Air-conditioned Buildings Research Articles

Building heating load forecasting based on the theory of transient heat transfer and deep learning

Reliable and accurate heating load forecasting can provide comprehensive information for the monitoring and control of Heating, Ventilation, and Air Conditioning (HVAC) in buildings, which reduce uncertainty on the load demand of energy effectively. Data-driven method has demonstrated a potential to forecast heating load, but current methods generally lack the consideration of features on model forecasting performance and applicability. Based on the theory of transient heat transfer and conduction transfer function for building hourly heating load calculation, this study proposes an idea that comprehensively selects physical variables affecting the hourly dynamic changes of the building heating load as features, which enhances the persuasiveness of selecting datasets features. Then we use the deep learning method to build short-term heating load forecasting models, and explore the influence of different feature combinations and time steps on the model forecasting performance. Combining the physical property of building heat gains, we divide the features into external heat gains, internal heat gains and historical heating load and then show their performance of models at different time steps. It is shown that the two-hour data of external heat gains and internal heat gains, the three-hour data of past heat load have the highest value. The best model can achieve a mean absolute error of 0.153 kW and a mean absolute percentage error of 6.2 %. These findings are helpful for researchers to select more relevant features to forecast heating load in buildings and improve their models through physical aspect.

Evaluation of Energy Density in Hexadecane Phase Change Emulsions in Comparison to Water

The development of energy-dense, thermomechanically stable, and low-viscous phase change emulsions (PCMEs) is proposed as an alternative thermal energy storage solution for building air conditioning. A set of oil-in-water (O/W) nanoemulsions with hexadecane concentration varied between 10, 20, 25, 30, 35, and 40 wt. % is prepared and characterized with respect to their physical, thermal, and rheological properties. The storage characteristics are evaluated in terms of storage density, phase transition behaviour, supercooling, and dynamic viscosity. A systematic comparison in terms of energy density between the PCMEs and water is carried out at different temperature conditions. For this purpose, the storage break-even temperature TBE is proposed as a novel parameter to determine suitable operating temperature ranges and cycling conditions. The cycle stability is evaluated by rheological measurements, applying thermomechanical loads to the samples for a high number of cycles. According to the results, the energy density of the PCMEs is always higher than that of water, when the minimum temperature used for the cycling is below the storage break-even temperature. The emulsion with 30 wt. % hexadecane fraction is considered particularly promising, thanks to its high stability when exposed to thermomechanical stress, relatively low viscosity between 10 and 22 mPa s (0–30°C), and a storage density of 98 MJ/m3 within a cycling temperature range of 12 K.

Unveiling overlooked aspects of model predictive control for building air conditioning systems

The ongoing research on model predictive control (MPC) for building air conditioning systems predominantly centers on improving the predictive capabilities of system models. In this paper, the impacts of three additional pivotal factors on MPC performance are assessed by examining a generic MPC design for a typical variable air volume (VAV) system that serves large commercial buildings. The three factors encompass the nuanced reformulation of optimization, the judicious relaxation of constraints, and the meticulous tuning of parameters. Detailed case studies with an integrated Modelica and EnergyPlus model of the US Department of Energy's Commercial Reference Building are conducted. The results confirm that the optimization formulation, along with relaxation methods, significantly affects MPC performance in terms of energy savings, zonal thermal comfort level, and computational demand. They also reveal that the impact of the MPC control parameters on the energy savings and thermal comfort may vary by season and can be non-monotonic.

Deterministic and probabilistic occupant-centric control's impacts on the indoor environment in free-running households

PurposeOccupant behavior can lead to considerable uncertainties in thermal comfort and air quality within buildings. To tackle this challenge, the use of probabilistic controls to simulate occupant behavior has emerged as a potential solution. This study seeks to analyze the performance of free-running households by examining adaptive thermal comfort and CO2 concentration, both crucial variables in indoor air quality. The investigation of indoor environment dynamics caused by the occupants' behavior, especially after the COVID-19 pandemic, became increasingly important. Specifically, it investigates 13 distinct window and shading control strategies in courtyard houses to identify the factors that prompt occupants to interact with shading and windows and determine which control approach effectively minimizes the performance gap.Design/methodology/approachThis paper compares commonly used deterministic and probabilistic control functions and their effects on occupant comfort and indoor air quality in four zones surrounding a courtyard. The zones are differentiated by windows facing the courtyard. The study utilizes the energy management system (EMS) functionality of EnergyPlus within an algorithmic interface called Ladybug Tools. By modifying geometrical dimensions, orientation, window-to-wall ratio (WWR) and window operable fraction, a total of 465 cases are analyzed to identify effective control scenarios. According to the literature, these factors were selected because of their potential significant impact on occupants’ thermal comfort and indoor air quality, in addition to the natural ventilation flow rate. Additionally, the Random Forest algorithm is employed to estimate the individual impact of each control scenario on indoor thermal comfort and air quality metrics, including operative temperature and CO2 concentration.FindingsThe findings of the study confirmed that both deterministic and probabilistic window control algorithms were effective in reducing thermal discomfort hours, with reductions of 56.7 and 41.1%, respectively. Deterministic shading controls resulted in a reduction of 18.5%. Implementing the window control strategies led to a significant decrease of 87.8% in indoor CO2 concentration. The sensitivity analysis revealed that outdoor temperature exhibited the strongest positive correlation with indoor operative temperature while showing a negative correlation with indoor CO2 concentration. Furthermore, zone orientation and length were identified as the most influential design variables in achieving the desired performance outcomes.Research limitations/implicationsIt’s important to acknowledge the limitations of this study. Firstly, the potential impact of air circulation through the central zone was not considered. Secondly, the investigated control scenarios may have different impacts on air-conditioned buildings, especially when considering energy consumption. Thirdly, the study heavily relied on simulation tools and algorithms, which may limit its real-world applicability. The accuracy of the simulations depends on the quality of the input data and the assumptions made in the models. Fourthly, the case study is hypothetical in nature to be able to compare different control scenarios and their implications. Lastly, the comparative analysis was limited to a specific climate, which may restrict the generalizability of the findings in different climates.Originality/valueOccupant behavior represents a significant source of uncertainty, particularly during the early stages of design. This study aims to offer a comparative analysis of various deterministic and probabilistic control scenarios that are based on occupant behavior. The study evaluates the effectiveness and validity of these proposed control scenarios, providing valuable insights for design decision-making.

Development of adaptive behaviour models for thermal comfort: Longitudinal investigation in Japanese office buildings and literature review

In the recent year's energy consumptions has increased, especially in the office buildings for heating and cooling use. Adaptive behaviours such as clothing adjustments, window opening, fan use, heating use and cooling use are important contributing factors for thermal comfort of the occupants. The main objectives of this study is to clarify different behavioural adaptations carried out by occupants in Japanese office buildings and to compare with previous studies. The occupant behaviour models were developed for clothing adjustments and air-conditioning use. Occupant behaviour survey was conducted in the five mixed mode (MM) and one heating, ventilation, and air-conditioning (HVAC) Japanese office buildings over a period of fifteen months resulting in 16,411 votes from 45 participants. Range of clothing insulation was wider in MM buildings compared to HVAC buildings which indicate that occupant behaviour in MM buildings required less energy for thermal comfort. The mean proportion of window opening and fan use was 0.54 and 0.41 respectively. Developed logistic model suggested that 80% of occupant used heating and cooling when the outdoor air temperature drops below 11 °C and rise above 27 °C respectively. The obtained results from field investigation are validated by the extensive literature review. The occupant behaviour models in Japanese office buildings are comparable with the behaviours models from different parts of the world having various climatic conditions. It was also confirmed that occupants behaviours are effective for energy saving building designs. The acknowledgement of these behaviour of the occupants is fruitful in designing thermally comfortable and possibly energy saving MM buildings in future.

Energy efficiency of life support systems of buildings in «green construction»

Purpose: develop an integrated air conditioning system with the environment, which will allow to reduce energy consumption due to lowering the temperature of air taken from outside from natural or artificial green areas. Methods: the basis of the solution to the task of developing an integrated system was the use of three well-known methods of greening of home territories: traditional, non-traditional and container. Because green spaces, in the warm period of the year, allow you to naturally reduce the parameters of the outside air, which are used for the needs of the building's ventilation and air conditioning systems. Findings: due to the complex use of all types of landscaping, it is possible to reduce the energy consumption for work of ventilation and air conditioning systems by reducing the temperature of air taken from the outside from natural or artificial green areas. Due to this, when developing integrated air conditioning systems, we can achieve: a decrease in the temperature of the supply air from the landscaping area, which will reduce not only the energy costs for cooling and humidification, but also the reduction of pollution of the supply air; when using trees and shrubs of certain breeds, which emit phytoncides and other beneficial secretions, in the outdoor air intake area, it will improve the quality of incoming air. Practical implication: the developed integrated air conditioning system with the environment will allow to reduce the influence of the outside air temperature on the indoor air temperature due to the integrated use of all types of greening. Originality: a review of literary sources showed that today the possibility of taking outside air from existing or artificially created green areas is not used in the design of ventilation and air conditioning systems.

An Analysis of Energy Consumption In The Goverment Buildings’ In Indonesian Border

In this research, energy consumption analysis was conducted at the Main building regent’s office of nunukan. The analysis was conducted on the main variables of energy efficiency, namely: measurement of temperature and relative humidity, calculation of Overall Thermal Transfer Value (OTTV) and Roof Thermal Transfer Value (RTTV), calculation of Energy Consumption Intensity (IKE) in air-conditioned and non-air-conditioned rooms as well as an analysis of opportunities to increase the efficiency of energy consumption in the buildings.. Based on the calculation and result of IKE in both buildings, they are still considered in the category of EFFICIENT. However, based on the measurement of temperature and relative humidity, it shows that in both buildings air conditioning is still necessary to achieve the level of thermal comfort, therefore an increase of efficiency in the load is needed to avoid wastage.

Information entropy analysis of the relation between climate and thermal adaptation: A case study in hot summer and cold winter region of China

The shift of paradigm from reductionist to holism in the field of thermal adaptation promoted a boom in thermal adaptation theory and provided a systemic perspective on this issue. The thermal adaptation theory confronts twin difficulties of scale and complexity. The complexity and entropy of occupants' thermal adaptation emerging. This paper aims to investigate the information entropy exchange in the coupled climate-building-occupants system. First, we justified that the building-occupants system is an open system and exchanges energy, matter, and entropy with its surrounding climate system. Then, correlation analysis results suggested that climate entropy could influence thermal adaptation entropy. Thermal adaptation entropy fluctuated with climate entropy and the difference varied between −0.5 and 0.5 below 31 °C. A generalized entropy balance model was proposed for quantifying the entropy exchange among coupled climate-building-occupants systems for both free-running and air-conditioning buildings. The quantitative relation between the entropy of thermal adaptation and H_DTR reveals the dynamic occupant's thermal adaptation under the process of entropy exchange with the climate system. The H_DTR and entropy relation models provide a new perspective on thermal adaptation coupled with climate beyond outdoor daily mean temperatures. Control strategies that integrate the dynamic characteristics of DTR can bring more economical, energy-efficient and comfortable effects to the operation of air conditioning or heating systems. Our findings shed some light on the dynamical and complex thermal adaptation. In further studies, more results and methods from meteorological research could be used for thermal adaptation research and interdisciplinary theories could be adopted to help us better understand occupants' thermal adaptation.

Fault detection and diagnosis of electric bus air conditioning systems incorporating domain knowledge and probabilistic artificial intelligence

The air conditioning systems in electric city buses usually operate in rapidly changing ambient conditions and are more likely to suffer from mechanical faults. Although many fault detection and diagnosis (FDD) methods have been developed for building air conditioning systems, they are difficult to be applied to bus air conditioners since its operation is highly dynamic and fault-free data are usually unavailable. Therefore, this paper proposes an FDD method for electric bus air conditioners to tackle the above issues. First, the method identifies faults in an unsupervised manner by comparing selected features among a group of peer systems. Then, considering the features are influenced by the operating conditions, Gaussian process regression (GPR) models are established to find the relationships between each feature and its influential parameters. The probabilistic nature of the GPR is used to differentiate predictions with large uncertainty, which are then excluded from FDD. In this way, robustness of the method is evidently improved. Finally, fault indexes are defined to detect and diagnose mechanical faults. We applied the method to a group of air conditioners in a city bus fleet. Results showed that it can effectively identify refrigerant undercharge and indoor and outdoor fan problems with low false positive/genitive rates. Also, the method is highly robust and not sensitive to the faulty systems in the bus fleet.

Development of a rapid assessment tool for integrating thermal comfort in early design stage of energy-efficient office buildings

Comprehending and predicting energy performance of existing buildings and new constructions is crucial towards decarbonization. Instead of utilizing simulation software, multiple regression models are utilized to predict building energy consumption while ensuring indoor thermal comfort to speed up this process. However, previous predictive models prioritize reducing energy demand, with limited focus on thermal comfort. This study aims to support decision-making during retrofitting and new construction planning though developing a prediction model. An air-conditioned office building served as a reference building for simulation. 21 design parameters were analyzed, including aspects of weather, building envelope, internal loads, ventilation, and temperature settings. Stepwise regression results unveiled the crucial variables in the final model, with 8, 9, 13, and 6 variables remaining for peak cooling load, annual cooling load, overheating hours (WE), and Environmental Quality Index for thermal comfort (EQITC) in the perimeter zones, and 5, 6, 8, and 5 variables for the core zones, respectively. Furthermore, insights into the important variables regarding cooling load and thermal comfort were respectively provided. Weather- and envelope-related variables, such as cooling degree-days, global solar radiation, solar heat gain coefficient (SHGC), and U-value, have the highest impacts on cooling load. For thermal comfort, variables including temperature setpoint, occupant activity level, and factors related to window sunlight transmission performance, such as SHGC, window area ratio, and overhang projection ratio, proved to be influential. Overall, this study provided accurate models for assessing optimal strategies for energy efficiency and thermal comfort during the early design phases, advancing building performance practices.

Control Strategy for Building Air Conditioning Cluster Loads Participating in Demand Response Based on Cyber-Physical System

In recent years, with rising urbanization and ongoing adjustments in industrial structures, there has been a growing dependence on public buildings. The load of public buildings gradually becomes the main component of the peak load in summer, among which the load of air conditioning is particularly prominent. To clarify the key problems and solutions to these challenges, this study proposes a multi-objective optimization control strategy for building air conditioning cluster participation in demand response based on Cyber-Physical System (CPS) architecture. In a three-layer typical CPS architecture, the unit level of the CPS achieves dynamic information perception of air conditioning clusters through smart energy terminals. An air conditioning load model based on the multiple parameter types of air conditioning compressors is presented. Then, the system level of the CPS fuses multiple pieces of information through smart energy gateways, analyzing the potential for air conditioning clusters when they participate in demand response. The system of system level (SoS level) of the CPS deploys a multi-objective optimization control strategy which includes the uncertainty of the initial states of air conditioning clusters within the intelligent building energy management system. The optimal model takes into account the differences in the environmental conditions of each individual air conditioning unit within the cluster and sets different operating modes for each unit to achieve load reduction while maintaining temperatures within a comfortable range for the human body. The Multi-Objective Particle Swarm Optimization (MOPSO) algorithm based on Pareto frontiers is applied to solve this optimization control strategy and to optimize the operational parameters of the air conditioning clusters. A comparative analysis is conducted with single-objective optimization results obtained using the traditional Particle Swarm Optimization (PSO) algorithm. The case study results indicate that the proposed multi-objective optimization control strategy can effectively improve the thermal comfort of the human body towards the controlled temperatures of air conditioning clusters while meeting the accuracy of demand response. In the solution phase, the highest temperature within the air conditioning clusters is 24 °C and the lowest temperature is 23 °C. Adopting the proposed multi-objective optimization control strategy, the highest temperature is 26 °C and the lowest temperature is 23.5 °C within the clusters and the accuracy of demand response is up to 92%. Compared to the traditional PSO algorithm, the MOPSO algorithm has advantages in convergence and optimization precision for solving the proposed multi-objective optimization control strategy.

Optimization of the Air-Conditioning Energy Performance and Daylight Performance of AResidential Building According to the Bioclimatic Design Principles: An Application to the Moroccan Mediterranean

The bioclimatic architecture concept refers to an approach that takes into account the various characteristics of a building environment to make it more comfortable for its occupants. This work aims to improve the passive design parameters of an air-conditioned residential building located in the north of Morocco, in accordance with bioclimatic principles. The bioclimatic chart diagram is used to select the passive design measures that are the most appropriate for the north Morocco climate characteristics. Then, a set of design parameters are selected for more delimitation in the optimization study. The optimization problem is multi-objective and aims to find the design solution that simultaneously includes the best air-conditioning energy performance and daylight performance. The obtained results showed that the multi-objective optimum design solution is characterized by massive walls and roof, exterior insulation, double window glazing type, and a high summer ventilation rate. Also, a small glazing area with a large sun-shading covering is needed for the east facade. Ultimately, the building performance analysis revealed that the optimum bioclimatic design solution fully meets the requirements establishedby the Moroccan Building Thermal Regulation (MBTR), leading to an energy performance improvement of about 52%.

Investigation on the thermal-fluidic characteristics of ice slurry in sinusoidal corrugated plate heat exchangers

The sinusoidal plate heat exchangers (SCPHEs) using ice slurry as coolant have a critical role for building air conditioning. However, the thermal-hydraulic properties of ice slurry in SCPHEs are still unclear. Therefore, its flow and heat transfer performances in SCPHEs are studied using Euler-Euler model in this paper. The results show that with increasing corrugation pitch (P), the velocity of the mainstream direction and the flow dead zone decrease. As enlarging the corrugation amplitude (H), the low-velocity flow zone and flow dead zone increase. The average resistance coefficient (fave) of ice slurry reduces with increasing P and volume flow rate. When volume flow rate is between 0.144 m3/h and 1.44 m3/h, fave decreases more significantly than other stages. In addition, fave increases with increasing H and ice concentration (αin). The mass transfer of ice particles is increased at higher H and smaller P. The average Nusselt number (Nuave) of ice slurry, heat transfer rate (Qw) and total heat transfer coefficient (U) of SCPHEs increase as enlarging H, αin and volume flow rate, and decrease with increasing P. While the U and Qw are less affected by ice particle concentration. In addition, the empirical correlations of fave and Nuave in SCPHEs are developed.

Impact of modules number of thermoelectric cooler coupled with PV panels and phase change material on building air conditioning

This paper integrates a photovoltaic panel, phase change material, and thermo-electric cooling system into the room wall for air conditioning to replace conventional air conditioning with a new environmentally friendly system. This technique uses a photovoltaic panel on the wall's exterior to power the thermo-electric system in the wall's interior surface. Two phase change materials layers are installed inside the wall to extract the heat dissipation from the PV panel and the thermo-electric cooling system. A complete transient mathematical model for a room is constructed and solved numerically. The cooling system is studied in five wall positions: east, west, south, north, and the room's roof. The effect of each cooling system position on the room temperature, cooling capacity, and its coefficient of performance is investigated. The highest PV output power in the roof system is 857 W, while this number is 819 and 510 W for the east and west walls, respectively. The results show that the best cooling system performance is achieved at a specific number of thermoelectric elements, which is different for each wall position. It is 300 for the east and roof systems and 500 for the west and south systems. At this optimum number, the minimum room temperature reaches 19.4, 26.7, 26.6, and 20.4 °C for the east, west, south, and roof system, respectively. While, the maximum cooling capacity is about 1734, 2157and 1662 W for the east, west and roof systems, respectively. The lowest coefficient of performance value is 2, 4.35, and 1.9 for the east, west, and roof systems, respectively, making the new solar-powered system competitive with the conventional one.

Study of melting behavior of phase change material in a square enclosure with constant and variable heat flux at different wall heating conditions: A numerical approach

Latent heat thermal energy storage system offers the most promising cost-effective solution in thermal energy storage applications like solar water heaters to building air conditioning, textile industries, pharmaceutical industries, etc. In this article, the melting process of phase change material (PCM) in a square enclosure with constant, linearly increasing, linearly decreasing and sinusoidal heat flux on different sides of the wall is studied. The result shows that double-wall heating has the highest melting rate followed by side-wall heating and bottom-wall heating. This happens because double-wall heating increases the heat transfer area. Between side-wall heating and bottom-wall heating with uniform heat flux, side-wall heating gives a higher melting rate due to the higher length of solid–liquid interface promoting the heat transfer to solid PCM, thus increasing the melting rate. Again, for different heat distributions of side-wall heating the linearly decreasing heat flux provides the highest melting rate. This type of heat distribution actually transfers more heat to the lower part of the container, which counters the effect of convection, resulting in an enhanced melting process. On the other hand, in the case of distributions at bottom-wall heating, linearly increasing heat flux shows the highest melting rate. In addition, for linearly increasing heat flux, the shape of the liquid cavity is triangular, which gives more space and thereby intense natural convective circulation. This enhanced convection heat transfer leads to a higher melting rate.

A comprehensive review of air conditioning condensate water supply models

Non-potable water building systems have the potential to significantly reduce water consumption, aiding in the preservation of water resources used in urban supply. Among the alternative sources of non-potable water use in buildings, clear waters stand out due to their considerable quality. Condensate water from air conditioning is a kind of clear water that is typically discarded into the sewage. Little is known about the applicability of building systems for using condensate water from air conditioning in buildings - especially within the Brazilian context. To assess the potential for reducing potable water consumption and consequently evaluate the feasibility of implementing air conditioning condensate recovery systems, it is crucial to determine the quantity of available air conditioning condensate. Therefore, this work aims to identify, through a systematic review, the models for predicting the supply of condensed water in air conditioning systems and analyze methods and variables adopted to investigate their applicability within the Brazilian climate context.

Performance investigation of solar energy-aided compression-based building air conditioning strategies for variable climatic regions.

Decoupling cooling and ventilation tasks with an existing air conditioning methodology are a promising performance-enhancement technology. In this direction, different configurations of a desiccant-integrated independent ventilation element attached to a conventional cooling system are proposed in this study. This work establishes a quantitative comparative performance analysis among the different process air cooling (obtained through desiccant dehumidification) techniques for three different climates, namely, hot-dry, tropical, and Mediterranean. EnergyPlus simulations have been executed on a small-scale office building of 400-m2 area. The building constructional details and other required simulation input parameters follow benchmark standards. As the chemical dehumidification increases, the process air, i.e., supply air temperature that cannot be sent directly to the room, needs to be cooled. Three approaches for process air cooling have been considered: direct expansion (DX) cooling coil, indirect evaporative cooling (IEC), and sensible heat recovery wheel (SHRW). A solar collector assembly with a supporting heating arrangement is coupled with desiccant unit for regeneration. Outdoor air is used for regeneration in the case of the DX cooling coil and IEC, whereas return air is used in the heat recovery wheel case. Annual simulation results reveal that the SHRW-aided case performs superior than DX coil case for the pertinent climatic conditions, with 9.6 to 45.01% of annual energy savings. For the IEC, energy consumption was 1.8 to 18.38% less than that of DX coil. Also, using return air in this best-suited case reduces the net thermal energy requirement for regeneration by 14.63 to 71.65% with respect to DX coil.

Efficient harvesting of renewable evaporative energy from atmospheric air through hierarchical nano/microscale shaping of air-water interface

Renewable evaporative energy from atmospheric air is a recently emerged research field that demonstrates the great potential for significant energy savings in the air conditioning of buildings, data/big-data/integrated-big-data centers, agricultural storage facilities, and greenhouses. Here, we develop a method for an essential increase in the harvesting efficiency of renewable air evaporative energy by enhancing the water evaporation rate through the shaping of the air-water interface (AWI) by the menisci formed in superhydrophilic hierarchical surface nano/microstructures. Using this method, we achieve a 10-fold rise in the evaporation rate for the microscale AWI shaping. For the first time, we discover the superevaporation effect that provides an unprecedented 130-fold rise in the evaporation rate at the hierarchical nano/microscale AWI shaping. Furthermore, based on these findings, for the first time, we elaborate a novel material with an engineered AWI for a significant increase in the harvesting of renewable air evaporative energy in the dew point (Maisotsenko cycle) indirect evaporative air conditioning systems whose operation is fundamentally based on utilizing renewable air evaporative energy. The dew point cooling device fabricated using this novel material shows significantly superior cooling performance, validating the substantially enhanced harvesting of the air's evaporative energy. Our findings can essentially advance the emerging field of renewable air evaporative energy and, besides the air conditioning technology, can provide significant efficiency enhancements in water purification/desalination, thermal management, gas turbine power generation, and waste heat recovery technologies.

Personal Comfort System Approach Associated with Fan Usage: A Review

Due to the significant energy consumption of the air conditioner (AC), an alternative energy-saving method is required. To achieve this objective, the design of a building's heating, ventilation, and air conditioning (HVAC) systems must comply to the energy consumption criteria without sacrificing occupant comfort. In this instance, the personal comfort system (PCS) provides a promising means of meeting the demand. This paper aims to summarize the recent discoveries and research on personal comfort systems combined with fan usage. The PCS in conjunction with fan use, which is regarded as the most prevalent thermal adaptation behaviour, offers advantages in terms of conditioning the indoor thermal environment, modulating the person's interaction with the surrounding environmental control system, and reducing the excessive use of energy on HVAC.

Numerical Investigation of Influence of Extent and Position of a Bypass on the Performance of a Single Unit Liquid Desiccant Based Evaporative Cooler

Air-conditioning of buildings is more energy-consuming with widely used vapour compression refrigeration systems in hot and humid areas. Alternatively, evaporative cooling does not show much effect in sultry regions because of increased humidity despite the minimum energy consumption. Indirect evaporative cooling is a promising alternative to direct evaporative cooling systems, but it suffers from low cooling effectiveness and is unsuitable for highly humid regions. Considering the above facts an alternative liquid desiccant-assisted modified M-cycle cooling system is proposed and examined numerically in the present work. The proposed cooling and dehumidification system is a simple unit incorporating chemical dehumidification and regenerative evaporative cooling in a single unit. A simultaneous heat and mass transfer model is developed for the numerical analysis. The numerical code is written in MATLAB and is validated with results available in the literature. Further, numerical analysis was carried out for the effect of various parameters on the performance of the proposed cooling system. The study shows an improvement of 19.2% in dew point effectiveness by incorporating an intermediate opening in the plate separating the product air and working air channels.