Air-conditioned Buildings Research Articles

Strategy for Energy Savings in a Commercial Building Air-conditioning System with Chilled Water Storage: A Case Study in a Retail Mall in Thailand

In this study, a commercial retail mall is used as a case study to integrate a chilled water storage (CHWS) with the existing chilled water system to reduce electrical energy consumption and capitalize on the economic benefits of electrical energy saving cost and the differential between on-peak and off-peak tariffs. This study aims to improve the chiller efficiency in three operating strategies: full storage, partial storage load leveling, and partial storage demand limiting, by operating the chillers at optimal part load conditions. Technical and economic assessments were conducted to determine the necessary storage capacity and appropriate operational strategies. In comparison to the existing operation, which uses two 800 RT chillers continuously during on-peak hours and one chiller operating at 20-30% capacity during off-peak hours, the proposed systems: three 800 RT chillers with a 9,150 m³ tank for full storage, one 800 RT and one 260 RT chiller with a 3,292 m³ tank for partial load leveling, and two 800 RT chillers with a 4,987 m³ tank for partial demand limiting, demonstrate significant potential to reduce electrical energy consumption. The full storage strategy achieves the lowest electrical energy consumption, followed by partial demand limiting and partial load leveling. Economically, partial demand limiting strategy emerges as the most feasible, providing a payback period of 7.42 years and an internal rate of return (IRR) of 14.92%. This is more favorable compared to payback periods of 8.6 and 9.65 years and internal rate of return of 12.08 and 10.33% for partial load leveling and full storage strategies, respectively.

The value of air conditioning

The advent of global climate change and rising incomes, particularly in some developing countries such as Egypt, means that the use of air conditioning is poised for a dramatic increase over the next few decades. Although this anticipated increase appears inevitable, it is often associated with a negative connotation because of the increased energy demands and greenhouse gas emissions associated with expanded air conditioning use. Yet, the benefits of air conditioning are not often described in existing literature in conjunction with its associated negative externalities. For example, higher productivity in commercial buildings, and positive health benefits in all manner of buildings (residential, commercial, and industrial) could potentially offset the greater energy consumption and related disadvantages. A levelized cost of cooling (LCOC) analysis is presented to quantify under what circumstances building air conditioning provides benefits that exceed its costs, and vice versa. The LCOC is calculated for the application of air conditioning to a small office building located in either Phoenix, Arizona, United States, or in Cairo, Egypt. The electrical energy required for cooling is calculated with EnergyPlus software. The results indicate that the benefits of air conditioning far outweigh its disadvantages for the Phoenix location, largely because of the productivity benefits derived from maintaining the interior temperature at a comfortable setting. The results for Egypt are more nuanced, but still indicate the overall benefits of air conditioning in an office environment.

Assessing heat-related health perceptions in the minibus taxi industry in Tshwane, South Africa

Global warming, the increase in heatwaves and periods of intense heat, is a major problem across the world, including in South Africa. Heat exposure has adverse health impacts, ranging from dehydration and heat stroke to death. The transport sector and its users are vulnerable to heat exposure both in vehicles and in places where they wait for transport. We investigated the heat perceptions and experiences of minibus commuters and the minibus taxi industry in minibus taxis and minibus taxi ranks to inform an intervention to prevent adverse health impacts from heat exposure in the City of Tshwane. Commuters (n = 279), drivers and marshals (n = 46) reported feeling hot in minibus taxis and minibus taxi ranks, experiencing sweating, headaches, exhaustion and dizziness. Some participants reported opening windows and doors, drinking water/cold drinks, removing a jersey and fanning themselves to try and cool down. All participants suggested solutions to address heat exposure in minibus taxis and minibus taxi ranks, including more shelters and trees for shade, the provision of water, benches and potentially an air-conditioned building for waiting/holding periods between trips. In consultation with our stakeholders, we prepared educational awareness materials about heat risks to health and actions to take when it is hot, and these were distributed through the minibus taxi sector in the City of Tshwane. Future research needs include measuring temperatures in these settings and rolling out large-scale interventions to protect health and well-being in a changing climate.

Heat sink temperature modeling for reservoir source heat pumps with experimental validation

Heat-pump systems utilizing renewable resources can significantly enhance the energy efficiency of building air conditioning. This study focuses on a system that uses reservoir water as a renewable resource and develops a macroscopic numerical model to simulate heat sink temperatures, which critically influence the energy efficiency of heat pumps. Experiments were conducted to gather essential data for constructing this model. Heat was released, simulating the exhaust heat from a heat pump, from the bottom of an experimental tank filled with water. Initially, the water was thermally stratified, with the lower half at 15 °C and the upper half at 25 °C, mimicking summer conditions. The experimental results indicated that the heat release caused temperature increases exclusively in the lower layer, elevating the boundary between the layers by 0.2–0.4 m over 5 h. Consequently, we developed a heat sink temperature model by simulating the plume and entrainment of ambient water to replicate this phenomenon. The model accurately represented the increase in the boundary height across different scenarios, demonstrating a high level of agreement between the simulated heat sink temperature and the experimental values, with a deviation of <0.8 K.

Modelling and management of flexible residential building components using system based heuristic approaches

AbstractThe building energy management system (BEMS) components, that is, the heating, ventilation, and air conditioning (HVAC) systems, refrigerators, and lighting significantly impact energy consumption. This paper presents the modelling, including HVAC and refrigerator with interior heat and external illuminus of lighting for residential buildings. The energy consumption of these components has been examined using eight meta‐heuristic algorithms with weather conditions of five cities in India. The statistical and box‐plot analysis results recommended the original artificial ecosystem algorithm compared to others for energy management. The results of the proposed smart residential building have been compared with the published model results of a residential building with and without BEMS and an economic analysis has also been carried out. The simulation results show that the maximum load has been shifted to off‐peak durations. The energy savings in the proposed BEMS compared to existing BEMS and without BEMS are 34% and 57%, respectively.

Optimising thermal-daylight performance in tropical open-plan offices: A coupled OTTV and daylight prediction approach

In tropical climates, the thermal performance of air-conditioned commercial building envelopes, particularly offices, is commonly assessed using the Overall Thermal Transfer Value (OTTV). Designing office buildings in these regions requires meticulous attention to achieve the optimum thermal-daylight balance, which often has conflicting characteristics. This study aims to enhance the thermal-daylight performance optimization process for open-plan office building envelopes in tropical climates, with Kuala Lumpur as a specific case study. The methodology involves parametric thermal and daylight simulations, incorporating an extensive global sensitivity analysis (GSA) based on the Monte Carlo method. Next, the most critical design parameters affecting daylight provision are identified and used to develop a prediction formula for daylight provision assessment. Finally, the exploration further examines the impact of dominant parameters on energy consumption across diverse urban densities. The results pinpointed the Shading Coefficient (SC1) and Window-to-Wall Ratio (WWR) as pivotal factors affecting heat gain. At the same time, obstruction angle (Theta), WWR, and Visible Transmittance (Tvis) significantly influence daylight provision. Furthermore, the developed daylight prediction formula consists of a fast method that can be coupled with OTTV to evaluate and optimise the thermal-daylight performance in the early design stage of office buildings. Moreover, the study reveals potential energy savings of up to 8 %, 4.83 %, and 4 % in very low, medium, and very high urban densities, respectively. These insights and the daylight prediction formula provide valuable tools for optimising building envelope thermal-daylight performance during the early stages of architectural design, offering practical guidance for both practitioners and researchers.

Development of Innovative Thermoplastic Foam Materials Using Two Additive Manufacturing Technologies for Application in Evaporative Cooling Systems.

Evaporative cooling systems have emerged as low-energy consumption alternatives to traditional vapor compression systems for building air conditioning. This study explored the feasibility of utilizing polymeric foamed materials produced through additive manufacturing as wetting materials in evaporative cooling systems. Specifically, two different commercial polylactic acid filaments, each containing a percentage of a chemical blowing agent, were studied. Experiments were designed to evaluate the influence of critical process parameters (line width, flow rate, speed, and layer height) on the performance of the resulting foamed materials in terms of evaporative cooling by conducting water absorption, capillarity, porosity, and wettability tests. Considering that high water absorption, capillarity, and porosity, coupled with an intermediate contact angle, are advantageous for evaporative cooling effectiveness, a low flow rate was found to be the most important parameter to improve these properties' values. The results showed that the appropriate combination of polymer and process parameters allowed the production of foamed polymer-based materials processed by additive manufacturing technology with optimal performance.

ABSORPTION REFRIGERATION SYSTEMS FOR WASTE HEAT RECOVERY AT THE SILICATE INDUSTRY

The glass, ceramic and cement plants are energy intensive industrial systems, releasing high amounts of greenhouse gases. The dissipation of the waste heat reduces their profitability, energy and ecological efficiency. The absorption refrigeration systems are successful solutions for the recovery of thermal energy at different temperature levels to obtain useful cooling and heating powers for technological needs, and for air conditioning of administrative and industrial buildings. Although the absorption units in a heat pump and refrigeration cycle are currently used in building and industrial systems, they have not yet penetrated widely into the silicate factories. This paper discusses possibilities for the applications of basic types of absorption cycles at heat pump and refrigeration modes to utilize waste energy at different temperature levels in glass, ceramic and cement plants. The examined variants are demonstrated via examples, diagrams and analyses of the possible energy saving.

Prediction of building HVAC energy consumption based on least squares support vector machines

Air conditioning, as an essential appliance in daily life, has the function of ensuring comfortable room temperature, but it is also accompanied by a large amount of power consumption. Consequently, the study suggests an energy consumption prediction model based on improved genetic algorithm—least squares support vector machine—to accurately predict the energy consumption of building heating, ventilation, and air conditioning. This model uses the improved genetic algorithm for regularization parameter and kernel parameter optimization to prevent overfitting and underfitting issues. According to the testing results, the least squares support vector machine, an upgraded genetic algorithm, may accomplish convergence faster than other algorithms, taking only 0.2 milliseconds to finish. In addition, the average relative error of the improved genetic algorithm- least squares support vector machine did not exceed 0.6%. In the energy consumption prediction for the whole year of 2022, the average error of the improved genetic algorithm-least squares support vector machine was only 2.0 × 106 kWh, and the prediction accuracy could reach up to 97.2%. The above outcomes revealed that the energy consumption prediction model can accurately predict the air conditioning energy consumption, which provides a strong support for the control and optimization of the air conditioning system.

Co-existence of airborne SARS-CoV-2 infection and non-infection in three connected zones of a restaurant

The lack of knowledge on quanta generation rates presents a major obstacle to specifying the minimum ventilation required to prevent airborne infections. The expected largest quanta generation rate of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by a super-spreader remains unknown. Here we investigated a SARS-CoV-2 outbreak during lunch in a restaurant using epidemiological, whole-genome sequencing and environmental analyses. Both tracer gas and fine particles were used in field experiments to quantify aerosol dispersion and removal across three interconnected zones: Zone A, Zone B and Zone C. All 21 secondary patron infections occurred in Zone B. This unique infection feature and measured dilution flow rates allowed us to estimate the largest reported quanta generation rates to date, ranging from 1724 to 1968 quanta/h. These rates were sufficiently high to cause a high attack rate in Zone B but did not cause infections in Zones A and C, likely due to sufficient dilution and insignificant contaminated airflow from Zone B, respectively. Our finding of the largest quanta generation rate so far suggests that avoiding secondary infection by dilution alone in the presence of a super-emitter might not be possible in typical air-conditioned buildings and other prevention strategies need to be developed.

Transient investigation of a residential building air conditioning system with heat pump and PV/T modules

Abstract Nowadays, in response to the European energy crisis and the imperative to reduce carbon emissions, the study of energy systems plays a crucial role. New energy systems and configurations have been studied in the recent years to improve the energy efficiency and reduce greenhouse gases emissions. This study investigates the dynamic performance of a residential HVAC system integrating photovoltaic thermal (PV/T) modules and a heat pump. The system aims to harness thermal energy from solar radiation using PV/T modules to generate electricity and heat water. The case study is performed considering a building located in Caserta. According to the authors knowledge, there is a lack of information regarding the modeling of PV/T systems with a heat pump. Inside the studied system, the thermal energy is stored in a storage tank for later use. An auxiliary heater is activated to produce domestic hot water (DHW) when the PV/T cannot provide it. The system components are modeled using TRNSYS. A dynamic simulation approach is adopted to assess the system performance under varying environmental conditions and building load demands. These load demands are used to model real-world scenarios. This kind of system offers several advantages. Firstly, the PV/T modules serve a dual purpose of electricity generation and water heating, maximizing energy utilization. Secondly, the heat pump enhances the overall efficiency of the system by extracting heat from the water stored in the puffer tank, thereby reducing reliance on conventional heating methods. The findings of this study provide valuable insights into the performance and feasibility of integrating PV/T in residential HVAC systems. During the winter season, the solar fraction, the ratio between energy supply from PV/T and total energy demand, averages about 25%. When heating is not required, the PV/T panels manage to ensure the production of approximately 75% of DHW.

A Comparative Study of Building Energy Consumption Prediction Methods

Continued usage of fossil fuel-based electricity generation is one of the main factors for the greenhouse effect. As the greenhouse effect increase, the ambient temperature of the earth will also increase. As the temperature increase, the usage of air conditioning in buildings is also expected to increase. Since that more than 50 % of building energy consumption goes to air conditioning, it is utterly important to look into the methods that can be used to predict the impact of variations in temperature towards building energy consumption. This paper hence tries to perform a conceptual review on the prevalent methods that have been used for prediction of energy consumption, grouped in the category known as the white box, grey box and black box. The comparison of the different methods used in forecasting of energy consumption is discussed in terms of application, input, specific approach, advantage and disadvantage. It is hoped that the work carried out in this paper will be the reference to jump start the research work of others in this field of study.

Calibration of a hybrid model for HVAC systems for fault data generation

The application of automated fault detection and diagnosis algorithms has proven to be an effective way to increase the energy efficiency of buildings. While data-driven strategies have demonstrated their potential in developing such algorithms, they require a set of historical data that represents both healthy and faulty equipment operation, which is not a common scenario in real facilities. This article presents a methodology for the generation of synthetic data on both healthy and faulty operation for building heating and air conditioning equipment, which is especially useful for supervision and failure detection in the case of replication and expansion of buildings in tertiary or residential building planning programmes. This work investigates the automatic calibration of a typical air-handling unit hybrid model, composed of the detailed parametric representation of the system components and its control sequence coupled with a simplified thermal load. The model is then extended with fault models that resemble commonly encountered component faults to generate operation data in faulty scenarios. The proposed framework is validated in a real use case with the calibration of an air-handling unit system and its control sequence using 15 days of data gathered from the building management system. The results obtained from the injection of seven typical faults are then compared with the fault-free simulations to highlight and validate their impact on key operating variables. The results prove the capabilities of this methodology to support database generation in the fields of fault detection and advanced maintenance of buildings’ air conditioning systems for building replicas.

PMVd/PPDd model for predicting thermal comfort in air-conditioned buildings in hot and humid regions of Sub-Saharan Africa

The model for predicting thermal comfort conditions established by Fanger remains widely used in scientific work, as a default means of in situ measurements. However, the use of Fanger data leads to dissatisfaction among users of air-conditioned buildings in humid tropical areas. This conclusion emerges from the work of Kemajou and al. (Cameroon) and Olissan and al. (Benin) in 2012, after survey studies on the judgments of thermal sensations of people occupying various air-conditioned spaces. This article develops a correction model for the Fanger model, by coupling the latter to models for predicting skin temperature and heat loss by evaporation of sweat through the skin, as well as to the skin thermal sensitivity of people active in a humid tropical climate. The model thus determined shows that the predicted optimal comfort temperatures are located in the range of 26.1 °C to 27.5 °C and better meets the expectations of the populations in this region. The respective differences with the investigations of Kemajou and al. and those of Olissan and al. are 0.40 °C and 0.55 °C. It also appears that the comfort humidity range is 30% to 80%, apart from any other safety measures.

A joint optimization strategy for electric vehicles and air conditioning systems with building battery configuration

Building air conditioning systems, electric vehicles and battery energy storage systems all provide substantial flexibility for grid operations. However, the joint optimization strategy involving these three demand response resources in buildings has been infrequently studied. This research proposes a day-ahead optimization strategy to coordinate the joint operation of air conditioning systems and electric vehicles. In this framework, cooling load is predicted using an autoregressive exogenous model, while electric vehicle charging load is predicted through Monte Carlo simulations. An evaluation method is introduced to assess the comprehensive benefits of the demand response strategy, considering thermal comfort, economic efficiency, and grid friendliness. Using an office building in Tianjin, China, as a case study, the results indicate that the joint optimization strategy reduces operational costs by 3.71 % and peak electricity load by 38.62 % compared to the original strategy. Furthermore, it enhances the grid friendliness of the energy system by 42.64 %. The configuration of the battery energy storage system is also explored in conjunction with the optimization strategy to further improve grid friendliness. The impact of economic factors and thermal comfort on the configuration of the battery energy storage system is discussed. In the case study, raising the upper temperature limit by 1 °C can save at least 17.1 % in capacity, while battery energy storage system investment and operational costs can respectively be reduced by 55.04 % and 27.14 % within the thermal comfort range.

Development of an FDD model for an existing building using transfer learning

Building heating, ventilation, and air conditioning (HVAC) systems are affected by several errors that can cause thermal discomfort to occupants and waste energy in buildings. Therefore, early and accurate Fault Detection and Diagnosis (FDD) is vital for enhancing the system’s efficiency. Data-driven FDD is promising because it is convenient compared to the first-principles-based rule set that demands in-depth expertise. However, to realize data-driven FDD for real-life cases, the data-imbalance problem in FDD must be solved. In this study, the authors suggest a novel approach that generates synthetic data from a building system simulation tool, HVACsim+, using them as a source model to apply transfer learning to a target air handling unit system. Even though from the existing target system only the normal operational data were available, the transfer learning approach was satisfactory, confirming that the proposed method effectively mitigates data imbalance in developing data-driven FDD.

The Cost-Optimal Control of Building Air Conditioner Loads Based on Machine Learning: A Case Study of an Office Building in Nanjing

Building envelopes and indoor environments exhibit thermal inertia, forming a virtual energy storage system in conjunction with the building air conditioner (AC) system. This system represents a current demand response resource for building electricity use. Thus, this study centers on the CatBoost algorithm within machine learning (ML) technology, utilizing the LASSO regression model for feature selection and applying the Optuna framework for hyperparameter optimization (HPO) to develop a cost-optimal control method for minimizing building AC loads. This method addresses the challenges associated with traditional load forecasting and control methods, which are often impacted by environmental temperature, building parameters, and user behavior uncertainties. These methods struggle to accurately capture the complex dynamics and nonlinear relationships of AC operations, making it difficult to devise AC operation and virtual energy storage scheduling strategies effectively. The proposed method was applied and validated using a case study of an office building in Nanjing, China. The prediction results showed coefficient of variation in root mean square error (CV-RMSE) values of 6.4% and 2.2%. Compared with the original operating conditions, the indoor temperature remained within a comfortable range, the AC load was reduced by 5.25%, and the operating energy costs were reduced by 24.94%. These results demonstrate that the proposed method offers improved computational efficiency, enhanced model performance, and economic benefits.

Innovative silica aerogel fiberglass walls and roofs: A path to lower carbon emissions and higher energy savings

ABSTRACT Buildings account for a significant portion of global energy use and consumption. Buildings have substantial energy consumption due to the use of heating, ventilation, and cooling systems. It is evident that the insulation materials used in the design of building envelopes can efficiently reduce the cost of air conditioning by reducing external heat gains and losses. Additionally, the use of environmentally friendly and cost-effective can be beneficial from an environmental standpoint. This paper aims to evaluate the potential for cost savings in the air conditioning of buildings incorporated with silica aerogel fiberglass insulation in hollow concrete bricks (wall) and hollow roof tile (roof). Silica aerogel fiberglass insulation is extensively used for heat insulation purposes, including building insulations, due to its superior thermal insulation and flame retardant properties. The thermo-physical properties of silica fiberglass insulation and building materials were determined experimentally as per ASTM D 5334 standards. Twenty distinct building design concepts are investigated in this study, each featuring insulation-integrated concrete blocks composed of silica aerogel fiberglass: (WEM1) insulation layer in the outer side, (WEM2) insulation layer in the center, (WEM3) insulation layer in the inner side, (WEM4) insulation layers in the outer-middle, (WEM5) insulation layers in the middle-inner, and (WEM6) insulation layers in the outer-inner sides. Additionally, two arrangements of insulation-stuffed roof tiles, REM1 above the RCC and REM2 below the RCC. In addition, novel building designs integrated with insulation were analyzed numerically, related to environmental conditions that refer to two different scenarios in India (hot dry and composite climates). Thermo-economic analysis of novel wall and roof designs with silica fiberglass insulation materials on air-conditioning costs, carbon dioxide emissions, and payback time are compared with conventional roof and wall patterns. The thermo-economic analysis was carried out based on the number of degree-hours of heating and cooling to determine the building’s annual energy usage. The building model arrangement (WEM6-REM1), which consists of an insulation composite wall (WEM6) and insulation roof tile (REM1), demonstrated the greatest annual air conditioning cost savings of 3.4 $/m2/year and 1.74 $/m2/year when compared to conventional building design for climatic conditions of Kurnool and Gauhati. The building model arrangement (WEM6-REM1) composed of silica fiberglass aerogel insulation exhibits the highest reduction in carbon emissions of 65 kg/kWh and 33 kg/kWh, when compared to conventional building design analyzed in both hot-arid; (Kurnool) and composite (Gauhati) climatic conditions. The placement of insulation in the roof alone (REM1) has the shortest payback duration of 2.15 years. The results of this study point to a viable approach to enhancing building design decision-making and narrowing the performance gap in sustainable and energy-efficient strategies.

Experimental study on the performance of the vertical shell-tube indirect evaporative cooler with inner grooved tubes

The vertical tube indirect evaporative cooler (VTIEC) could be preferred one to air-conditioning buildings if its water film quality could be improved. This paper proposed a new VTIEC with inner grooved tubes to improve the water film quality and obtained its performance by experimental method. The results indicated that inner grooved tubes have positive effects on the water film and performance of the new VTIEC. A low working air enthalpy at inlet can significantly improve the total cooling capacity from evaporation, and then VTIEC performance. In this paper conditions, the velocity ratio of 1.52 of the produced air to the working air is better one condition compared to 1.01 and 2.28. The produced air velocity is positive effect on the cooling capacity per unit area until the produced air velocity of about 4.05 m/s and is negative effect on COP. The maximum unit cooling capacity, wet-bulb efficiency and COP are 307.74W/m2, 81.7% and 44.97.The results will promote the application of the new VTIEC.

Coordination Compound Guided a Novel Composite Film with Zn2V2O7 Nanoflake and VO2@Zn2V2O7 Nanoparticle for Enhanced Thermochromism Smart Window.

Thermochromic vanadium dioxide (VO2) can intelligently modulate the transmittance of indoor solar radiation to reduce the energy consumption of air conditioning in buildings. Nevertheless, it remains a great challenge to simultaneously improve the luminous transmittance (Tlum) and solar modulation ability (ΔTsol) of VO2. In this study, a novel approach is employed utilizing a coordination compound to finely tune the growth of a VO2 based composite film, yielding a hierarchical film comprising Zn2V2O7 nanoflakes and VO2@Zn2V2O7 core-shell nanoparticles. Remarkably, the resulting composite films showcase exceptional optical performance, achieving a Tlum of up to 73.0% and ΔTsol of 15.7%. These outcomes are attributed to the antireflection properties inherent in the nanoflake structure and the localized surface plasmon resonance of well-dispersed VO2 nanoparticles. In addition, the Zn2V2O7-VO2 film demonstrates remarkable environmental durability, retaining 90% of its initial ΔTsol even after undergoing aging at 100°C under 50% relative humidity for a substantial period of 30 days - a durability equivalent to ≈20 years under ambient conditions. This work not only achieves a harmonious balance between Tlum and ΔTsol but also introduces a promising avenue for the design of distinctive composite nanostructures.