the actual coefficient of performance (COP) between 0.32 and 0.36. The contribution of the components to internal entropy production is analyzed. It shows that the larger irreversibility is caused by spanning the largest temperature and dissipated thermal energy by heat transfer losses at the generator and evaporator. In the experimentation, the low pressure is lower than the designed value. This is a consequence of a large capacity in the falling film absorber which performs as expected. This decreases the evaporation pressure, and the evaporating temperature could be reduced to the designed value.

Energy, Exergy and Thermoeconomics Analysis of Water Chiller Cooler for Gas Turbines Intake Air Cooling

Gas turbine (GT) power plants operating in arid climates suffer a decrease in output power during the hot summer months because of the high specific volume of air drawn by the compressor. Cooling the air intake to the compressor has been widely used to mitigate this shortcoming. Energy and exergy analysis of a GT Brayton cycle coupled to a refrigeration air cooling unit shows a promise for increasing the output power with a little decrease in thermal efficiency. A thermo-economics algorithm is developed to estimate the economic feasibility of the cooling system. The analysis is applied to an open cycle, HITACHI-FS7001B GT plant at the industrial city of Yanbu (Latitude 24o 05” N and longitude 38o E) by the Red Sea in the Kingdom of Saudi Arabia. Result show that the enhancement in output power depends on the degree of chilling the air intake to the compressor (a 12 - 22 K decrease is achieved). For this case study, maximum power gain ratio (PGR) is 15.46% (average of 12.25%), at an insignificant decrease in thermal efficiency. The second law analysis show that the exergetic power gain ratio drops to an average 8.5%. The cost of adding the air cooling system is also investigated and a cost function is derived that incorporates time-dependent meteorological data, operation characteristics of the GT and the air intake cooling system and other relevant parameters such as interest rate, lifetime, and operation and maintenance costs. The profit of adding the air cooling system is calculated for different electricity tariff.

Energy Performance Analysis of Ice Thermal Storage for Commercial HVAC Systems

Ice thermal storage is a promising technology to reduce energy costs by shifting the cooling cost from on-peak to off-peak periods. The paper investigates the application of ice thermal storage and its impact on energy consumption, demand and total energy cost. Energy simulation software along with a chiller model is used to simulate the energy consumption and demand for the existing office building located in central Florida. Furthermore, the study presents a case study to demonstrate the cost saving achieved by the ice storage applications. The results show that although the energy consumption may increase by using ice thermal storage, the energy cost drops significantly, mainly depending on the local utility rate structure. It found that for the investigated system the annual energy consumption increases by about 12% but the annual energy cost drops by about 3 6%.