Central Air Conditioning System Research Articles

Barriers to implement energy efficiency strategies to heating, ventilation, air conditioning of airside system in commercial buildings in Sri Lanka

At present, debates on climate change, fossil fuel depletion, and energy saving highlight the need for a sustainable built environment to reduce energy consumption and emission trends. The Heating, Ventilation, and Air Conditioning (HVAC) system is a priority due to its significant share of a building’s electricity consumption. While energy efficiency strategies for central air conditioning systems focus on both waterside and airside components, implementing airside efficiency strategies is notably lacking in Sri Lanka. This is a concern because airside inefficiencies lead to excessive energy use, higher operational costs, and compromised indoor air quality. Thus, the study aims to address this gap by identifying the barriers to implementing energy efficiency strategies for HVAC airside systems in Sri Lankan commercial buildings. To explore these barriers, a qualitative research approach was employed, involving interviews with 17 industry experts. The study identified 27 barriers, with key barriers being a lack of technical expertise, rapid technological advancements, misalignment with organisational objectives, limited financial resources, inadequate training and technical knowledge, and insufficient regulatory support. The insights gained from this study can assist industry professionals in enhancing HVAC energy performance and encourage further academic research on this sub-branch of HVAC systems in the Sri Lankan context.

Performance Evaluation of a central air conditioning system using condensate as a discharge line cooler

The energy consumption by central air conditioning (A/C) in a building is very high and efforts to reduce this energy consumption is ongoing. This study investigates the use of condensate produced by the evaporator inside the air handling unit (AHU) to cool the compressor discharge line. A central A/C with a direct expansion (DX) system and a compressor capacity of about 25 HP which uses R22 as a working fluid was used. The discharge line has a diameter of 15.9 mm wrapped with a 520 mm long heat exchanger with diameter 50 mm. The condensate produced by the AHU is passed to the heat exchanger that envelops the discharge line. The use of discharge line cooler could reduce the input power from 18.21 kW to 17.54 kW. On the other hand, the cooling capacity increased from 46.44 kW to 49.11 kW. This means that discharge cooler reduces the input power by 3.8% and increases the cooling capacity by 5.7%. As a result, the COP increases by 9.8%, from 2.5 to 2.8. The method developed is not complex and only simple modification is required, thus an improvement of the performance of a central A/C system can be achieved.

Hybrid forecasting model of building cooling load based on EMD-LSTM-Markov algorithm

Precise forecasting of the cooling load (CL) of buildings is crucial for the efficient functioning of central air conditioning systems. The study proposed a new hybrid model based on empirical modal decomposition (EMD) and Markov chain improved LSTM neural network, denoted as EMD-LSTM-Markov. First, Pearson’s correlation coefficient (PCC) and Gradient Boosting Decision Tree (GBDT) are used to extract features with a high degree as the input data. Then, the LSTM is employed to establish a prediction model. Finally, to verify the validity and prediction accuracy of the proposed model, this paper selects the CL data of an office building in Guangzhou as the research sample. The results show that the Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) of the EMD-LSTM-Markov model are 4.53 and 0.84%. Compared with the other three predicting models, the RMSE and MAPE values of EMD-LSTM-Markov are decreased by 40% − 94% and 70% − 96%, which has better performance in accuracy and stability. It testifies that the proposed strategy is reliable and effective. This work successfully resolves the issue of delayed cold response. The hybrid model proposed demonstrates significant energy-saving potential for accurately predicting building CLs and enhancing the optimal control of cooling systems. Future research should explore the hybrid model’s robustness across different building types and climatic regions.

Enhancing the performance of photovoltaic using exhausted air from thermal comfort spaces

This paper presents an experimental investigation using the exhaust air from the central air conditioning system as cooling air for the PV modules. Experimental tests were conducted under harsh outdoor weather conditions in Baghdad, Iraq, during the summer session, where the recorded ambient temperature was around 33 to 47 °C. In this study, the exhaust air was flowing in the back side of the PV module to reduce the operating temperature of the PV module and thus improve its performance and electrical efficiency. The results show that the temperature of the PV module decreased from 62.42 to 47.42 °C, the output voltage increased from 14.28 to 16.17 V, the generated electrical power increased from 80.39 to 87.89 W, and the electrical efficiency increased from 13.88% to 15.18%. Overall, the enhancement percentage of the PV temperature, voltage, power, and electrical efficiency is 23.7%, 13%, 9.33%, and 9.33%, respectively, compared to the PV module without cooling.

Analysis of the Energy-Saving Effect of a Novel Central Air-Conditioning System with an Internal Heat Exchanger in Summer

In this paper, a novel central air-conditioning system with an internal heat exchanger is proposed and analyzed for its energy-saving effect. Two frequently used systems are chosen as the reference systems, i.e., a conventional system with a sensible heat exchanger (Reference System I) and a conventional system with a total heat exchanger (Reference System II). Analysis models are built to simulate the performance of the system. The energy-saving effects of the proposed system and the two reference systems under different conditions are theoretically calculated using a case-studied shopping mall in Nanjing, China. The results show that the influence of indoor relative humidity (RH) on the energy-saving effect is much greater than that of the indoor design temperature. Indoor design parameters have a greater impact on energy saving than outdoor design parameters. Under the studied conditions, the maximum energy-saving rates of the proposed system, Reference System I, and Reference System II, are 52.7%, 2.3%, and 12.1%, respectively. With the decrease in fresh-air ratio from 70% to 20%, the difference in energy-saving rates between the proposed system and Reference System II (Reference System I) can increase from 5% to 23% (15% to 30%). Therefore, the proposed system has obvious energy-saving potential and advantage, especially under the condition of a lower fresh-air ratio.

COMPARATIVE EXERGY ANALYSIS OF ADIABATIC AND ISOTHERMAL HUMIDIFICATION IN A DIRECT-FLOW CENTRAL AIR CONDITIONING SYSTEM

Central air conditioning systems of buildings and structures are significant consumers of electric and thermal energy of different temperature levels and are the least economical in terms of energy consumption. When designing these systems, due attention is not always paid to assessing their energy efficiency and no variant design is carried out with a comparison of the relevant indicators. This is due to the lack of proven engineering methods. The exergy method of analysing energy-consuming systems provides a correct numerical assessment of energy efficiency and enables a comparative analysis of circuit solutions and system elements. In contrast to the energy method, the peculiarity of the exergy method in relation to air conditioning systems is the possibility of taking into account all available mass and energy flows in the system in exergy units. The extension of the exergy method to systems for creating and maintaining a microclimate in buildings and structures has not yet acquired the status of practical engineering support. This article presents an example of an exergy analysis based on the original methodology for comparing methods of humidification in a central air conditioning system for a public building in order to select the best method in terms of energy efficiency. Two traditional methods of air humidification for the cold season - adiabatic and isothermal - were used for the study and comparison. The results of analytical studies are presented in the form of relative values of exergy.

Numerical analysis for the design of a central air conditioning system for center of excellence

The temperature of the towing tank floor of the Center of Excellence in Marine and Offshore Engineering, Rivers State University needs regulation due to the high level of humidity during experiments. Since vapor evaporates from the towing-tank liquid column, the need for central air conditioning is timely. With the temperature regulated, it will help enhance the comfort of the students and improve the working condition of the staff and equipment. This is achieved by conducting a cooling load analysis, consistent with ASHRAE Guidelines, on the floor plan of the Laboratory building that provided useful information on the proper selection and sizing of fit-for-purpose air-conditioning equipment. Analysis revealed a total sensible and latent heat load of 59195.74 W with system capacity of 16.91TR (tons). Duct design utilizing the Velocity Reduction method resulted in a main supply duct length of 57m and flow are of 0.72m2 incorporating four branched ducts measuring 6m each in length and flow area of 1.05m2

CONFUSION OF REAL SITE IMPLEMENTATION OF VSD UTILIZATION ON WATER PUMP OF A CHILLER PLANT SYSTEM IN OFFICE BUILDING JAKARTA

The utilization of VSD in centralized air conditioning systems has been applied for years for efficiency purposes. However, found in real implementation has not been really applied as its function yet. This paper will present real site implementation of applying VSD on regulating the motor speed of chilled water pump as its function [1] to control the chilled water flow rate [2] go into the evaporator to let the chiller work as correspond on cooling demand at the actual load level and at its necessary power input. By analyzing some related parameters such as temperature, water pressure and amperes measured and observed to be the raw data then they will show the working performance of chiller impact on energy consumed to be evaluated on its efficiency impact. Found the real implementation at this site the VSD does not look like varying the speed of motor pump as usually applied but more by being set at certain frequency such as 32 Hz. Then mostly the chiller cannot be run as high as cooling demand as running at only about 50-60% as lower chilled water flow rate flowing into the evaporator. Other than that it looks efficiency of refrigeration effect on handling the building load is not good enough as mentioned in catalogue/reference with difficulties on reaching the target chilled water leaving temperature.

Pentagon Found Daily, Metagenomic Detection of Novel Bioaerosol Threats to Be Cost-Prohibitive: Can Virtualization and AI Make It Cost-Effective?

In 2022, the Pentagon Force Protection Agency found threat agnostic detection of novel bioaerosol threats to be "not feasible for daily operations" due to the cost of reagents used for metagenomics, cost of sequencing instruments, and cost of labor for subject matter experts to analyze bioinformatics. Similar operational difficulties might extend to many of the 280,000 buildings (totaling 2.3 billion square feet) at 5,000 secure US Department of Defense military sites, 250 Navy ships, as well as many civilian buildings. These economic barriers can still be addressed in a threat agnostic manner by dynamically pooling samples from dry filter units, called spike-triggered virtualization, whereby pooling and sequencing depth are automatically modulated based on novel biothreats in the sequencing output. By running at a high average pooling factor, the daily and annual cost per dry filter unit can be reduced by 10 to 100 times depending on the chosen trigger thresholds. Artificial intelligence can further enhance the sensitivity of spike-triggered virtualization. The risk of infection during the 12- to 24-hour window between a bioaerosol incident and its detection remains, but in some cases it can be reduced by 80% or more with high-speed indoor air cleaning exceeding 12 air changes per hour, which is similar to the rate of air cleaning in passenger airplanes in flight. That level of air changes per hour or higher is likely to be cost-prohibitive using central heating ventilation and air conditioning systems, but it can be achieved economically by using portable air filtration in rooms with typical ceiling heights (less than 10 feet) for a cost of approximately $0.50 to $1 per square foot for do-it-yourself units and $2 to $5 per square foot for high-efficiency particulate air filters.

Design of a Novel Creel Conditioning System for Circular Knitting Machines

Maintaining a certain humidity level of humidity in yarn packages and removing fibre fly from the environment is very important for production efficiency and product quality in textile mills. Humidity has a significant effect on the quality and efficiency of fabrics, especially those made from hydrophilic fibres. The high temperature and low humidity level in the factory environment results in lower yarn strength and higher yarn breakage. The solution is to provide optimum temperature and humidity levels through a central air conditioning system. However, conditioning the entire factory environment is an expensive approach and does not facilitate satisfactory production efficiency. In this study, a new creel system for circular knitting machines was designed to provide excellent yarn package conditioning. More efficient production and economical conditioning were achieved with this new creel system.

Short-term cooling load prediction for central air conditioning systems with small sample based on permutation entropy and temporal convolutional network

In air-conditioning load predicting, the mainstream methods mainly include mechanism model based methods and data-driven prediction methods. The mechanism model can achieve accurate prediction, but are normally used to predict non-existent buildings and by default have to make several assumptions regarding post occupancy. This study proposes a novel data-driven short-term cooling load prediction method based on historical data of the existing buildings to improve the prediction performance when the size of the training sample datasets, including load data and air conditioning internal operation data, is small. Firstly, an improved version of variational mode decomposition (IVMD) technique is proposed to deconstruct complex historical cooling load signals. Then, the permutation entropy and Savitzky-Golay (PE-SG) smoothing method is developed to extract singles with distinct characteristics and high regularity, which comprises multiple single-component amplitude and frequency modulation (AFM) signals, thus mitigating the interference of noise in predictive accuracy. Subsequently, a data-driven model based on temporal convolutional network (TCN) is constructed, which effectively alleviates the risks of over-fitting and under-fitting. Finally, the efficacy of the proposed method is validated through two case studies, and the obtained results show that the issues confronted by small sample datasets are adeptly solved by this method. The precision of prediction is significantly enhanced according to the comparison to other traditional models, showcasing greater stability and generalization ability.

Field Study of a Liquid-Desiccant Central Air-Conditioning System for an Apartment Building

Field Study of a Liquid-Desiccant Central Air-Conditioning System for an Apartment Building

Energy efficiency optimization analysis for a cooling composite air conditioning system for internet data centers

In this study, a validated mathematical model for a composite air conditioning system was established based on onsite test data. The system consists of a refrigerant pump driven two-phase cooling loop (RPTCL) and vapor compression refrigeration (VCR) cycles. The system can be switched to refrigerant pump (RP) mode, compressor mode, or hybrid mode, according to the outdoor temperature. By analyzing, the inadequacy of the existing Internet Data center (IDC) air conditioning system operation strategy was confirmed, and subsequently, five optimization strategies were proposed. The optimization strategies took two identical composite air conditioning systems as optimization unit, and under the premise of meeting the demand for cooling capacity, maximizing the operating time of RP and hybrid mode, which with higher energy efficiency, through complementary cooling capacity, to reduce the energy consumption. Meanwhile, when the cooling supply was higher than the demand, paired with optimization unit’s ON/OFF ratio control, the unit’s energy consumption was further reduced. The most optimization strategy provided 525.6 MWh of cooling energy to meet demand while consuming a minimum of 182.5 MWh. The optimization strategy also achieved a minimum of 12.1% and a maximum of 52.5% energy savings for IDCs in other climate zones of China.

Study on Sensor Fault-Tolerant Control for Central Air-Conditioning Systems Using Bayesian Inference with Data Increments.

A lack of available information on heating, ventilation, and air-conditioning (HVAC) systems can affect the performance of data-driven fault-tolerant control (FTC) models. This study proposed an in situ selective incremental calibration (ISIC) strategy. Faults were introduced into the indoor air (Ttz1) thermostat and supply air temperature (Tsa) and chilled water supply air temperature (Tchws) sensors of a central air-conditioning system. The changes in the system performance after FTC were evaluated. Then, we considered the effects of the data quality, data volume, and variable number on the FTC results. For the Ttz1 thermostat and Tsa sensor, the system energy consumption was reduced by 2.98% and 3.72% with ISIC, respectively, and the predicted percentage dissatisfaction was reduced by 0.67% and 0.63%, respectively. Better FTC results were obtained using ISIC when the Ttz1 thermostat had low noise, a 7-day data volume, or sufficient variables and when the Tsa and Tchws sensors had low noise, a 14-day data volume, or limited variables.

Research on energy-saving optimization method for central air conditioning system based on multi-strategy improved sparrow search algorithm

Aiming at the problem of high energy consumption caused by the nonlinear, strong coupling, and large hysteresis characteristics of central air conditioning (CAC) system, an energy-saving optimization method based on WTD–CNN–LSTM and multi-strategy improved sparrow search algorithm (MISSA) is proposed, which works to minimize the total energy consumption during the operation of the CAC system. Firstly, minimize the sum of energy consumption of chillers, freezing pumps, cooling pumps, and cooling towers as the objective function, and use the range of operating parameters of each equipment as the basic constraint conditions to establish an energy-saving optimization model for the CAC system. Then, WTD–CNN–-LSTM is used to predict the future cooling load, and the predicted results are used as key constraint condition to achieve on-demand cooling. Finally, MISSA is proposed to improve the initialization, update and convergence stages of the CAC system operation parameter optimization process, accurately obtaining the optimal operating parameters. Compared with manual experience, MISSA reduces energy consumption by 15.32 % and improves energy efficiency ratio by 20.76 %. Meanwhile, compared with other optimization algorithms, MISSA reduces energy consumption by 4.85–13.26 % and improves energy efficiency ratio by 6.53–16.33 % after optimizing the CAC system. The experiment verifies that MISSA is more energy efficient when applied to the CAC system and has the advantages of accuracy, fast convergence, strong global search capability, and the ability to jump out of local optimization.

Radon levels and dose assessment at the basement workplaces of hospitals in different regions of Taiwan

The basements of large hospitals in Taiwan are usually working areas for image radiometry, radiation therapy, and nuclear medicine, where the radon concentration can be accumulated. This study investigated radon concentrations in the basement working environments of 30 hospitals in different regions with various geology of Taiwan, aiming to explore the relationship between geological conditions and radon concentrations and estimate the radiation dose received by the working staff. Portable MR107+ semiconductor radon detectors calibrated with a radon chamber were used for radon measurement at the hospital basement working areas according to the protocol of MAH-2019 instrument placement recommendations from the US EPA. The excess lung cancer risk (ELCR) as well as the lung cancer cases per million persons (LCC) were further derived from the radiation dose.The basement working areas investigated are located on the first to sixth underground floors of hospitals in Taiwan mainland and islands, Penghu and Kinmen. The 222Rn concentration higher than 100 Bq/m3 was observed at CH-1 (122.1 Bq/m3) in Changhua City and CY-1 (114.7 Bq/m3) in Chiayi City. This is attributed to that the central air conditioning systems of these hospitals were turned off during off-duty hours. The radon concentrations of all hospitals were lower than the action level, 150 Bq/m3, regulated by the US EPA. No significant relationship was found between radon concentration and the geological characteristics of the measured sites. That is, the ventilation of the basement working areas in hospitals is more important than local geological characteristics on indoor radon concentration, and therefore proper ventilation is crucial for reducing radon gas concentration in the hospital basements. Estimated annual effective dose from 222Rn for the hospital staff was higher than 1 mSv/y at YL (1.24 mSv/y), CH-1 (1.64 mSv/y), CY-1 (1.54 mSv/y), CY-2 (1.34 mSv/y), and PH-2 (1.14 mSv/y), and that for the rest sites was <1 mSv/y. The maximum mean ELCR was found to be 0.63% at CH-1, and the related LCC was estimated to be 29.5 per million persons.

The impact of the new EPBD “Green Houses” in the Italian building context: Technical-economic analysis on improving the energy class of existing buildings

The new European directive “Green Houses” aims at the decarbonization of the existing building stock. In this work, three building types widespread in Italy are analysed, virtually positioned in Palermo, Naples, and Milan. Considering that almost 60% of Italian residential buildings fall within the G and F energy classes, three energy retrofit measures are proposed (thermal insulation of vertical walls and roofs; replacement of the methane gas boiler for building heating and domestic hot water with a high temperature air-to-water heat pump; installation of a photovoltaic system), in order to reach at least D energy class based on Italian energy performance certification. A simulation-based approach is used. A declining tendency is noted in the normalized prices of the interventions when moving from detached house to terraced house and from terraced house to apartment in a tower building. Shifting from an independent to a centralized air conditioning system results in the same savings. Considering equal building features, hotter and milder climate zones reach higher energy classes; this also results in more difficult energy efficiency improvement in colder climates. Potential inequalities result from the implementation of the new European directive. Economic incentives to support the energy efficiency transition should be tailored to more specific conditions.

Energy saving control method for central air conditioning systems in public buildings based on improved particle swarm optimisation

Energy saving control method for central air conditioning systems in public buildings based on improved particle swarm optimisation

Energy saving and economic competitiveness of solar desiccant cooling technology – A case study of the Moroccan Kingdom

As many countries in the world, Morocco is vulnerable to climate change having direct impacts on its main economic sectors highly dependent on natural resources. This is exemplified, among other things, by long periods of drought, increase of average temperatures and successive heat waves. These circumstances have increased the demand for cooling energy, particularly in tertiary building where centralized air conditioning systems still predominant. Currently, the installed power capacity seems to be insufficient to respond effectively to this increasing demand. In this context, sustainable alternatives to traditional cooling systems such as solar air conditioning systems can be a suitable option for energy efficiency and security. Solar desiccant cooling systems present a great opportunity since they do not use any ozone-depleting coolants. This study discusses the techno-economic feasibility of solar desiccant systems in tertiary building, in particular a conference room, compared to a conventional air handling unit. Besides the use of air solar collectors to heat up the regeneration air, the particularity of the studied system is the use of exhaust air leaving the desiccant wheel and purge zone to preheat regeneration air. Accordingly, simulations were performed in three climatic regions with different enthalpy loads. The main result of this work is that solar desiccant cooling systems can be an attractive investment if appropriate economic conditions are met with a substantial governmental support, since a significant energy-saving of about 77% can be achieved compared to conventional systems.

Comprehensive and quantitative evaluation for selecting a suitable scheme of central air-conditioning during the design phase

As for routinely selecting the number and size of chillers in central air-conditioning system, the conventional scheme in which the total cooling capacity is allocated in an equal or empirical way is generally suboptimal. A few factors are brought into consideration, and the time domain of evaluation is too short. The low suitability between the cooling load of building and the scheme selected results in an inefficient state of system during the most of operation time. Some novel methods provide long-term evaluations for selecting an efficient scheme by simulating the cooling loads then calculating the cost and performance of the scheme. However, the schemes are formed without correlating actual plants which is difficult to be applied to an actual project, and the long-term environmental impact is rarely considered. The evaluation method with a high engineering value is required. But the more complicated the method is, the more work is required. The relationship between the benefits and the costs is unknown. Therefore, this study proposes three evaluation methods at different levels. From simple to complex, the three methods are corresponding the cooling load curve of building calculated through EnergyPlus to the performance curves of chillers, system simulation using TRNSYS and co-simulation based on BCVTB respectively. A case study using a hospital building located in Zhejiang province, China combined with equipment list was conducted to demonstrate the evaluation process. The results calculated by different methods and the various indexes of different schemes were compared to illustrate how to optimize the scheme selection during the design phase in order to select a suitable scheme for a certain building reducing the energy consumption and carbon emission.