Table of contents

PREFACE

The 4^th Asia Conference of International Building Performance Simulation Association (ASIM2018) was held in Hong Kong on the 3-5 December, 2018. ASIM2018 was organized by International Building Performance Simulation Association (IBPSA) - China and co-organized by The Hong Kong Polytechnic University. This biennial conference provides a platform for academics, professionals, consultants, designers, engineers and research students to exchange ideas, knowledge and information about building performance simulation. The participants of the conference came from more than ten countries in the world, with background of either academia or the industry. The success and prosperity of the conference are reflected by the high level of the papers received.

The conference proceeding is a compilation of the accepted conference papers and represents an interesting outcome of the conference. At this conference, we have received papers from authors all over the world, not just from the Asian countries such as Indonesia, India, China, Australia, Japan, South Korea, Singapore, but also from other countries like Ireland, United States, Canada and more. The topics of the conference papers include building physics; simulation and real performance; simulation in design practice; simulation for regulation/code compliance and certification; software/interface development, test and validation; simulation to support commissioning, controls and monitoring; case studies of building simulation application; community/urban scale modelling and simulation; occupant behavior in buildings; indoor environment: comfort, air quality, lighting and acoustic; optimization of control and design; BIM and BEM; uncertainty and sensitivity analysis; and machine learning and data-driven model.

We would like to acknowledge everyone who supported ASIM2018. Each individual help was very important for the success of this conference. Especially we would like to thank the organizing committee and scientific committee for their valuable advices in the organization and helpful peer reviews of the papers.

We sincerely hope that ASIM2018 is a platform for excellent discussions that puts forward new ideas and promotes collaborative researches. We are confident that the proceedings will serve as an important research source of references and the knowledge, which will lead to not only scientific and engineering progress but also other new products and processes.

Prof. Shengwei Wang,

Conference chair of ASIM2018

The Hong Kong Polytechnic University

All papers published in this volume of IOP Conference Series: Earth and Environmental Science have been peer reviewed through processes administered by the proceedings Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing.

In a conventional swimming pool temperature control, the return water temperature is considered as the representative temperature of the swimming tool rather than the average temperature although the latter is more representative regarding to thermal comfort. This is because the average temperature is difficult to measure. This paper uses field data to identify a relationship between the average and the return water temperature and develops a temperature control method based on this relationship. This control method is applied to an open-air swimming pool, for which the heat is supplied from a PCM storage tank. Numerical study, which is resorted to a simulation platform constructed using TRNSYS and MATLAB, is used to analyze the control performance of the new method and demonstrate its effectiveness by comparing with the conventional control.

Building energy efficiency is an important section of energy conservation, while the premise of mining energy-saving potential is clearly obtain the specific energy consumption of each building service system. So electricity sub-metering was widely implemented in China in recent years. Main building energy systems and high-power electrical equipment all can be metered directly except the HVAC terminal units (like fan coils and air handing units), because they are always mixed with lighting system caused by existing electricity circuit design. It is an obstacle to get detailed and systematic sub-metering data. Therefore, an indirect calculation algorithm is necessary. Considering the fact that the amount of historical sub-metering data is huge, the algorithm should be calculated fast and ensure a certain degree of accuracy. And given the variety of building types, it is better that the algorithm also has classification function. To solve above problem, an automatic HVAC terminals energy use calculation method is proposed in this paper. The core algorithm of this method is classification and regression tree (CART). In this research, the establishment of CART model is achieved and the selection of input variables is discussed. Finally, this method is demonstrated and validated in an actual building located in Shanghai.

In the whole life cycle of buildings, proper building energy management is important to achieve energy efficiency. In this research, Building Energy Model (BEM) was used to analyze the energy consumption of a hotel building. The BEM of the building with information of the HVAC system was established to simulate the energy consumption. The performance of the HVAC system was measured using the sub-metering technology. The comparison between the simulation results and the measured performance revealed several problems of the HVAC system in operation, including unreasonable setpoint temperature of the chilled water and a small temperature difference between the supplied and returned chilled water. The BEM was adjusted to take into account the real operational load. Finally, an optimal setpoint temperature schedule of the chilled water was proposed to reduce the operational energy consumption of the HVAC system.

The automatic control strategy of existing heating, ventilation, and air-conditioning (HVAC) systems generally determine the set-point of building thermal environment in accordance with the relevant design criterion or occupants' preference, and have not taken the real-time thermal sensation of human body into consideration, which may make the human body feel uncomfortable under the range of comfortable design parameters. In order to improve the thermal comfort of human body, this paper presented an optimal strategy for indoor building environment control based on the human thermal sensation. The control logic of indoor air temperature based on the thermal sensation of human body was given, and the linear adjustment algorithm was used for realizing the optimal adjustment of indoor temperature set-point. In order to evaluate the performance of the proposed control strategy, a numerical simulation platform was constructed, and a series of simulations were carried out to compare the set-point based and proposed control strategies. The results revealed that the proposed control strategy can improve human thermal comfort and have the potential in energy saving compared to the set-point based control strategy. The proposed control strategy is of significance for the application of current thermal comfort research results and the development of built environment automatic control theory.

The Seaside Momochi District Heating and Cooling (DHC) plant in Fukuoka, which has been operated for more than 25 years, directly uses seawater as heat source water. The current system COP is nearly 1.00, the improvement of which is a focal point in renewal of the DHC plant. The purpose of this study is, through renewal, to present a proposal for a new management and control method of DHC including customers as well as plants. For optimal plant control, energy loss in the whole system should be analysed in detail. In this study, as a kind of energy, pressure distribution is investigated in focus on regional conduit. First, for comprehension of renewal effect, the system COP after renewal is simulated. By optimization of the operation priority order, the system COP is calculated to be about 1.20 at least. Then, for water supply system, pressure loss inside regional conduit is calculated to be very small. By minimization of the energy loss including regional conduits and customer receiving facilities, the total pump water power could be reduced by more than 40 percent. This means that further consideration of supply pump control and system management would significantly contribute to effective energy saving.

A lighting condition has a significant influence on humans' concentration, performance, and eye comfort. A well-designed lighting environment is critical for work efficiency and human health. Lighting design is commonly based on designer's previous experience and computational lighting simulation results. Although simulations can provide relatively accurate calculation results, several difficulties exist in terms of measuring actual users' experience and reflecting their feedback into the design. In this traditional approach, users are unable to experience or feel realistic lighting effects until the installation phase. This lack of user experience in the design phase leads to increasing risk of redesign and revision, which are extremely time-consuming and reduce the efficiency of lighting design. Therefore, it is necessary to minimize the gap between the lighting design and users' satisfaction. This research aims to enhance visualization of lighting design and thus improve the design efficiency by developing a real-time interactive lighting design approach using building information modeling (BIM) and virtual reality (VR) technologies. By integrating these technologies, the proposed approach is able to support user interactions, actual activities simulation, and personalized lighting design. In addition, the proposed approach can provide users with immersive and sensory experiences to evaluate their lighting design alternatives. The whole process of the approach includes 3D modeling in Revit, texture mapping in 3ds Max, simulation analysis in DIALux, and interactions development and VR realization in Unity. A case study was conducted to implement and validate the proposed approach. In this case study, users were able to experience realistic lighting effects and provide their feedback for improving the design in a sensory way while lighting simulation was automatically conducted simultaneously. The approach enables better user experience and provides a practical way to apply BIM and VR technologies to improve the efficiency of real-time interactive lighting design.

In the long-term adaptation of Huizhou traditional dwellings to the local environment, a variety of climatic creating techniques have been formed, and natural ventilation creating technology is one of them. Three methods, i.e. theoretical analysis, simulation and actual measurement are combined to study the natural ventilation creating technology of Huizhou buildings. Natural ventilation design of Huizhou traditional dwelling can be summarized into four types: basic ventilation mode, reinforce of natural ventilation, passive cooling and control strategies. Natural ventilation performance is indicated by field measurement, and the hall and the bedroom both meet the minimum number of air changes per hour. The influencing mechanism of patio on natural ventilation of Huizhou traditional dwelling is studied by CFD software, flow rate is similar between the dwelling with patio and without patio. The wind speed range of the hall is 0.3∼1.4 m / s, and the bedroom is 0.1∼0.5 m / s. Cross ventilation of the hall is restrained and flow direction of each opening is changed by the patio, and chimney effect makes the inflow and outflow of patio simultaneously.

Building form has great influence on energy performance. However, the indoor volume was usually considered as a whole and the difference between perimeter (passive zone) and core (non-passive zone) were rarely discussed. Actually, the energy performance of perimeter space is very unlike the core because of the accessibility to building envelope. The distribution of passive zones has direct influence on building form as well as energy use. In this paper, energy performance of passive and non-passive zones were studied by numerical simulations in three Chinese cities. Results indicate that passive zones normally require more thermal energy than non-passive zone in severe cold climate zone (Urumqi), while south-orientated passive zone could achieve less thermal demand in cold climate zone (Beijing and Lhasa). Among different orientations, the highest and lowest annual energy demand occurs in north-and south-orientated zone, respectively. High potential of energy saving on the west orientation is also noticed. When natural ventilation or window shading are considered, energy demand in west-orientated passive zone could be even lower than non-passive zone in Beijing and Lhasa. Understanding the energy performance of passive and non-passive zone could help to guide building design with the aim of energy saving in the future.

Intelligent control has attracted more attention in the operation of commercial buildings, and the control of lighting system is one significant part. The way of lighting system control in most of commercial buildings is commonly based on occupancy data. The passive infrared (PIR) sensor is mostly chosen to obtain the occupancy data. Compared with the traditional lighting system control method based on constant schedule, the proposed control methods are adjusted by actual occupancy. The problem lies in the inaccuracy of PIR sensor, which causes "false off" when room is still occupied. To solve this problem, the current control method uses delay period as the criteria. In this research, we process the occupancy data, and improve the control method combining occupancy prediction method. The improved prediction method mainly correlates the prediction with historical occupied ratio. Higher accuracy and lower rate of "false off" are achieved.

In this paper, a new heat transfer model for single U-tube ground heat exchanger is proposed. By considering the influence of U-tube heat capacity, an improved infinite composite-medium cylindrical source model is established to calculate the average fluid temperature, and then combined with a quasi-3D heat transfer model in borehole, the inlet and outlet fluid temperatures are derived as functions of average fluid temperature and the heat flow, therefore the inlet and outlet fluid temperatures of U-tube can be calculated. To verify the feasibility of the proposed model, it is applied to a sandbox experiment and compared to other models. The result shows that the inlet and outlet fluid temperatures calculated by the proposed model are accurate in the whole time period. Compared to other models, the inlet and outlet fluid temperatures calculated by the proposed model are in better agreement with the experimental data especially during short time, and the mean absolute percentage error, maximum absolute error, mean absolute error and root mean squared error are basically smaller. The mean absolute errors of the inlet and outlet fluid temperatures predicted are 0.11 °C and 0.09 °C, respectively, and the maximum absolute errors are less than 0.4 °C.

Sensors for the role of control ensure the HVAC system operates reliably and optimally. Among them, the readings of some sensors are the key for the whole system since they are the representation of the controlled objects, such as the chilled water outlet temperature, or the room temperature and so on. Unfortunately, sensor fault is unavoidable due to the system error. The system will be misled to the unexpected or even very severe situation by the controller which got the erroneous input. In this paper, a real building model, which was developed in the simulation environment of the EnergyPlus and its external interface, BCVTB, was employed to investigate the performance under the key sensor fault condition. The chilled water outlet temperature sensor, which is in the supply side of the chilled water loop, and the room temperature sensors, which are in the demand side, were introduced different bias fault from negative levels to the positive levels to reveal the performance changing. Results show that the variation of energy consumption with the sensor fault in the demand side is higher than that in the supply side. Some performance parameters, such as COP of the chiller, and the SCOP of the plant, are quite different, while the indoor thermal comfort is stable under the chilled water outlet temperature sensor fault but different under the fault of the room temperature sensors. This simulation model will be combined with the strategy of the sensor fault detection, diagnosis and reconstruction to accomplish the fault-tolerant control in the future.

We develop a novel mathematical model to represent the dynamics of heat transfer across atrium space, that is, a large open space inside a building. This modeling is established by a combination of an equivalent electric-circuit equation of thermal mass and measurement data. A novel point of it is to introduce not only resistance and capacitance but also inductance to the circuit model, which is different from traditional models of thermal mass and induces the second-order equation of heat balance. We propose to use the so-called Koopman mode decomposition to estimate the values of circuit parameters from measublack time-series data. Effectiveness of the circuit model is established with a numerical simulation incorporated with geometry, structure, and time-series data on a practically-used building in Japan.

In recent years, there has been a tendency to focus on high airtightness and the thermal insulation performance of houses for the purpose of the improvement of the indoor heat environment and reduction in the heating and cooling loads. However, the high airtightness and insulation performance increase the risk of intrusion into the inside of the wall, which causes interstitial condensation because the water vapor generated in the room cannot be discharged to the outside. In this study, we evaluate the anti-condensation performance of the walls using cellulose-fiber-based heat insulation (CF), which has a large moisture capacity and excellent moisture adsorption and desorption performance. The usefulness of CF is confirmed by clarifying the occurrence of internal condensation through measurement data analysis of a demonstration house, as well as numerical simulations.

As a rapid developed area in China, the Pearl River Delta (PRD) has its own building features. Analysis on its characteristic can serve as a reference for future application of energy-saving technologies in this region. As a key factor for energy consumption simulation, a typical building model can be used to evaluate the energy-saving potential of green building materials, designs as well as device. It is of great significance for building energy research, policy formulation, and market orientation. In this paper, a statistic involving over 200 construction drawings is adopted to analyze the correlation among window-to-wall ratio (WWR), building area, building height, building age and floor number after 2000 in the PRD. Finally, based on the analysis of the design parameters of the influencing factors, a typical commercial building model of the PRD is defined.

This study quantitatively analyzed the impact of resident AC (Air Conditioner) use behaviors on the cooling energy use of residential buildings. Behavior models extracted from different households were applied to a building of identical performance to compare cooling energy use according to behaviors. The behavior model used in this study is an AC on/off state prediction model using random forest algorithm; three models extracted from respective households were used. To apply the AC on/off state predicted through random forest, BCVTB was utilized for a co-simulation of a data analysis tool(R) and an energy analysis tool (EnergyPlus). The results showed that despite the identical physical and system performance of the building, the cooling energy use differed by as much as 2.5 times at set temperature 24°C. This study confirmed the possibility of integrating various prediction algorithms with energy analysis tools in future studies and quantitatively reaffirmed the need for behavior studies in the cooling energy use analysis for residential buildings.

Thermally activated building structures with latent heat thermal energy storage (LHTES) are relatively new elements of building thermal energy systems. The system considered in the present study involved lightweight wall panels with a plaster containing a microencapsulated phase change material (PCM). The polyethylene tubes of small diameter for heat transfer fluid were embedded in the plaster. The wall panel system could be used for both heating and cooling. The PCM provided short-term thermal energy storage in case of intermittent supply of heat and cold (e.g. in case of a PV powered heat pump). A 1D computer model of the wall system was developed and implemented as a TRNSYS type. Consequently, an optimization model based on the 1D model of the system was developed. The optimization model employed a metaheuristic particle swarm optimization method. The aim of the optimization was to determine the position of the tubes for HTF, relative to the surface of the panel, that would provide fast thermal response and, at the same time, high amount of stored heat. The optimization was performed for heating operation.

A ceiling radiant cooling system (CRCS) can provide comfortable environment with less energy consumption. It has been reported that the amount of heat removed by only radiant panels increases compared to one removed by only air handling units (AHUs) due to the existence of a plenum. However, few studies have focused on installation conditions of CRCS and surface temperature of radiant panels. Therefore, we proposed a new calculation flow to decide cooling system specifications, where we considered an impact of a plenum and the surface temperature of panels. In the conventional flow, the amount of heat covered by AHUs and the equipment capacity are determined by subtracting the assumed capacity of radiant panels from the load without radiant panels. On the other hand, in the proposed flow, the amount of heat covered by radiant panels and AHUs and the capacity of them are simultaneously calculated by using a thermal network model considering the impact of radiant panels on the wall surface temperature. In this study, we carried out case studies for different installation conditions of CRCS and examined the cooling loads and the equipment specifications. As a result, regardless of the laying area of radiant panels, the entire cooling load removed by both radiant panels and AHUs in the proposed flow was higher than that in the conventional flow. Furthermore, depending on installation conditions, we found that there is a possibility that the equipment capacity of AHUs is underestimated in the conventional flow. In addition, through the proposed flow, supply water temperature can be slightly raised when the heat capacity of the building is larger. This study will contribute to the establishment of the correct design method of CRCS. From now on, we need to study about the design of CRCS considering the energy-saving performance including heat source system.

Hybrid residential HVAC system, comprising of with a natural gas furnace and an air-source heat pump (ASHP), is gaining interest as a more environmentally friendly alternative to conventional HVAC system with a natural gas furnace and central air-conditioner. Such hybrid HVAC systems could take advantage of the relatively clean and cost competitive time-of-use (TOU) electricity pricing to meet heating demand with the ASHP during milder winter temperature and off-peak hours. Current hybrid systems rely on a pre-set outdoor temperature set point for heating source switching, thus making such system inflexible and not optimal. In the current study, the NZEH model was experimentally validated using collected data and an extensive sensitivity analysis was performed. The Smart Dual Fuel Switching System (SDFSS) was simulated to operate in different scenarios including different major cities in Ontario (Canada), different types of residential houses, operate under the proposed federal carbon tax and operate with different new time-of-use electricity pricing schemes. The different scenarios demonstrate the benefits and flexibility of such Smart Duel Switching System in terms of reducing the space heating energy consumption and associated operating cost and greenhouse gas emission on an annual basis.

Modeling and predicting building infiltration impact on building energy performance presents a challenge. This paper analyses the modeling method of infiltration rates in different simulation programs. Field blower door test results of building infiltration rates are compared and summarized. Based on literature simulation and field study data, this research analyses the building infiltration rates on the office building HVAC energy use under various climate conditions. Suggested and preferred infiltration rates under various climates are listed.

In the research of energy internet, demand response has become a hot issue which has been widely concerned. The residential load optimization model was constructed, which takes into account factors such as environmental change, electricity price, user habits, load fluctuation and so on. The adaptive harmony search-particle swarm optimization algorithm was used to solve the model, which got the program to meet the needs of users. It is the fusion of the particle swarm optimization algorithm and the harmony search algorithm. The simulation results were based on the actual time-sharing price, outdoor temperature and load parameters. After the simulation, the user load curve was improved and the electricity consumption and energy used was obviously reduced, which proved the algorithm is effective.

Most supply air temperature in variable air volume systems is typically set at 55F(13 °C) that is design value in these systems. However, sometimes the load of cooling varies greatly in different zones, and it means the indoor temperature of low-load zones is lower than comfortable value, even if the supply air damper is at the minimum value that is not closed for minimum outside air requirement. Meanwhile, in transition season, the indoor temperature is also lower due to low outdoor temperature. These factors provided an opportunity to apply higher supply air temperature to reduce air handling unit (AHU) cooling load and box reheating. In this paper, a cascade control method is used to raise the supply air temperature. The external control loop controls the setting value of supply air temperature with the minimum supply air volume as the control target. And the internal control loop controls the supply air temperature by regulating valve. The cascade structure can solve the problem that the time constant of the system is too large. The simulation results show that the quality of control is good and the reheating can be cancelled.

A novel π-shape device (π-D) was developed based on air full pressure supply theory to realize the uniform air/smoke exhaust for long duct with enormous vents in subway tunnel. To validate its performance, numerical simulation of internal flow field of the duct with π-D was conducted. Then an experimental 65-meter-long exhaust duct with π-Ds was set up in accordance with the real size. The air exhaust velocities of each vent and the total head losses along the main duct were measured. Both experimental and simulation results showed that the proposed new device could be designed and equipped flexibly into the long air/smoke exhaust duct. It would significantly enhance the ventilation uniformity, reduce the airflow resistance by 50%-65%, and achieve above 20% of distribution energy saving as well.

Deterministic chiller optimization control strategies, such as COP optimization strategy, are intended to save energy based on deterministic sensor measuring data and equipment characteristics. However, the sensor data and the equipment characteristics are typically uncertain due to poor calibration of sensors, poor maintenance of chillers, etc., which could harm the energy-saving performance of deterministic chiller optimization operation strategies. In order to tackle this problem, a stochastic chiller optimization operation strategy based on uncertainty analysis is proposed in this paper. The strategy consists of three steps: (1) Analyze the uncertainty of the HVAC system and specify the probability distribution of each uncertain parameter. (2) Calculate the mathematical expectation value of energy consumption and return chilled water temperature in each operation plan under uncertainty. (3) Select the operation plan with the least energy consumption expectation and limited return chilled water temperature. The performance of the proposed strategy is validated on TRNSYS with measured hourly cooling load data of an office building located in Shanghai. Compared with the deterministic optimized operation strategy, the proposed stochastic strategy performs better on robustness (i.e., keeping return chilled water temperature within safe criteria) because of the consideration of measurement uncertainty. Also, compared with traditional operation strategy without optimization, the proposed strategy performs better on saving energy

Prediction and optimization of energy consumption is valuable to recognize the status and assist in green campus retrofitting and energy efficiency making. The study focused retrofit strategies in subtropical Guangzhou to achieve energy efficiency in a higher educational campus. According to the building's envelope features, optimization using a pseudo orthogonal test based on assumption of window design. In this paper, field investigation and numerical simulation were used to assess the thermal performance of this building. The prediction was primarily verified using a numerical simulation with 16 cases. It was concluded: (1) on basic cases, the results revealed the methods' reliability based on Energy-plus is adopted in the green campus; (2) the retrofit cases in thermal performance considering the building envelop, solar shading and windows' glazing; (3) the rooms of divergent orientation play varied significant role in energy consumption. The study provided the technic support for the energy optimization strategies of campus building in hot humid area.

Common architectural visualization is using 3D digital model represented in 2D media such as screen and papers. However, this method has two limitations. First, it does not have a full scale to provide a true perception space. Second, the 2D media to represent the 3D model is static. These limitations diminish the user's experience and understanding of space. Currently, architectural visualization is starting to utilize technological advances of virtual reality (VR) and interactive game engine. The full-scale projection in VR can minimize the perception gap between the client's and the designer's idea. It also has interactivity that enables users to explore the space and perform direct manipulation at some design aspects. This paper observes how VR and interactive technology is used to explore scale, lighting experience, and material iterations. The research was conducted for one semester in 2 courses. In these courses, students worked in groups to create, experience, test, and evaluate their design through 3D VR environment and interactive representation. Afterwards, the VR was tested to common users. We examined the enhancement that users get by experiencing design through VR compared to viewing the architectural visualization on picture and discuss how this could be improved and integrated to curriculum.

Energy consumption simulation is widely used to analyse dynamic energy consumption in large spaces. In this paper, a real Engineering Training Centre (ETC) in Shanghai was took as the research object, and its energy simulation models were established by EnergyPlus. The zone division was combined with Room Air to investigate the rational forms of the ETC models. The results showed that the simulated values of the hourly air temperature and the hourly cooling (heating) load using Room Air were more close to the measured values, and the different zone division had different simulation advantages for summer and winter cases. Therefore, the modelling ideas for dealing with energy simulation in large spaces in different seasons were provided.

Desiccant air handling unit (DAHU) dehumidifies moisture in the air with adsorbent or sorbent. Hot water is necessary to regenerate them. In many buildings, for regeneration of the dehumidifier, hot water from combined heat and power (CHP) is used because it can supply hot water at stable temperature. When using fluctuating energy such as hot water from solar thermal collector, it is mixed with hot water from CHP in order to compensate the fluctuation, and supplied. In order to use renewable energy including solar thermal energy efficiently, we propose flexible control compared to ordinary fixed control. The ordinary fixed control controls outlet air temperature of pre-cooling coil at fixed temperature, for example 19°C, and the relative humidity is 100%. Therefore, dehumidification amount at dehumidification wheel as well as regeneration coil demand does not fluctuate very much. On the other hand, flexible control controls outlet condition of pre-cooling coil with absolute humidity of supply air and hot water temperature to regenerating coil. When hot water temperature is enough hot, absolute humidity of supply air fulfills set point, therefore pre-cooling coil demand decreases. When hot water temperature is not hot enough, supply absolute humidity does not fulfill the set point. In this case, outlet temperature of pre-cooling coil will get lower in accordance with hot water temperature. This study investigates the behavior and performance of DAHU under different control methods through energy simulation. Simulation results show that when installing flexible control, outlet air state of pre-cooling coil is determined depending on the hot water temperature to regenerating coil. It proves that it is possible to handle required latent heat load even when hot water temperature is low around 45°C. DAHU with flexible control can contribute the effective use of solar thermal heat.]

In order to compare the design of hybrid energy systems for on-grid and off-grid applications, a university dormitory in central China is selected and investigated to achieve the target of a zero energy dormitory. The building is modeled in DeST and hybrid system design optimization is performed in HOMER. Results show that the on-grid hybrid system under time-of-use rate policy is much more economic than that under single rate policy for on-grid case. The total net present cost is 230,534 $ and the levelized cost of energy is 0.124 $/kWh. The off-grid system with generators is more economical than system without them, and the cost is found to be about 6 times than on-grid system. Sensitivity analysis is performed by considering sell-back price and diesel price, it is found that NPC and COE can be increased by 9.7% and 12.7% for the decreased sell-back price and doubled diesel price respectively.

With the accelerated development of dynamic energy consumption simulation software, the accuracy and feasibility of steady-state calculation method for energy efficiency designs of residential buildings in severe cold and cold zones should be investigated. A six-story residential building model as a case study is introduced to be calculated and simulated by steady-state calculation method elaborated in 'Design standard for energy efficiency of residential buildings in severe cold and cold zones' and dynamic energy consumption simulation of EnergyPlus software respectively, in order to compare and analyze the differences between these two methods in five typical cities of China (Xi'an, Lhasa, Xining, Harbin and Hailar). The findings indicate that the index of heat loss of building obtained from both methods is different to typical cities with varied difference ratios. Especially in cities of high altitude, strong radiation and greater diurnal range, namely Lhasa and Xining, the difference ratio is as high as 43.83% and 16.63%. Thus, dynamic energy consumption simulation should be used for counting residential building energy efficiency instead of steady-state calculation method in above mentioned zones by analyzing main factors concerning the differences.

This study demonstrates an experimental example of application of time-lapse high dynamic range images for analyzing variations in correlated color temperature (CCT) and circadian lighting in an interior space daylit using a tubular daylight device (TDD). Previous studies have shown that the spectral composition of daylight affects human circadian rhythms, with emphasis on wavelengths towards the blue region of the visible spectrum. Spectrally based metrics such as CCT can therefore aid in evaluating the circadian impact of daylight. TDDs redirect daylight towards interior spaces with changing light levels and color temperatures during the daylight hours. This paper details the color temperature and circadian lighting metrics (circadian luminance and illuminance) in an interior space throughout a period of several days in a mid-latitude, temperate, sunny climate. An automated time-lapse HDR photography apparatus was modified to allow for calculation of CCT and circadian lighting metrics using state-of-the art techniques available in the literature. Prior to the measurements in the space with the TDD, this device was calibrated against a spectrophotometer. Results indicate the level of daily variation in CCT and circadian lighting metrics that can be expected in interior spaces daylit by TDDs without any other sources of daylight. Besides showcasing the use of HDR techniques, these results could be used to support design decisions involving daylighting in interior spaces. These techniques can also be used outside the laboratory in the evaluation of the circadian impact of lighting throughout the built environment.

In this paper, the wind characteristics on building with single-sided louvers under different wind directions were studied by using computational fluid dynamics (CFD) method. The RNG k-ε model was employed to establish the different outdoor airflow fields under different rotation angles θ of louvers. To investigate the wind pressure on facades, wind pressure coefficient C_P was introduced and average surface difference ΔC_P was applied to evaluate wind-induced cross ventilation between the shaded and the opposite building surfaces. Results show that airflow pattern around the studied building is highly dependent on the building envelope under shading conditions due to obstruction and diversion of louvers. In general, the larger rotation angle of louvers contributed to more differences in average surface C_P under both normal and parallel wind directions. Shading louvers lead to an increase in ΔC_P for parallel approach flow and a decrease in ΔC_P for perpendicular approach flow. In simulations of this study, it could be seen that ΔC_P decreases 0.01 (1.6%) for θ = 0° and 0.15 (18.0%) for θ = 60° under normal wind direction, while ΔC_P increases 0.05 (436.1%) for θ = 0° and 0.15 (1393.5%) for θ = 60° under parallel wind direction. The results elucidates that a larger rotation angle can affect wind-induced cross ventilation more strongly. What's more, the locations of minimum and maximum C_P on some facades moved obviously after shading and turning up rotation angle. This study indicates that the influence of complex building envelopes like shading louvers, should be considered in ventilation design.

Lighting designs, both daylight and artificial light, have a major effect on creating visual comfort and room atmosphere. The Parahyangan Catholic University's architectural design studio room has its limitations in providing daylight into the room, where a lot of the literatures express the importance of daylight's role to room quality. This study aims to evaluate the lighting quality in the studio and provide lighting design recommendations to improve the user's productivity and creativity. Data were collected through observation to obtain physical room data and existing lighting design. DiaLux software is used to simulate the lighting performance. User's perception about the room quality obtained through questionnaires distributed to students. The results show that despite the below-standard illumination level, respondents are still well-rated the studio lighting quality. Visual comfort perception is higher than the room atmosphere perception. The lighting techniques, illumination levels, light colors, room reflection factors, and daylighting contribution are the factors that most affect the room quality.

In the design stage of air-conditioning equipment, by predicting the annual air-conditioning energy and heat load with high accuracy and by comparing multiple designed air-conditioning systems, it is possible to select optimal equipment and reduce capital investment. However, occasionally, it is difficult to predict energy consumption by means of energy simulation (ES) assuming that the thermal environment of the room is uniform, because of various reasons such as the influence of the uneven distribution of the pieces of equipment that act as heat loads, and mixing loss due to the air-conditioning system. In addition, when evaluating an air-conditioning system considering human comfort in a room, it is necessary to calculate a comfort index such as the Predict Mean Vote (PMV). In that case, it is important to predict the distribution of the thermal environment such as the bias in wall surface temperature. Therefore, attempts have been made to combine Computational Fluid Dynamics (CFD) with energy simulation for predicting the distribution of the thermal environment. However, in a few cases, measurements are made considering thermal load fluctuations in actual outdoor environments, and validation of CFD analysis is performed. Therefore, in this study, in a laboratory simulating an office, considering the effect of actual solar radiation, we measured the performance by changing the air-conditioning system of the perimeter zone and analysed the behaviour of thermal load in the room. Subsequently, by comparing the actual measurement results with the results of unsteady CFD analysis, the prediction accuracy of indoor temperature distribution and air-conditioning heat quantity was validated. As a result, it was clarified that the prediction accuracy of indoor temperature distribution is affected by how the airflow that was directed out of the air conditioner in the perimeter section collides with the window shade.

Currently, energy savings in buildings are an urgent issue to be tackled in the world widely. In Japan, energy savings in buildings have been promoted through some policies such as energy saving standard compliance, Building-Housing Energy-efficiency Labeling System (BELS), and relevant subsidies. For more efficient policy making, it is important to estimate how those policies work and which of them should be considered to be important. Firstly, we developed agent-based simulation incorporating decision making model of building owners and tenants. Building owner agents apply energy retrofit based on energy saving policies and tenant agents move their offices to maximize profits based on a given circumstances such as energy efficiencies of buildings. Their decisions influence each other and we analyzed their behavior. Since the demonstration for all actual office buildings in target area is costly task, it was conducted in downscaled area while keeping statistical characteristics of office buildings in target area. The target was a business district in Tokyo, Japan. Then using the simulation, we demonstrated the effects of the policies. The results show that it is not easy to accelerate energy saving with only subsidies; appropriately combining subsidies and standard compliance obligations allows energy saving to be progressed.

Vegetation pattern and wind speed have a significant impact on outdoor thermal environment. This paper takes the air temperature of pedestrian areas in building group as the analytical variable. The simulation software of ENVI-met is employed to analyze air temperature variations under different vegetation patterns, tree heights and wind speeds in Shanghai. Firstly, a lot of cases are established to analyze the impact of vegetation patterns on outdoor thermal environment. Secondly, different tree heights are talked about to analyze the impact on outdoor thermal environment. Finally, the impact of wind speed is added on the basis of previous cases. The simulation results show: The tree pattern has the best cooling effect in three vegetation patterns, which can reduce the temperature by about 1°C; Within a certain height range, the taller the tree is, the more obviously the thermal environment temperature reduces; Higher wind speed is beneficial to reduce the ambient temperature of pedestrian areas, but it will lead to intensified uneven temperature distribution and make pedestrians feel uncomfortable. The simulation results can provide references for the preliminary planning and design of building group.

Faults cause building systems to under-perform in operation. An operation and maintenance process of building systems using fault detection and diagnosis (FDD) essentially requires evaluating the influence of faults in advance because deciding how to respond to faults is necessary to establish the strategies. However, many studies on FDD in a building's operation have not considered these processes. Then, we focused on sensor errors as faults at ten temperature sensors and four flow sensors in a real heat source system and examined to evaluate the influence of faults. The real heat source system with two chillers and two cooling towers were used to demonstrate calculating system behavior with sensor faults, analyzing results, and evaluating the influence of sensor faults. We developed a detailed simulation model of the system covering a sensor network and combining automatic control system based on the specifications. Using this simulation, we calculated the system behavior without faults and behaviors with fourteen sensor faults in six fault severity levels. As for the annual system coefficient of performance (SCOP), the results showed that sensor faults had influence in various degree and each sensor has different features against fault severities. Some sensor faults had no effect on the system controls, but others had wide influence on controls of sub-systems and energy efficiency reduction. By considering these features of sensor faults, we evaluated the influence of each faults using the annual SCOP as an indicator. Using this method, we analyzed the influence of faults in detail and prioritized sensor faults using the indicator. It is expected that this fault evaluation method helps operation and maintenance of the system.

Urban energy supply systems are changing to distributed energy supply systems according to the spreading of renewable energy. In order to effectively arrange and operate distributed energy supply systems in the city, it is necessary to (1) predict energy demands for each use in each building, (2) consider operation technology such as interchange or storage, and (3) study on a city scale rather than a building scale. Therefore, we aim to construct a method to calculate the optimal energy supply system with renewable energy based on data from geographical information systems (GIS). This paper describes the development of an energy-demand prediction method for non-residential buildings and a demand analysis in Japanese business areas by using this method. For the demand analysis, we developed a method to predict the demand of electricity and heat (heating, cooling and hot water) of non-residential buildings for one year. This program fluctuations in demand by five-minute intervals depending on the type of buildings (office, hospital, hotel, store, restaurant and school), total floor area, outdoor air temperature and so on. The standard demand amount of each type of buildings is based on statistical data and measurement data about energy consumption of non-residential buildings in Japan. Furthermore the fluctuation method of the demand incorporates random number simulation and probability distribution to reproduce an actual fluctuation. We predicted and accumulated the demand for hundreds of buildings by three districts for the demand analysis in the whole district. One of these analyses showed that there are large fluctuations in the demand of each building, and these fluctuations decrease by grouping the buildings in the block. Moreover, we analyzed the gap of peak demand between aggregated individual buildings and districts. This analysis revealed that some of peak demand in districts are less than 40% of aggregated individual.

The railway station is a representative kind of large space building, whose air-conditioning system design has always been paid a lot of attentions. At present, the air-conditioning system at a train station is mainly a stratified air conditioning mode with spout air supply outlets, which has a significant thermal stratification and energy waste in winter. In this paper, a large space waiting room of one railway station in Wuhan is taken as the analysis example, and the CFD method is used to simulate the airflow and temperature distribution under different air-conditioning terminal devices in winter and summer. The airflow organization models of the waiting hall under three typical air-conditioning systems have been established including stratified air conditioning system, air handling unit special for large space system and floor radiation system. The temperature and velocity distributions of the large space in the waiting hall are comparatively simulated under each system. The temperature stratification, the amount of cooling and heating requirements are obtained for three types of air conditioning systems. According to minimum amount of the annual cooling and heating loads, a terminal device form of air-conditioning system which is suitable for large space is provided. The results can provide a reference for the design of air-conditioning systems for similar large space buildings.

Building occupant density is a key factor influencing urban energy consumption. However, it is difficult to predict and thus often simplified to be an assumed and fixed number in urban energy simulation. In this study, the hourly occupant densities of ten representative commercial buildings in Nanjing, China were measured. The pattern of the hourly occupant density was analyzed and the key parameters defining the pattern were identified. To expand the measured hourly occupant density pattern to thousands of commercial buildings in Nanjing, five predictors, namely function, accessibility, population, business diversity, business density, were proposed. Big data technique was used to obtain the value of the five predictors for more than 3000 commercial buildings. A regression analysis was conducted to establish a model linking the five predictors with the parameters defining the hourly occupant density pattern. The methodology developed provides an effective means to predict the hourly occupant density of buildings and thus substantially improves the accuracy and reliability of urban energy consumption.

Jogging is increasingly popular as a robust activity. However, the concentration of the exhaled carbon dioxide exposes to human during the outdoor exercise. Thus, the healthy air supply is in growing demand. By changing vertical and horizontal locations and air supply rate, an additional airflow field can alter the performance of local ventilation. This work assumes the addition of an auxiliary personalized ventilation device (PV), under various specific air supply rates, distances and angles to investigate the optimization of concentration dissipation and microclimate promotion. The results show the flow field characteristics and concentration distribution in respiration area under an unsteady breathing process. Based on the orthogonal test, the condition with those determined parameters (the supply velocity: 3m/s, distance from the nostrils: 2cm and the angle: + 20 °) has the optimal performance. Moreover, the velocity of air supply is the primary factor among other factors that influence the performance of pollutant removal, through the sensitive test.

Ground source heat pump, as renewable energy technologies, are increasingly appearing to provide the indoor thermal environment for residential buildings in Hot Summer and Cold Winter zone. However, it needs to be tested whether GSHP is proper to the Hot Summer and Cold Winter zone? From 2012-2017, comprehensive field test was carried for 8 GSHP systems of residential buildings in Hot Summer and Cold Winter zone. The field test focused on performance of GSHP and the heat balance of ground source, which is an important factor for the application of ground source heat pump systems. In this paper, the analysis results of the balance of ground source of the systems with different AC terminal units are different from each other. The main influence factors for the heat balance of ground source are performance of heat pump and heating/cooling demand of buildings. The results of field test reveal that there is little difference for COP of heat pump. The heating/cooling demand is different for different systems. The further investigation reveal that the occupant behavior of different AC terminal units may determine heating/cooling demand of system, which resulted in the difference of the heat balance for ground source. The paper proposed an integration model of building load simulation considering the occupant behavior and GSHP systems. A case study will be conducted to quantitative analyze for the influence of the occupant behavior of different AC terminal units on the balance of ground source.

Discomfort glare frequently occurs in the west-facing rooms of office buildings during the afternoon. Using conventional opaque and fixed solar screens can obstruct the direct solar radiation, and reduces the glare. However, they may considerably reduce indoor daylighting levels and block the view outside at the same time. Thus, dynamic translucent panels are proposed in this study as external solar shading screens on the west-facing facades. Most importantly, a systematic method is developed to optimize the positions of the panels, addressing both daylighting, glare and view. The optimization algorithm - Artificial Neural Networks, combined with daylighting performance simulations is used to determine the optimal design parameters of the proposed solar shading screens. An office room in Guangzhou is used as a case study to test and optimize the proposed method. The whole study process consists of three steps: simulation, regression, and optimization. The results show that the neural network regression results are very close to the simulation ones. It means that deep neural networks can achieve a relatable regression performance and reduce the optimization time significantly. The optimal positions of the solar screens effectively reduce the glare level and maintain a relatively high indoor daylighting level and a large view field. Furthermore, this study also discusses the different effects of the weights for evaluation indicators on the final optimization results.

By 2030, South Korea plans to reduce greenhouse gas (GHG) emissions by 37% compared to current business-as-usual emissions. In response, the aim of the study proposed here is to analyze current building design trends in South Korea and provide baseline data to develop a reference model for the effective reduction of GHG emissions in South Korea's building sector. First, the energy conservation plans of a recently 3 year designed retail building will be examined. The subject of the survey was divided into the areas of construction, machinery equipment, electric equipment, and lighting. Second, statistical analysis will be performed for the medium, median, and mode values for each item investigated, which will be used to determine representative values to apply to the reference building. Third, the building will be compared with another building of similar size and finalize the settings of the reference building. Last, using simulation tools, energy consumption will be estimated and characteristics analyzed for the reference building. By expanding the energy consumption characteristics of the reference building model obtained from this study and comparing them with the building energy consumption characteristics in South Korea's National Integrated Building Energy Management System (NIBEMS), a detailed target for the national-level building energy performance enhancement and greenhouse gas reduction management can be defined. In addition, the energy consumption potential for each technological element can be analyzed by using the reference building and policy improvement measures and incentive criteria can be established.

During a process of building an experimental facility, the thermal bonding joint of organic glass bulk polymerization needs to be annealed by a heating belt with the heat flux density of 4200 W/m². The excessive heat needs to be removed efficiently to avoid damaging the surrounding areas. In this paper, the cooling effect of the air supply velocity on the high heat flux surface is investigated using CFD simulations, while the air supply temperature and volume are kept constant between cases. The results show that the air supply velocity has a significant impact on the cooling process of the high heat flux surface. With the increase of air supply velocity, the maximum and average temperature of the high heat flux surface decrease significantly. In addition, the cold air of large velocity could effectively suppress the spread range of hot air. These results provide a reference on the further study of organic glass annealing process.

The imbalance of the electrical grid between source and demand causes great decrement of grid efficiency and energy loss. The main reason for the imbalance comes from the fluctuation of electricity consumed by buildings. Numerous efforts have been conducted to mitigate the fluctuation of buildings electricity consumption. The phase change material (PCM) can store heat or cold to keep indoor thermal environment stable for a certain period without heat/cold supply from heating, ventilation, and air-conditioning (HVAC) systems. It can effectively shave the peak of HVAC electricity demand. Meanwhile, the electricity cost of running HVAC systems can also be cut down. Therefore, this paper proposes a novel type of air-ducts integrated with PCM and studies its performances of the indoor thermal environment through theoretical analysis and dynamic simulation. The simulation results show that the indoor thermal environment can be kept within the comfortable range when turn off chiller during the peak load period using the proposed PCM integrated air conditioning ducts.

Energy consumption for space cooling is increasing in Chinese residential buildings due to the extensive use of split air conditioners. To build a comfortable indoor environment and reduce energy consumption, comprehensive understanding about human thermal requirements of air conditioning is highly needed. As a reflection of human demand for indoor thermal environment, thermal sensation is usually under the effect of human physiological responses. For these reasons, a series of experiments were conducted in a climate chamber to understand human physiological thermal responses in air conditioning environment. During the experiments, indoor temperature was kept at 29°C in the first 30 minutes and then cooled down to 25°C in the next 30 minutes, after that, indoor temperature was held stable in the final 60 minutes. Twenty subjects were recruited to participate in the experiments. Results reveal that first, the temperature of limbs was lower than trunk due to the blood flood and clothing resistance, second, skin temperature and Thermal Sensation Vote(TSV) may still be in the dynamic change after the ambient temperature reached stable, third, significant linear correlation was found between skin temperature and TSV in the limbs, moreover, individual difference could be found in local skin temperature.

Various types of faults occur in building energy systems throughout their life-cycles. Some faults grow gradually causing system energy penalty and performance degradation. Hence, it is crucial to implement an efficient fault diagnosis strategy and maintain optimal operations for systems. Recently, data-driven methods have got increasing interests due to the model flexibility and data availability. The fast development of data science has provided advanced data analytics to tackle data classification problems in a more convenient and efficient way. This paper attempts to investigate the potential of a promising data analysis technique, i.e., deep neural network, in classifying and diagnosing faults in a building energy system, i.e., centrifugal chiller plant. This study exploits the deep neural network based method in both supervised and unsupervised manners, and compares the fault diagnosis accuracy. Centrifugal chiller experimental data from the ASHRAE Research Project 1043(RP-1043) are used to validate the proposed method. Results show that the method can correctly diagnoses the fault data for seven typical chiller faults.

The proportion of electricity used for civil buildings is increasing, which intensifies the imbalance between the demand side and supply side of the grids and leads to a large decrement in grid efficiency and large energy losses. The phase change material (PCM) can be used to store numerous heat or cold for heating, ventilation, and air-conditioning (HVAC) systems for its phase change temperature range suitable for maintaining comfortable building thermal environment. Utilizing PCM for HVAC is an important way to mitigate fluctuations in the power consumption of buildings. This paper proposes a new type of air-conditioning duct combined with PCM. The demand shift effects of the PCM integrated air-conditioning duct is studied through experiments. The PCM material ingredients are designed according to the required phase change temperature range. The feasibility of PCM application in HVAC ducts is verified. The results show that air-conditioning duct combined with PCM can keep the indoor temperature in a comfortable range during the power peak load after shutting down chiller.

During the last decade, the energy consumption of residential appliance has grown rapidly in China and accounted for 20% of total urban residential energy consumption in 2015. Many studies show that the occupant behavior has a great influence on the appliance energy consumption. Due to the changes of Chinese residents' lifestyle, the total energy consumption of residential appliance has changed a lot, so it is an important factor when we select the technology roadmap and make policy suggestions. For existing research of macro energy modelling, there is less consideration on occupant behavior. So we develop a new macro energy model to analyze the residential appliance in urban China, considering the influence of both technology and occupant behavior. This research developed a bottom-up model and did a case study on China urban residential television. The energy consumption of television in China urban households was calculated and scenarios are established to analyze the related policy suggestions. For model input, we got the panel data by conducting many regional range or nationwide survey during 2008∼2015, and arranging the data from yearbook or database. The survey and modelling analysis output the total residential television energy use in urban China by different technology, different province and different occupant behavior. The results show that total energy consumption of television starts to decline from 2011, this is mainly due to the continuous decrease of television watching duration in China urban households and the technical progress. For other appliance, the occupant behavior should also be carefully considered by researchers and policy makers.

With the development of urbanization, the energy consumption of residential buildings is growing rapidly. Previous researches mainly focus on the daily profile of residential electricity consumption, while monthly electricity consumption profile is essential for the design and optimization of power system and energy storage system. With the advancement of smart meters as well as mass data storage and transfer techniques, the availability of building energy data is growing rapidly. Thus, data mining methods are becoming possible and effective in the analysis of monthly electricity consumption in residential buildings. This paper first reviews the current research of monthly energy consumption profiles in residential buildings, then proposes a new stochastic distribution method based on data-driven models. A case study of Jiangsu residential building electricity consumption is conducted to illustrate and verify the application of this method. Finally, this paper discussed the future promotion of this method and possible perspective of monthly energy profiles.

Transactive energy is a two-way exchange of energy between the electric power grid and a community's distributed energy resources, offering opportunities for efficiency improvements through market-based economic and control techniques. A community's distributed energy resources include electricity-producing resources and controllable loads. Increased usage of unsynchronized generation of non-dispatchable solar photovoltaic energy and household demand at the community level can adversely affect the power quality, reliability and network balancing of the electricity grid. A solution was developed in this paper in the form of energy storage and demand side management on a solar residential community. An agent-based transactive energy management system was developed and simulated using multiple prosumer houses with roof-top PV systems and local energy storage. Experimental work conducted on an archetype house, near Toronto, Ontario, Canada, was used to model an all-electric residential house and clusters were created with varying orientations and building properties to mimic different efficiency levels of the houses within the virtual community. A machine learning algorithm using historical data and weather forecasts from Natural Resources Canada (NRCan) was used to forecast the community's energy generation as well as building's thermal loads. In this community, consumers can curtail their loads based on price signals sent to smart devices in homes. Open-loop mixed integer linear programming technique (MILP) and model predicted control (MPC) were compared and evaluated. The simulation shows promising results with a 9% energy savings during the summer solstice day and 5% during the winter solstice day when compared to the normal operation of houses' mechanical equipment.

A well-designed mixed mode building allows natural ventilation when the outside weather conditions are favorable and deploys air-conditioning when natural ventilation is not able to provide sufficient comfort. In this study, a methodology is proposed to enable real time control of operable windows for mixed mode ventilation building. EnergyPlus is used for building energy simulations. A real-time simulation is performed using Building Controls Virtual Test Bed (BCVTB). In this methodology, AERIS Weather Data is used to forecast hourly weather parameters. Seasonal Autoregressive Integrated Moving Average (SARIMA) Models are used to model a day-ahead prediction for the lighting load, electric load and the occupancy profiles. Co-simulation of EnergyPlus is carried out with BCVTB to enable real-time simulation wherein; the EnergyPlus weather file parameters and input building loads are updated every hour. Based on the indoor and outdoor conditions, EnergyPlus calculates the schedule for opening/closing of windows. A simulation based case study for Hyderabad, India is performed to demonstrate the working of the proposed methodology. Reduction of 25% in cooling energy demand was estimated in a mixed mode building as compared to the fully air-conditioned building during the study period.

The predicted mean vote (PMV) index is taken as the control target in an air-conditioning system is in line with the requirements of the indoor thermal environment. In addition, with the emergence of "air conditioning disease", people began to pay more attention to the study on the dynamic thermal comfort of indoor thermal environment. Firstly, the dynamic PMV is proposed, and the amplitude and period of the dynamic PMV are confirmed by experiments and questionnaire surveys. Then, a simulation model of variable air volume (VAV) air-conditioning system based on dynamic PMV control is built by Transient System Simulation Program (TRNSYS). Simultaneously, the simulation models of the VAV air-conditioning system based on constant temperature control and static PMV control are also built by TRNSYS. The simulation results show that the comfort and energy saving of the VAV air-conditioning system based on dynamic PMV control are more prominent.

Occupational thermal comfort is one of the key performance indicators for green and sustainable buildings. Within air-conditioned indoor spaces, the deployment of air supplies play an importance role in determining thermal comfort conditions. This becomes more critical when the non-uniformity of heat loads in space increases. The objective in this study is to develop a set of systematic solution procedure for optimizing the locations of air supplies so as to maximize the thermal comfort conditions in a typical air-conditioned office environment. High-fidelity CFD simulations, corresponding to pre-defined locations of air supplies, are performed first, followed by surrogate-based optimization (SBO) process for the pursuit of the optimal location of the air supply. The thermal comfort index, predicted mean vote (PMV), is adopted as the objective function for optimization, which is evaluated at the people's sitting height level. Results real that the most appropriate location of the air supply has been successfully obtained using the proposed optimization algorithm and procedure. Efforts in this study imply that CFD can be extended further to optimize the building designs, with the help of cost-effective optimization approaches.

As China has entered the aging society, most of the buildings are concern to the use of elderly. When fire occurs in crowded places, the elderly casualties will take up larger proportion. However, current residential design code did not made special targeted requirements of this kind of buildings in construction standards and building design for there is a lack of elderly building security legal documents and data support. To solve this problem, it is considered the provisions of the building height restrictions from the perspective of construction safety in the revision process of Code for design of residential building for the aged. The purpose is from the angle of architecture and improves the elderly living safety to reduce fire evacuation process in risk. Furthermore, the building plane complexity and other internal factors will also become an important factor affecting the evacuation. This study focus on the tall residential buildings, several different numerical simulations are carried out to clarify the main influence factors of evacuation in elderly concentrated buildings and to provide data support for the architectural design and standard formulation.

Cooling of server is getting more attention these years, which directly influence the efficiency of data processing, storage, and telecommunication. In order to solve the hot issues of sever, a thermal simulation model was built. Finding that the hotspots were mainly concentrated in CPU and Northbridge chips. With regard to CPU, the structure optimization analysis of CPU heat pipe radiator was carried out without changing the volume of heat pipe radiator. The fin thickness and fins number of heat pipe radiator were optimized. The optimized radiator could reduce the CPU hotspot temperature by 5.3%-9.09%. With regard to North Bridge chip, a chip-level cooling method based on Peltier effect was proposed. The cooling performance of thermoelectric cooler was investigated by experiments, and the best working current under different wind speed and cooling load was explored. Compared with the original heat dissipation method (non-thermoelectric cooler), the thermoelectric cooler could improve the starting characteristics and response characteristics of heat dissipation radiator, and the added thermoelectric cooler could reduce the temperature rise of North Bridge chip by 4.45%-31.12%.

This study aims to improve the energy efficiency of heating, ventilation, and air-conditioning (HVAC) system in existing building by adding a thermal energy storage (TES) tank. By installing the TES tank with volume of 1 m3 in the chilled water loop of HVAC system. it can make charge/discharge surplus heat from heat source equipment. The chilled water can be delivered not only to secondary side but also to TES tank, while the required heat load is less than the rated capacity of the heat source equipment, it does not need to shrink its output and can be operated under the relatively higher load ratio without falling down efficiency. The charge/discharge progress is considered occurring within short-term less than an hour. During the discharge progress the heat source equipment can be turn off or idling operation yields reduce operation hour of heat source equipment and achieve energy-saving. In this paper, a case study is conducted to evaluate the energy efficiency improvement by adding TES tank into HVAC system using system energy simulation, coupling two-dimensional, steady-quasi TES numerical model that is verified by comparison with the measurement data. The error of the TES numerical model compared with the experiment was less than 5%. From the case study results, it is found that the TES tank can improve energy efficiency of HVAC system because of increasing the COP of the heat-source equipment reduces its energy consumption and reducing operation time of the primary chilled water pumps.

The possibility of introducing distributed energy system consisting of combining heat and power generation (CHP) for existing multi-family housing is discussed in order to make an academic ground for calling for the spread of distributed energy systems in existing multi-family houses. Case study was conducted to evaluate energy conservation effect of the distributed energy supply system and obtain the findings concerning on its feasibility. The case study was focusing on all municipal multi-family housing in Nagoya city, Japan, and it was evaluated based on primary energy consumption reduction, CO₂ emission reduction, simple pay-back period, and recurring expenses merit by introducing the system. Annual energy consumption was estimated for nine typical municipal multi-family houses with different average occupied floor area and number of dwelling for each individual building unit. Based on the results of the case study, it was found that the effect of the distributed system varies depending on the average occupied floor area and the number of residences, and the generator capacity of CHP. In addition, when assuming adapting a distributed energy supply system into a type of housing has occupied floor area of 30m²-50m² per a dwelling that accounts for 83.5% of the total municipal housing in Nagoya, at least the overall reduction of 16.7% CO₂ emission reduction rate could be expected.

Rural housing is an important part of residential buildings in China, which has large construction amount, high energy consumption and large potential for energy saving. Unreasonable building layout and poor thermal performance of building envelope are the main reasons for high energy consumption through field survey of rural housing in cold region. Based on computer-aided simulation, this study uses DesignBuilder to simulate the energy consumption of typical rural housing, and compares it with other energy consumption under different strategies of building layout and envelope. Energy-saving strategies of building layout and envelope suited for rural housing are obtained. The research has significant reference value to the energy-saving design of rural housing.

Ultra-low-energy buildings have attracted increasing attention particularly for ensuring a comfortable indoor climate in summer and in winter with ultra-low energy demand. To permit this, there are high requirements on various parameters such as building envelope structure, and emphasizes the importance of building energy-saving optimization design. However, most of the current optimization analysis of the influencing factors of the building load is based on actual buildings with fixed spatial factors. Few studies have comprehensively considered the influence of building envelope parameters and spatial factors on building load. Actually, different architectural spatial design factors such as length-width ratio, building standard layer area, floor height correspond to different analysis results. Therefore, this paper first analyzes the influence of architectural space design factors on building load. Based on this, the orthogonal test method is used to study the contribution rate of nine building envelope thermal parameters to building load changes. The study found that under the premise of different spatial design factors, the thermal parameters of the envelope structure have different effects on the building load. The results of this paper provide a basis for energy-saving design and development of ultra-low-energy buildings in hot summer and cold winter regions.

This study aims to verify energy saving effects of an ERV system on the EHP energy consumption in a classroom. Simulations were carried out by TRNSYS, of which classrooms are equipped with EHP and ERV, which is a typical classroom heating system in Korea. The system performance models are proposed using an optimized method, and they are used for simulations. Results show that the energy saving rates of the ERV on Monday and in the early hours become lower since the classroom remains unheated during the weekend and night time. From the work, it can be concluded that the energy saving rates of the ERV are lower for buildings with lower occupancy rates.

Energy consumption for house heating in winter accounts for a large proportion of building energy consumption in rural buildings in western China. It is an alternative method to make full use of renewable energy for heating houses to save energy and cost. A solar assisted geothermal heat pump with phase change material heat storage tank (SAGHP-PCM) demo heating system in a rural building in Xi'an China was built up and the dynamic performance of the SAGHP-PCM heating system was simulated in different control strategies. The results show that PCM module can improve the heating effects, moreover, optimized control strategy selected by comparison can bring a better operation way and save electric energy by using solar energy as whole energy source for heating in 753 hours, and the heating performance is acceptable meanwhile. The simulated average temperature of the optimized system is 17.62°C and the guarantee hours is 3379 h when taking 16°C as qualified indoor temperature.

Besides meeting the cooling demands of each terminal space in a high-rise building, the smart operation of a central chilled water system is also aiming at saving more electricity. Hence, it is the key issue to distribute proper amount of chilled water to each room according to its cooling load variations, i.e. achieve hydraulic balance in the chilled water network. To save electricity consumption of both chillers and circulation pumps in operation, in this paper, a supervisory optimization model is proposed for a general chilled water system. An improved node method is also presented to simulate the hydraulic behavior of the general chilled water pipe network, which is particularly adapted for a high-rise building with faster computation speed and fine accuracy. Then the proposed model is validated in a real high-rise hotel in Shanghai. In the case study, comparing with conventional operation method (On/Off or PID control), the proposed smart operation method can save 15.4-29.3% of electricity for the chilled water system in the typical days of cooling season.

As the major electricity consumers worldwide, buildings can play an important role for power balance of smart grid through demand response (DR). Demand side-based control and supply side-based control are two typical types of DR measures when using centralized building air-conditioning systems for DR. For demand side-based control, the major disadvantage is that the response speed is generally too slow to allow buildings providing an immediate power reduction for the smart grid. For supply side-based control, the response speed is fast enough while it may cause control disorder to the whole system and uneven indoor temperature increase among different zones. In order to overcome above disadvantages, we proposed a novel DR method for building air-conditioning systems, which combines both the demand side-based and supply side-based control simultaneously. It consists of two major steps. First, some running chillers will be shut down to provide an immediate power reduction once urgent power reduction requests from smart grids are received by buildings. Second, the indoor air temperature set-points will be adjusted stepwise based on an "incremental schedule" to achieve a uniformly indoor temperature rise among all concerned zones/rooms. By implementing such two steps, an immediate power reduction is achieved while minimizing the uneven sacrifice of thermal comfort among different occupants. Two new performance indexes are proposed to evaluate the thermal comfort performance of DR methods. The proposed DR method is implemented and tested as case study in a virtual building dynamically simulated by TRNSYS. Five scenarios with different incremental steps for adjusting the temperature set-points are compared to determine the optimum "incremental schedule". Results show that buildings can provide immediate power reduction and achieve a small and even thermal comfort sacrifice by implementing the proposed compound DR method.

This study examines the influence of building form – comprised of plan shape and roof slope – on the net annual energy performance of solar net-zero energy (NZE) buildings. The renewable energy system used is the building-integrated photovoltaics with thermal heat recovery (BIPVT). BIPVT is a relatively new enhancement of the building-integrated photovoltaics (BIPV) system which others have studied for the effects of building form on building energy demand and energy generation. Previous sensitivity analyses of building form have typically not considered BIPV or BIPVT. When they have, it has been limited to simple, prismatic forms; it is unclear how more complex or compound building forms impact building energy demand and BIPVT generation. Therefore this study analyzes the relationship between building form and BIPVT performance to provide guidance for medium-sized NZE commercial and institutional building design at the early design stage. The main input parameters are the building form: compound or complex plan shapes, and BIPVT roof slope. Also included are: building orientation, window to wall ratio (WWR), and U-value. These parameters are evaluated in a heating dominated climate to determine the parameters sensitive to the net energy demand – the balance between annual energy loads including heating/cooling energy demand and PV electricity generation and useful thermal heat recovery. A customized BIPVT model is used in TRNSYS simulations. A variance-based ANOVA global sensitivity analysis method is used for both main and interaction effects. Results show that each of the form variations studied is able to reach NZE using different combinations of input values. The most sensitive input parameters for the NZE output target are the BIPVT roof tilt angle, the azimuth, WWR (South), plan shape, and WWR (North). Each one is quantified. This information may provide building designers guidance at the early design stage.

This paper uses the improved green CTTC model to explore the selection method of background temperature for long-term continuous calculation. A new method to determine the background temperature is proposed, and the feasibility of the method is verified by tested. This method not only improves the prediction accuracy of the model due to external meteorological factors, but also applies to long-term continuous calculations of one week or more. The consistency index d = 0.991, RMSE = 1.272°C, absolute error maximum = 5.6°C, relative error maximum 23.8%. 0.2°C ∼1.4°C is improved compared to the original calculation model.

Water source heat pump (WSHP) systems are widely used for cooling and heating due to high efficiency. Accurate modeling of water source heat pump systems is the basis for performance prediction, design and control optimization. However, various uncertainties exist in the simulation and affect the simulation results, which can be categorized into parameter uncertainties and model form uncertainties. Without considering these uncertainties, the performance of water source heat pump systems would be overestimated or underestimated and then affect the decision of stakeholders. The models of heat pumps are especially important for accurate simulation. This paper therefore attempts to quantify the uncertainty of heat pump models and associated impacts on the energy performance of water source heat pump systems. Based on the experiment data of a heat pump, 13 models of heat pumps are examined. The energy performance of the system considering uncertainties in the heat pump model can also be obtained. Results show that the uncertainty in heat pump models can result in a deviation of around 30.55% in the energy consumption. The energy saving potential of WSHP systems can vary between 28.04% to 48.22%. It demonstrates that the uncertainties in models affect the system performance significantly. It is therefore highly recommended to take the uncertainty of heat pump models into account in building energy prediction and design optimization.

Clustering has become a very popular machine learning technique for identifying groups of data points with common features in a set of data points. In several applications, there is a need to explain the clusters so that the user can understand the underlying commonalities. One such application is in the area of building energy simulation. There is a need to cluster solutions obtained by parametric energy simulation runs and explain the characteristics of each cluster for human consumption. This paper demonstrates how the axis-aligned hyper-rectangles based clustering, on building energy simulation data, can help identify clusters and describe the governing rules for each cluster. We are calling these rules design strategies. Instead of the distance-based clustering methods that are unable to extract simple rules from the underlying commonalities in each cluster, this method is able to overcome this limitation. This method is applied to identify design strategies from a parametric run of a simple five-zone rectangular building model. Based on a user-given threshold, low energy solutions are selected for clustering. Each axis-aligned hyper-rectangle cluster is a unique design strategy that can be easily communicated to the user.

Forecasting energy consumption enables users to plan their resource utilization optimally. For this, it is essential to make reliable forecasting of consumption profile in real-time which is very challenging and still emerging. In this study, we focus on forecasting HVAC cooling energy consumption at sub-hourly forecasting horizon which enables us to analyze and control the demand in real-time. With the aid of energy meters and adaptation of BACnet technology in the target building, we collected real building cooling energy consumption data and HVAC systems usage at a higher resolution. In this methodology, weather data from Weather Underground of Gachibowli, Hyderabad location has been used. These recorded weather parameters are being used as explanatory variables. Along with the weather parameters, many other feature-engineered explanatory variables which are discussed in the paper has been used to capture the trend and variation of energy consumption. Required pre-processing and data analysis is performed on the raw data to obtain meaningful information for modeling. We have implemented one-step ahead static forecasting using Gradient Boosting Regression Trees (GBRT), where we forecast for single-time-step ahead in each iteration then update the training data at the end of each iteration with actual data available next time-step in order to assess how well the model forecasts one-step-ahead. Our results show that we could improve forecast accuracy by almost 45% by including feature engineered variables. We achieved a Mean Absolute Percentage Error (MAPE) of 14.7% with GBRT.

Since a heat source system that produces and conveys the heat for air conditioning comprises various devices, and has complex controls, faults that impair performance occur. Heat source systems are customized, however, and are complicated to the extent that a 'one-fits-all' approach to fault detection and diagnosis (FDD) has not been established. Here we propose a novel method for FDD, using a fault database generated by a simulation, and using convolutional neural networks (CNNs) trained by the database. A real system, with a water thermal storage tank, was the object of this research. Firstly, system behaviors in response to faults were calculated, using a detailed simulation, and then a database was generated, using the simulation results with fault labels. There were 16 fault types in total, which included a condition without faults, four types of faults, and their combinations. The assumed four types of faults: were chiller deterioration by condenser fouling, improper sewage pump set value, heat exchanger fouling, and temperature sensor error at the supply side of the heat exchanger. Then, we preprocessed the database, and converted the data into images, with two axes of time series, and with items from one 24-hour data set as a representative image. Then, CNNs were trained by the database, and trained CNNs were tasked with the diagnosis of real data. The CNNs performed with 98.7% accuracy in training, and diagnosed the real data using probabilities. We reviewed the analysis of the real data, where the probability indicated the likely presence of a fault, and how the real data was similar to the fault severity assumed in the simulation. We concluded that this FDD method will help analyze real data, because it indicates faults emerging in the real data with probability, whereas conventional data analysis requires checking the data using expert knowledge.

This study aims to evaluate an optimal operation control scheme for a radiant floor heating system in a residential building to maintain a desired room temperature. Radiant floor heating systems frequently cause overheating—exceeding the set temperature—due to the heat capacity of the flooring material. To mitigate this problem, an optimal operation control scheme is proposed to determine the optimal set temperature for each room. To evaluate the suggested optimal operation scheme, experiments were conducted on a living test bed—two bedrooms. In Bedroom 1, three operation periods with the suggested operation control were implemented and in Bedroom 2, three operation periods with the optimal operation control were implemented, reducing overheating from 4.0 °C to 0.0 °C and 4.5 °C to 0.5 °C, respectively.

Prediction and optimization of energy consumption is valuable to recognize the status and assist in green campus retrofitting and energy efficiency making. The study focused retrofit strategies in subtropical Guangzhou to achieve energy efficiency in a higher educational campus. According to the building's envelope features, optimization using a pseudo orthogonal test based on assumption of window design. In this paper, field investigation and numerical simulation were used to assess the thermal performance of this building. The prediction was primarily verified using a numerical simulation with 16 cases. It was concluded: (1) on basic cases, the results revealed the methods' reliability based on Energy-plus is adopted in the green campus; (2) the retrofit cases in thermal performance considering the building envelop, solar shading and windows' glazing; (3) the rooms of divergent orientation play varied significant role in energy consumption. The study provided the technic support for the energy optimization strategies of campus building in hot humid area.

A comfortable learning and teaching environment is one of the key concerns in the design of school buildings. In Singapore public school buildings, most of classrooms are naturally ventilated, for the sake of energy saving and sustainable design. It is necessary to study the impact of environmental conditions and design features to get some clues to facilitate the designers for naturally ventilated school designs. In this study, CFD simulations have been carried out to evaluate the natural ventilation condition of the classrooms and identify the plausible reasons causing thermal discomfort for an actual school in Singapore. The CFD approach adopted in this study is closely in reference to the CFD methodology outlined in Green Mark 2015 for Non Residential Building from Building and Construction Authority (BCA), subject to the four prevailing wind conditions available in Singapore. Meanwhile, some mitigation measures including the removal of incline roofs have been explored in order to enhance the natural ventilation for those classrooms. In addition, thermal comfort analyses have been performed with simulations including ceiling fans and heat loads. CFD simulations demonstrate that classrooms at higher levels experience weaker cross ventilation than those at lower levels for the three prevailing wind conditions from the north, northeast and south, respectively. This may due mainly to the fact that the school resides within the wake zone of the surrounding buildings. The flow directions across the classrooms of concern are found to be opposite to the prevailing wind direction under the three prevailing wind conditions. Thermally uncomfortable conditions in the classrooms at higher levels are well simulated and captured using the proposed thermal comfort analyses. All the observations match well with the feedback from the school. Besides, scenario-based studies with regard to plausible mitigation measures have shed the lights towards enhanced natural ventilation across the classrooms of the school of concern.

Traditional HVAC design process contains a large amount of time-consuming work such as load calculation for each space, hydraulic calculation to determine duct size and careful duct layout arrangement to avoid collision. Computer is more suitable for such kind of "dumb" work with higher efficiency and less fault. Also present building design work is a less integrated process where engineers of each domain focus on their own work. This often result in unconformity and poor quality with limited project time. IFC is a neutral platform, open file format specification to facilitate interoperability in the architecture, engineering and construction. In this paper, we propose a general framework of an IFC based integrated semi-automated design tool for central HVAC system design. It contains four main modules corresponding to specific design procedures. Human is allowed to make decision during the design process for more flexibility.

Due to the low efficiency and frosting of the air source heat pump (ASHP) in extreme cold climates, the use of existing solar water heaters or dedicated solar collectors as auxiliary heat sources can further improve the overall operating efficiency of ASHPs. Based on the case study of a typical rural building in Shandong, the simulation models of the solar-air source heat pump (SASHP) systems connected respectively in series and in parallel have been established under the TRNSYS platform. The operating performance and the solar fraction of the two systems have been simulated under different conditions. The results show that the performance of the parallel SASHP system is higher than that of the series SASHP system. The research results can provide certain guideline for the clean heating in rural areas of Shandong province in China.

Compared with traditional air-conditioning systems which aim at maintaining the designed indoor air temperature and humidity, radiant panels are capable to improve the human thermal comfort through the direct radiant heat transfer with occupants. Based on the Fanger's thermal comfort model, the simplified PMV (Predicted Mean Vote) model and calculation equation of cooling load are established. This paper analyzes the relationship between the human thermal comfort and indoor sensible cooling load, and explores the design and operation methods of indoor parameters. The model room with typical boundary conditions in the hot-summer and cold-winter zone of China is simulated and analyzed by Airpak. The widely accepted PMV and PPD (Predicted Percentage of Dissatisfied) indices are adopted to evaluate the indoor human thermal comfort. The parameters including the radiant surface temperature, the air supply temperature, the relative humidity and the ratio of the radiant surface areas are researched. The optimum indoor parameters in typical summer conditions are finally obtained, it is expected to provide a relevant reference for the design and operation methods subject to the radiant panel combined with fresh air system.

We developed natural ventilation simulation tool to provide an integration of BIM and CFD simulation in one simple, time efficient and cost effective solution. There are three main working procedures in this GrBEST developmental work. Firstly, we work with an Architect to prepare a clean BIM-REVIT model (IFC output) for GrBEST flow solver. A modelling protocol for REVIT base geometry creation was developed to help create a clean BIM-REVIT model (IFC output), allowing for seamless conversion algorithm to convert the primitive REVIT IFC file for GrBest flow solver. Secondly, a unique geometry handling tool to perform BIM conversion to CFD input file has also been developed. It involves the development of a new triangular mesh repair solution that automatically rectifies common geometrical and topological errors that are inherent in the processes of CAD modelling and simulation. Finally, we use an in-house CFD code and customize it for building ventilation simulation. GrBEST Flow Solver consists of UNIX executable modules to conduct meshing and incompressible CFD computation activities. Solver enhancement with immersed boundary method for building geometry adaptation has also been developed. This GrBEST software could promote building designers and architects to implement good natural ventilation strategies during conceptual planning and master design stage, and therefore resulting in larger impact towards urban sustainability effort in new town development.

Radiant cooling and displacement ventilation system has an extensive application in large space building where there has a significant stratification of heat and mass. This paper focuses on the effects of the floor cooling proportion on the indoor comfort under radiant cooling and displacement ventilation system in large space. By simplifying the building model according to a practical waiting hall in certain railway station, a three-dimensional space model describing the comfort distribution characteristics in working area with composite system is presented. The discrete ordinates radiation model and indoor zero equation model are used to describe the indoor temperature and humidity distribution law. Floor temperature, inlet parameters and the indoor comfort control conditions are researched. The indoor thermal and moist environment is analyzed based on CFD simulation. The simulation results provide that the temperature and velocity of supply air had similar influencing characteristic on the indoor comfort. Meanwhile, the cooling capacity of floor could be higher when the supply air temperature was higher and the air supply velocity was lower and the optimum cooling proportion of floor was 0.76 to 0.77 in this paper. More importantly, the compound system could be applicable in indoor comfort control in large space.

This paper aims to share about the recent development on the performance-driven and scientific-based CFD quality control and framework in order to assess the naturally ventilated building designs in Singapore. The topic is an essential component for Green Mark 2015 Schemes, recently advocated by Building & Construction Authority (BCA), Singapore, for the sake of green and sustainable building designs. It covers six (6) different types of NRB buildings, namely with regard to industrial facilities, healthcare facilities, commercial atriums, hawker centres, sports facilities, and schools. A comprehensive quality control checklist is also developed to ensure the quality and accuracy of the simulation results. In addition to the regulations from respective building stakeholders, the adopted parameters also take reference from internationally accepted standards and/or peer reviewed literatures. This CFD methodology development can help to supplement limited guideline on natural/passive ventilation for the building code of practice in Singapore. Finally, based on the efforts in this project, we will summarize the potential research topics that may require further collaboration with building practitioners, e.g. pilot scale study on certain building type and good modelling approach/tool to support both building designers and policy makers.

With the increasing penetration of technologies, building automation systems (BASs) are capable of managing building operational performance in an efficient way. Meanwhile, BAS has accumulated a large amount of data during the building lifecycle. Data quality issues have become increasingly important, which affect the effectiveness and accuracy of energy big data analytics. In this paper, we study the data quality of electric consumption of a building energy management platform in a developing city of China. An overview of the selected building energy management platform is presented, and the electric sub-metering system is then illustrated. The data quality issues of electric consumption are divided into three aspects, namely item number of data, missing sub-items of data and the efficiency of data. After conducting a detailed discussion on these aspects, we discover a common and severe issue that many duplicate items and fuzzy-classification items exist in the data. The practical guidance for building energy management platform, which may help the platform operate effectively, is given based on the analysis.

There are many problems with the present centralized energy systems. With the advancement of distributed energy systems and the advancement of renewable energy technologies, the supply of electricity and heat will be gradually decentralized, forming the Energy Internet combined with information technology that makes energy transactions easier and more efficient. In this research, a bidding mechanism of peer to peer electricity system is proposed for supplier nodes and consumer nodes to sell or buy energy on the market. And computer simulation is applied to test and optimize the mechanism. The results indicate that the proposed mechanism conforms to the market regularity and can improve the efficiency of local energy utilization compared with the traditional centralized system, reduce the cost of consumers, propel the utilization of renewable energy, and make the market more flexible and transparent.

The number of buildings that adopt the multiple split-system air conditioners is increasing, especially for small and medium-sized buildings. Many researches have been done on the energy consumption performance of the multiple split-system, but there are still many unclear points about its actual performance, in particularly, with regard to performance under partial load condition. It is important to understand the partial load performance and set the reliable performance characteristics when we perform building energy simulation because it will have a significant influence on annual energy consumption of the system. In order to clarify the efficiency under partial load condition, we have analysed the measurement data of actual buildings and found that there is a range of the efficiency even at the same load ratio. We assume that the cause of this range is due to bias (unbalance) in the heat amount handled by multiple indoor units. The efficiency tends to be higher when the heat amount of all indoor units of the system are equal, which is same as the test condition specified by ISO 15042:2017, but the efficiency tends to be lower when the heat amount handled by the indoor units is highly unbalanced. This research clarifies the influence of the unbalanced heat load to the system energy efficiency. We measured fundamental data on the energy efficiency of the multiple split-system air-conditioner in an experimental facility that connects multiple constant temperature and humidity chambers. We found that the unbalanced load operation caused about 20% energy loss in maximum and concluded that the indoor units should be arranged so that extreme unbalanced heat load does not occur.

This paper presents a framework for the development of early-design guidance to inform architects and policy-makers using parametric whole-building energy simulation. The emphasis of the study was to identify and assess the benefit of energy efficiency alternatives primarily focused on the building's thermal envelope. The energy efficiency alternatives included performance adjustments to the external glazing, wall, roof, floor properties. The Result indicated the glazing selection should look to achieve the highest thermal resistance (R-value) and best solar control (lowest shading co-efficient value) within budget. Ideally a solar control low-e IGU system could be installed. Solar control glazing also reduced the required development cooling capacity by ∼17%.

Coal is still the main energy of space heating in North rural areas in China, and coal stove, coal fired boiler are most common heating technology through literature analysis of North rural areas heating status. With the development of clean energy heating in rural areas, solar heating gets people's attention. In 2016, through investigating 15 solar heating projects in North rural areas, we find that all rural solar heating is household heating, due to factors such as collector installation, heat storage technology, operation and maintenance, solar household heating has not been accepted by rural residents. But large scale solar assisted ground source heat pump district heating technology (SAGSHP) is popularized, one successful case is Xiaowangjiapu village project, we measured operation factors of this system, including indoor air temperature, relative humidity, heating demand etc. And setting up software simulation model by using TRNSYS 18.0. Taking the measured outdoor meteorological parameters and heating demand as software input parameters, by contrast to model output parameters of heat pump and test data, checking the software model. And then analyze the performance of the system for the whole year. Simulation results show that average storage temperature of soil decreases from 12.80°C to 12.54 °C, solar fraction (SF) is just 17.6%. Based on the experience of European cases, the reason for small SF is no preheat of soil and loss of soil heat dissipation.

The construction techniques and construction methods of traditional stilted dwellings are facing the danger of being lost. This paper proposes a parameterization method of stilted dwellings taking the digital construction of stilted dwellings as the starting point to improve the parameterization process of the original stilted dwellings, expanding the construction logic of shape grammar and combining with the multi-objective optimization algorithm. This method takes topography and land range as external constraints, takes economic technical index and total construction cost as optimization objective, also takes building type, floor number and room area ratio as parametric variable. Then using genetic algorithm for multi-objective optimization. Comparing with the original generation method, new method can match a given condition to a suitable form. By changing the original design mode "users demand–design digital model-adjusting size–layout model" to "Input condition– computer generating model – multi objective optimization –layout model and indicator", the design process is systematized and the evaluation system is discussed. It provides a design tool for the architects to intervene in the rural construction and also makes the design of stilted dwellings easier.

The cross-corrugated triangular ducts are suitable for plate heat exchanger because of its high heat transfer capability and strong mechanical strength. In this numerical study, a SST k-ω model is used, 6 different cases for installing different baffles in the cross-corrugated triangular ducts are involved. The frict ional resistance and heat transfer coefficient in the 1000-6000 range of Reynolds number are studied, the influence of baffle on flow-pattern and temperature distribution are analyzed. Combined with the comprehensive heat trans fer index, a good improvement plan was proposed. The results show that baffle can effectively increase the heat transfer area, change the mainstream direction, enhance the fluid disturbance, and enhance the heat transfer. In addition, case 6 is the best enhanced heat transfer scheme. Compared with the case without the baffle, the Nu of case 6 is 1.5-1.6 t imes that of the original duct, and the heat transfer efficiency can be increased by 13% under the same fan power. It is a feasible choice to set up baffles in the middle and lower part of the upstream channel of the cross-corrugated triangular plate flow channel.