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The HVAC (Heating, Ventilation, and Air Conditioning) system is an important component of a building's energy consumption, and its primary function is to provide a comfortable thermal environment for occupants. Accurate prediction of occupant thermal comfort is essential for improving building energy utilization as well as health and work efficiency. Therefore, the development of accurate thermal comfort prediction models is of great value. Deep learning based on data-driven techniques has excellent potential for predicting thermal comfort due to the development of artificial intelligence. However, the inability to obtain large quantities of detailed thermal comfort labeling data from residents presents a substantial challenge to the modeling endeavor. This paper proposes a building-to-building transfer learning framework to make deep learning models applicable in data-limited interior building environments, thereby resolving the issue and enhancing model predictive performance. The transfer learning method (TL) is applied to a novel technology dubbed the Transformer model, which has demonstrated outstanding performance in data trend prediction. The model exploits the spatiotemporal relationship of data regarding thermal comfort. Experiments are conducted using the source dataset (Scales project dataset and ASHRAE RP-884 dataset) and the target dataset (Medium US office dataset), and the results show that the proposed TL-Transformer achieves 62.6% accuracy, 57% precision, and a 59% F1 score, and the prediction performance is better than other existing methods. The model is useful for predicting indoor thermal comfort in buildings with limited data, and its validity is verified by experimental results. [ABSTRACT FROM AUTHOR]

Energy efficient control of thermal comfort has been already an important part of residential heating, ventilation, and air conditioning (HVAC) systems. However, the optimisation of energy saving control for thermal comfort is not an easy task due to the complex dynamics of HVAC systems, the dynamics of thermal comfort and the trade-off between energy saving and thermal comfort. To solve the above problem, we propose a deep reinforcement learning-based thermal comfort control method in multi-zone residential HVAC. In this paper, firstly we design a SVR-DNN model, consisting of Support Vector Regression and a Deep Neural Network to predict thermal comfort value. Then, we apply Deep Deterministic Policy Gradient (DDPG) based on the output of the SVR-DNN model to achieve an optimal HVAC thermal comfort control strategy. This method can minimise energy consumption while satisfying occupants' thermal comfort. The experimental results show that our method can improve thermal comfort prediction performance by 20.5% compared with DNN; compared with deep Q-network (DQN), energy consumption and thermal comfort violation can be reduced by 3.52% and 64.37% respectively. [ABSTRACT FROM AUTHOR]

To avoid unnecessary energy waste due to the single temperature setpoints of the heating, ventilation, and air conditioning (HVAC) system during the seasonal variation period, this study proposed a long-short-term memory (LSTM) neural network to predict and control the temperature setpoint. The thermal comfort, cooling rate, and heating rate were predicted with outdoor environment parameters and occupant count. A large scale of operation data was collected from the EnergyPlus simulation, which was previously developed based on the characteristics of a real case study house. Different kinds of input characteristics were offered to test the stable use of LSTM and other artificial neural networks. This paper discusses the development of a Matlab EnergyPlus co-simulation to predict and control the temperature setpoints of a variable air volume system, especially the relationship between temperature setpoint and energy consumption. The simulation results indicate the advantages of the LSTM prediction of energy consumption and the potential for energy saving with predictive control. [ABSTRACT FROM AUTHOR]

The heat metering of heating is a main link in energy conservation of ventilating airconditioning (VAC) heating. It is of great practical significance to study the heat metering of heating. However, not many scholars have estimated the heat index based on building heating area, in the light of thermal comfort. Therefore, this paper estimates the heat index of VAC heating area considering thermal comfort. Firstly, we analyzed the various factors affecting human thermal comfort. Then, four environmental factors were selected, namely, indoor air temperature, relative air humidity, mean radiation temperature of envelope surface on human body, and indoor vertical air error. In addition, we selected suitable thermal comfort indices to predict and assess the thermal environment under indoor VAC heating. After that, we analyzed the indoor heat flow under VAC heating, examined the components of energy consumption of indoor VAC heating, and estimated the heat index of VAC heating area. Next, a mathematical model was constructed for heat metering, according to the heat consumption of the building VAC, and the composition of the heat consumption of occupants. Experimental results verify the effectiveness of the proposed thermal metering model. [ABSTRACT FROM AUTHOR]

Energy efficient control of thermal comfort has been already an important part of residential heating, ventilation, and air conditioning (HVAC) systems. However, the optimisation of energy saving control for thermal comfort is not an easy task due to the complex dynamics of HVAC systems, the dynamics of thermal comfort and the trade-off between energy saving and thermal comfort. To solve the above problem, we propose a deep reinforcement learning-based thermal comfort control method in multi-zone residential HVAC. In this paper, firstly we design a SVR-DNN model, consisting of Support Vector Regression and a Deep Neural Network to predict thermal comfort value. Then, we apply Deep Deterministic Policy Gradient (DDPG) based on the output of the SVR-DNN model to achieve an optimal HVAC thermal comfort control strategy. This method can minimise energy consumption while satisfying occupants' thermal comfort. The experimental results show that our method can improve thermal comfort prediction performance by 20.5% compared with DNN; compared with deep Q-network (DQN), energy consumption and thermal comfort violation can be reduced by 3.52% and 64.37% respectively. [ABSTRACT FROM AUTHOR]

This paper uses an interview study in Doha, the capital city of Qatar, to consider the role of qualitative methods in identifying how human relationships with air-conditioning are influenced. Drawing on discussions with three groups of comparatively affluent residents who spent significant amounts of time in air-conditioned spaces, it makes four points to researchers hoping to encourage less energy demanding lifestyles. The first is that 'comfort is only one aspect' when a premature focus on comfort obscures other potentially important analytical concerns. The second is that 'air-conditioning changes cultures' when valuable insights may be gleaned from what people say about how it creates, rather than responds to, local preferences and expectations. The third is that 'comparison can be instructive' when different groups may feel themselves to possess very different relationships with air-conditioning. The fourth is that 'discussion can disappear' when those hoping to influence these relationships may benefit from understanding when and how 'conditioning conversations' currently occur and how they could be part of processes of positive local change. After substantiating these points, wider conclusions are drawn about the promotion of less energy consumptive ways of adapting to a warming world and the value of this approach to the cultural geography of air-conditioning. [ABSTRACT FROM AUTHOR]

For areas with hot summer and cold winter, air conditioning is an essential tool to improve the living environment, but the traditional air conditioning needs to consume a lot of energy in cooling and heating, the fan operation noise is large and the sense of blowing will be uncomfortable. This paper briefly introduced the basic structure of a ground-source heat pump-floor radiant air conditioning system and the control strategy which was used for regulating the operation of the air conditioning system. Then, in order to ensure the appropriate comfort and reduce energy consumption, the control strategy was optimized. An experimental room in Xining, Qinghai province, was taken as an example for analysis. The results showed that the thermal comfort under the control strategy proposed in this study was more stable at the moderate degree and the temperature was slightly higher under the traditional control strategy, although the indoor temperature fluctuation under the optimal control strategy was large and the temperature was slightly lower than that under the traditional control strategy; under the control strategy proposed in this study, the air conditioning system had shorter operation time and less power consumption. [ABSTRACT FROM AUTHOR]

There has been an increasing concern on thermal comfort in sleeping environments and its associated energy use in the past few years. To improve the thermal environment and to reduce energy use of air conditioning in bedrooms, applications of task/ambient air conditioning (TAC) systems were proposed and studied previously. It’s indicated that the TAC system can be well integrated with a bed. Due to the variation of the envelope heat gain in a bedroom during night, it is necessary to study the thermal environment inside a bedroom and the energy use of a TAC system for the bedroom at varying envelope thermal loads. Therefore, this paper reports on a numerical study on a TAC system applied to a bedroom with different envelope heat gains. The influences of envelope heat gain on energy consumption of the TAC system and the indoor thermal comfort were studied in this paper. The research results show that at supply air flow rate ( Q s ) of 50 l/s, energy consumption was increased from 47.78 W to 213.11 W, and the PMV value was increased from −1.69 to −1.29 with the increase in envelope heat gain from 3.11 W to 155.6 W. To make PMV equal to zero under different envelope heat gains, linear regression models between supply air parameters and PMV were built and solved. The obtained values form curves where PMV = 0 and give a guide for operation of the TAC system. It was found that the calculation of energy consumption on these curves depends only on envelope heat gain. [ABSTRACT FROM AUTHOR]

This paper presents an autonomous hierarchical control method for a direct expansion air conditioning system. The control objective is to maintain both thermal comfort and indoor air quality at required levels while reducing energy consumption and cost. This control method consists of two layers. The upper layer is an open loop controller that allows obtaining tradeoff steady states by optimizing the energy cost of the direct expansion air conditioning system and the value of predicted mean vote under the time-of-use price structure of electricity. On the other hand, the lower layer designs a model predictive controller, which is in charge of tracking the tradeoff steady states calculated by the upper layer. Control performance of the proposed control method is compared to a conventional control strategy. The results show that the proposed control strategy reduces the energy consumption and energy cost of the direct expansion air conditioning system by 31.38% and 33.85%, respectively, while maintaining both the thermal comfort and indoor air quality within acceptable ranges, which validate the proposed methodology in terms of both comfort and energy efficiency. [ABSTRACT FROM AUTHOR]

Abstract: Air conditioning is essential for maintaining thermal comfort in indoor environments, particularly for hot and humid climates. Today, air conditioning, comprising cooling and dehumidification, has become a necessity in commercial and residential buildings and industrial processes. It accounts for a major share of the energy consumption of a building or facility. In tropical climates, the energy consumed by heating, ventilation and air-conditioning (HVAC) can exceed 50% of the total energy consumption of a building. This significant figure is primarily due to the heavy duty placed on cooling technologies to remove both sensible and latent heat loads. Therefore, there is tremendous potential to improve the overall efficiency of the air-conditioning systems in buildings. Based on today’s practical technology for cooling, the major components of a chiller plant are (1) compressors, (2) cooling towers, (3) pumps (chilled and cooling water) and (4) fans in air handling units. They all consume mainly electricity to operate. When specifying the kW/Rton of a plant, there are two levels of monitoring cooling efficiency: (1) at the efficiency of the chiller machines or the compressors which consume a major amount of electricity; and (2) at the overall efficiency of cooling plants which include the cooling towers, pumps for moving coolant (chilled and cooling water) to all air-handling units. Pragmatically, a holistic approach is necessary towards achieving a low energy input per cooling achieved such as 0.6kW/Rton cooling or lower by considering all aspects of the cooling plant. In this paper, we present a review of recent innovative cooling technology and strategies that could potentially lower the kW/Rton of cooling systems – from the existing mean of 0.9kW/Rton towards 0.6kW/Rton or lower. The paper, broadly divided into three key sections (see Fig. 2), begins with a review of the recent novel devices that enhances the energy efficiency of cooling systems at the component level. This is followed by a review of innovative cooling systems designs that reduces energy use for air conditioning. Lastly, the paper presents recent developments in intelligent air-control strategies and smart chiller sequencing methodologies that reduce the primary energy utilization for cooling. The energy efficient cooling technology, innovative systems designs, and intelligent control strategies described in the paper have been recently researched or are on-going studies. Several have been implemented on a larger scale and, therefore, are examples of practical solutions that can be readily applied to suit specific needs. [Copyright &y& Elsevier]

Generally, conventional controllers for comfort are designed by using on/off control or proportional-integral (PI) control, with little consideration of energy consumption of the system. This paper presents a multi-input-multi-output (MIMO) model predictive control (MPC) for a direct expansion (DX) air conditioning (A/C) system to improve both indoor thermal comfort and air quality, whereas the energy consumption is minimised. The DX A/C system is modelled into a nonlinear system, with a varying speed of compressor and varying speed of supply fan and volume flow rate of supply air being regarded as inputs. We first propose an open loop controller based on an optimisation of energy consumption with the advantage of a unique set of steady states. The MPC controller is proposed to optimise the transient processes reaching the steady state. To facilitate the MPC design, the nonlinear model is linearised around its steady state. MPC is designed for the linearised model. The advantages of the proposed energy-optimised open loop controller and the closed-loop regulation of the MIMO MPC scheme are verified by simulation results. [ABSTRACT FROM AUTHOR]

• Implementation of a model predictive control scheme for HVAC systems is presented. • The hardware/software solution is generalisable to most building management systems. • Cloud solutions can offer low-cost, scalable control in commercial buildings. • Economic MPC reduced energy usage by 1.7% compared to baseline control. • Building thermal performance strongly affects viability of MPC schemes. Many businesses are looking for ways to improve the energy and carbon usage of their buildings, particularly through enhanced data collection and control schemes. In this context, this paper presents a case study of a food-retail building in the UK, detailing the design, installation and cost of a generalisable model predictive control (MPC) framework for its Heating, Ventilation and Air Conditioning (HVAC) system. The hardware/software solution to collect relevant data, as well as the formulation of the MPC scheme, is presented. By utilising cloud-based microservices, this approach can be applied to all modern building management systems with little upfront capital, and an ongoing monthly cost as low as $6.39/month. The MPC scheme calculates the optimal temperature setpoint required for each Air-Handling Unit (AHU) to minimise its overall cost or carbon usage, while ensuring thermal comfort of occupants. Its performance is then compared to the existing legacy controller using a simulation of the building's thermal behaviour. When simulated across two months the MPC approach performed better and achieved the same thermal comfort for a lower overall cost. The economic optimisation resulted in an energy saving of 650 kWh, with an associated cost savings of $240 (an improvement of 1.7% compared to the baseline), while the carbon optimisation gave negligible CO 2 savings due to the inability of the building to shift heating to low-carbon periods. Findings from this study indicate the potential for improving building performance via MPC strategies, however the level of impact will depend on specific building attributes. [ABSTRACT FROM AUTHOR]

In this paper we explore the influence of personal control over space conditioning systems on occupants’ thermal comfort perception. It aims to identify the psychological effects of perceived control as well as the physical impacts when the controllable approaches are utilized. A chamber experiment was conducted, the results from which indicate that subjects with perceived control tended to report more positive comfort perception. The severer the thermal conditions were, the more subjects wanted to use personal control approaches, thus corresponding to stronger psychological effects. When personal control approaches were utilized appropriately, even a slight improvement in thermal conditions could significantly alleviate subjects’ thermal discomfort complaints. These findings provide support to the adaptive comfort theory and can serve as reference for the design of personal environmental control systems. [ABSTRACT FROM AUTHOR]

Faults in heating, ventilation and air conditioning (HVAC) systems cause increased energy consumption, degrading thermal comforts, growing operational cost and reduced system lifespan. An effective evaluation of fault effects is critical to the development of various fault diagnostics solutions, the improvement of operation maintenance and the optimization of monitoring systems. In the HVAC area, a majority of research work in evaluating fault effects was to analyze energy consumption impacts or thermal comfort impacts. However, a handful of research has been conducted on evaluating fault effects on various measurements, which are increasingly employed to monitor equipment's operation. Fault effects on various measurements may display different symptom patterns and present changed sensitivities when the equipment operates under various faults, severity levels, as well as operation conditions. However, a long-term observation of fault symptoms under various operation conditions, different fault types and severity levels to evaluate fault effects is extremely challenging. In this paper, a simulation-based framework was proposed to evaluate fault effects in fan coil units (FCUs). Two metrics namely fault symptom occurrence probability (SOP) and fault symptom daily continuous duration (SDCD) were developed to quantify fault symptoms under various FCU faults. A total of 18 common FCU faults at different severity levels were implemented on the developed HVACSIM+ simulation platform to obtain a full year fault inclusive data set for 48 fault simulation cases. The framework, as well as obtained SOP and SDCD distributions will benefit multiple folds such as the development of probability-based fault diagnostics inference approaches, optimization of sensor location, and fault prioritization. [ABSTRACT FROM AUTHOR]

The car occupies the daily universe of our society; however, noise pollution, global warming gas emissions, and increased fuel consumption are constantly increasing. The electric vehicle is one of the recommended solutions by the raison of its zero emission. Heating and air-conditioning (HVAC) system is a part of the power system of the vehicle when the purpose is to provide complete thermal comfort for its occupants, however it requires far more energy than any other car accessory. Electric vehicles have a low energy storage capacity, and HVAC may consume a substantial amount of the total energy stored, considerably reducing the vehicle range, which is one of the most important parameters for EV acceptability. The basic goal of this paper is to simulate the airconditioning system impact on the power energy source of an electric vehicle powered by a lithium-ion battery. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents the effect of operating water mist system to enhance the energy efficiency of air-cooled chillers under various operating conditions. A thermodynamic model for an air-cooled chiller with twin refrigeration circuits coupled with a water mist system was developed and validated by measured operating data. The validated model was used to investigate how the thermal properties of the entering condenser air and the performance of the air-cooled chiller varied under different operating schemes with water mist pre-cooling. Under the conventional head pressure control (HPC) with a designed water mist generation rate, the coefficient of performance (COP) increased by up to 21.3%. The chiller performance could be improved further under variable condensing temperature control (CTC). Under CTC, chiller COP was increased up to 51.5% with optimal water mist generation rate. The potential energy savings of these chillers serving a representative office building in subtropical climate was evaluated, and CTC coupling with optimal water mist generation rate would reduce the annual total electricity consumption for cooling by 14.1%. The water consumption of the water mist system was comparatively small, comparing with the total water losses for an open-loop cooling tower system with equivalent heat rejection capacity. [Copyright &y& Elsevier]

Abstract: In Hong Kong, conventional air-conditioning (AC) systems cause a high energy consumption and poor indoor thermal comfort. This paper investigated the AC load profiles of three typical local commercial buildings, i.e. office, hotel and retail, and examined the energy consumption of liquid desiccant cooling system (LDCS) for these buildings. Simulation results showed that the cooling load contributed to more than 98% of total annual load, with high latent load proportion from March to September. The high reheating ratio, i.e. from 60% to 90%, is found to be the main reason for the poor thermal comfort. Therefore, the LDCS which could handle sensible and latent loads separately was proposed. However, the electricity-driven LDCS was found not suitable for local commercial buildings. significant energy saving could be achieved by the solar-assisted LDCS system with thermal storage, when the installation area for solar collectors is larger than the minimum required one, i.e. 9.7m2/(kWm−2) for office and 12.7m2/(kWm−2) for hotel buildings. Energy saving of different system types with different installation areas was also studied. The solar-assisted LDCS shows more energy saving in winter but less in summer. Results and conclusions can be useful for researchers and local engineers. [Copyright &y& Elsevier]

Abstract: Because of their excellent performance in local thermal environmental control, task/ambient conditioning (TAC) systems have attracted increasingly more research attention. However, the current applications of TAC systems are mainly for daytime activities, but seldom for nighttime. In fact, TAC systems may be best applied to a sleeping environment, since the subjects to be served by a TAC system are immobile during sleep. Therefore, there is a strong need for studying the operational and energy saving performance of TAC systems when applied to sleeping environments. This paper reports on an experimental study on evaluating the operational and energy saving performance of a novel bed-based TAC system. The experimental results and their analysis demonstrated that the use of the novel bed-based TAC system can help achieve energy saving, compared with the use of a full volume air conditioning (FAC) system. Considering the experimental limitations, the energy saving potential of the novel bed-based TAC system if used in an actual bedroom was studied through a theoretical analysis. It demonstrated that the novel bed-based TAC system would help achieve significant energy saving when used in real buildings. [Copyright &y& Elsevier]

Abstract: This paper explores the potential of reducing the annual energy consumption of a central air-conditioned building through advanced evaporative cooling systems. The building considered is a typical three floor library building of a University. The regenerative evaporative cooling technology is coupled with the liquid cooled water chiller system to accomplish the energy conservation objective. Comparisons of the regenerative evaporative cooling are made with simple evaporative cooling to bring out the importance such a system. The well-known building simulation software, TRNSYS is used to carry out the heat load calculations and the dynamic simulations of the building. Annual energy consumptions of different components of the air-conditioning system are estimated for the existing water chiller system as well as for both coupled evaporative cooling systems (simple and regenerative). The annual energy consumptions, the indoor temperature, the relative humidity and the thermal comfort index ‘PMV’ are compared for all the three different air-conditioning systems. The coupling of direct and regenerative evaporative cooling technologies with water chiller system has shown, respectively, 12.09% and 15.69% savings in annual energy consumption of the building, while maintaining PMV between −1 and +1 for most of the hours in the year. [ABSTRACT FROM AUTHOR]

Abstract: In harsh climatic regions, buildings require air-conditioning in order to provide an acceptable level of thermal comfort. In many situations buildings are over cooled or the HVAC system is kept running for a much longer time than needed. In some other situations thermal comfort is not achieved due to improper operation practices coupled with poor maintenance and even lack it, and consequently inefficient air-conditioning systems. Mosques represent one type of building that is characterized by their unique intermittent operating schedule determined by prayer times, which vary continuously according to the local solar time. This paper presents the results of a study designed to monitor energy use and thermal comfort conditions of a number of mosques in a hot-humid climate so that both energy efficiency and the quality of thermal comfort conditions especially during occupancy periods in such intermittently operated buildings can be assessed accurately. [Copyright &y& Elsevier]

Abstract: This paper evaluates the performance of a personalized air-conditioning system, namely an innovative partition-type fan-coil unit (PFCU), against that of a central air-conditioning system, in terms of their thermal comfort provided and cooling energy consumed. For a cooling load given, it is found that the thermal comfort index (PMV) resulted from the personalized system is always lower than that from a central system. Also, the PMV-curve of the personalized system responds to the loads faster. The experimental results indicate that the personalized system, as compared to the central system, can shorten the operation time for the same level of thermal comfort required and save up to 45% of the energy consumed by the central system. As regards thermal comfort, the experiment with a thermal manikin substrates the PFCU design for its considerable reduction of the cold draft. [Copyright &y& Elsevier]

A 9-month study of four relocatable school buildings, each retro-fitted with small reverse cycle air conditioners (ACs), was conducted to investigate their effectiveness in heating and cooling the classrooms. A comparison with data from previous studies found the energy used by the ACs for heating these temporary classrooms was only 19–20% of the energy used by individual gas heaters installed in permanent classrooms. When equipment efficiencies were considered, the AC units supplied 20–27% less energy to heat the classrooms. The possible reasons for this reduction in supplied energy are explored in this paper. CO2 emissions for the AC units in heating mode, however, were calculated to be 16% greater than for individual gas heaters. The AC units were also used for cooling and on an average the total annual energy consumption for heating and cooling was found to be 11.6 kWh m−2. Responses to a small survey of staff and students about the use and operation of the conditioners are presented. Their responses were more favourable than the predictions of comfort levels in the classrooms using the Predicted Mean Vote–Predicted Percentage of Dissatisfaction (PMV–PPD) model, which indicated “uncomfortable” conditions on average summer days at 3:00 p.m. and average winter days at 10:00 a.m. Background noise levels in the classrooms with the air conditioners in use were above the recommended maximum design level of 45 dB(A); levels of up to 65 dB(A) were measured. [Copyright &y& Elsevier]

Air conditioning accounts for up to 50% of energy use in buildings. Increased air-conditioning-system installations not only increase total energy consumption but also raise peak load demand. Desiccant evaporative cooling systems use low-grade thermal energy, such as solar energy and waste heat, instead of electricity to provide thermal comfort. This system can potentially lead to significant energy saving, reduction in carbon emissions, and it has a low dew-point operation and large capacity range. Their light weight, simplicity of design, and close-to-atmospheric operation make them easy to maintain. This paper evaluates the applicability of this technology to the climatic conditions of Brisbane, Queensland, Australia, specifically for the residential sector. Given the subtropical climate of Brisbane, where humidity levels are not excessively high during cooling periods, the numerical study shows that such a system can be a potential alternative to conventional compression-based air-conditioning systems. Nevertheless, the installation of such a system in Brisbane's climate zone requires careful design, proper selection of components, and a cheap heat source for regeneration. The paper also discusses the economy-cycle options for this system in such a climate and compares its effectiveness to natural ventilation. [ABSTRACT FROM AUTHOR]