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Daytime subambient radiative cooling is a most promising alternative to electricity-free building cooling. However, optical performance degradation arising from surface contamination and inevitable parasitic heat gain still pose unprecedented challenges to cool building at subambient temperatures. This paper proposed a superhydrophobic cellulose aerogel cooler (SHB-CAC) as building envelope by integrating self-cleaning capacity, passive daytime radiative cooling and thermal insulation to reduce environmental heat gain. The SHB-CAC demonstrates high solar reflectance (93%) and long-wave infrared emittance (91%), accomplishing a temperature drop of 8.5 °C lower than the ambient under sunlight of 800 W/m2 in the outdoor experiment. Notably, the SHB-CAC possesses low thermal conductivity (28 mW/(m∙K)) that suppresses parasitic heat gain from warmer surrounding and reduces cooling energy consumption. The self-cleaning property resulting from superhydrophobicity protects SHB-CAC from water wetting and dust contamination but also maintains its good surface radiation capacities under different humidity environment. A building energy simulation was conducted and results showed that 43.4% of cooling energy on average could be saved compared to the building baseline consumption, if SHB-CAC was widely used in China, indicating that the strategy of optical and thermal conductivity management of cooler has the potential to reduce the energy consumption of buildings. [Display omitted] • Waste paper is converted into aerogel cooler for building cooling. • High R solar and ε IR , thermal insulation, and self-clean are achieved in one design. • The aerogel achieves a high sub-ambient temperature drop of ∼8.5 °C on daytime. • The aerogel shows that 43.4% of cooling energy could be saved. [ABSTRACT FROM AUTHOR]

In the rural areas of Northwest China, the utilization of clean and renewable energy is deemed a crucial measure for reducing building energy consumption and environmental pollutant emissions. This paper focuses on constructing a simulation platform for a solar-assisted air source heat pump heating system. A rural residential building in Yongshou County, Shaanxi Province, serves as an illustrative example. A novel flexible temperature control method with a feedback controller in sub-area and period is proposed in this paper, alongside the selection of three distinct objective functions aimed at optimizing the heating system. The simulation results indicate an average temperature of 17.0 °C throughout the heating cycle, with a peak temperature of 18.7 °C. Moreover, the solar fraction is measured at 25.11%, underscoring the significance of collector area and heat storage tank volume as primary factors in system design. The results also demonstrate that across various optimization objectives, the life cycle cost optimization scheme yields greater economic benefits, while the target building unit heating cost optimization scheme boasts the shortest static payback period and lowest unit heating cost. Conversely, the solar fraction optimization scheme stands out for its superior environmental benefits. These findings offer valuable insights for the design of heating systems tailored to diverse objectives. [ABSTRACT FROM AUTHOR]

Ensuring optimal building performance is vital for enhancing student activity comfort and fostering energy-saving initiatives toward low-carbon objectives. This paper focuses on university student centers in China, aiming to diminish building energy consumption while enhancing indoor thermal comfort. Parametric modeling of typical cases is executed using the Grasshopper 1.0.0007 software package, and the simulation of building energy consumption and indoor thermal comfort relies on the Ladybug and Honeybee plug-in. Employing a multi-objective optimization design method and the Octopus multi-objective optimization algorithm, this study integrates numerical simulations and on-site surveys to analyze how factors like building form, orientation, envelope structure, and others impact the indoor and outdoor environment. A comprehensive optimization design approach is implemented for the building's exterior components, including the walls, windows, roof, and shading system. After conducting a comparative analysis of the annual comprehensive energy consumption and indoor thermal comfort before and after the optimization plan, it is determined that implementing these measures reduces the annual comprehensive energy consumption of the building under study by 58.8% and extends the duration of indoor thermal comfort by 53.0%. This study presents a practical optimization design methodology for university student center architecture in China, aiding architects in decision making and advocating for energy-efficient building designs. [ABSTRACT FROM AUTHOR]

The demand for energy in factories is huge. With abundant energy supply, factories can raise their production capacity to a new height. Energy is the material basis of domestic economic development. As the largest developing country in the world, energy shortage has become an urgent problem for China. In this paper, an Internet of Things based on big data ecosystem is proposed to analyze the energy consumption of the factory and build a model. The Internet of Things technology of big data ecosystem can be summarized as a technology that uses information sensing devices to complete the transaction and network connection according to the protocol content. A total of 853,000 power distribution operations were carried out in the power grid. In 2019, the average ratio of decision tree algorithm, machine learning algorithm, and machine learning algorithm was 36.8%, 37.4%, and 43.5%, respectively. Compared with the three methods, the method in this paper increased by 37.9% year-on-year and reduced the power outage by 2.63 million households, which is equivalent to a corresponding reduction of 35 users per operation. The functional requirements of the IoT energy consumption analysis system in factories based on big data ecosystem are reflected in three aspects: energy consumption monitoring and management, power control and management, and energy consumption supervision and analysis. Based on the management of energy consumption monitoring and power control through the software platform, the functional requirements of the system are analyzed. [ABSTRACT FROM AUTHOR]

An analytical hierarchy model of the impact of solar reflectance, thermal emittance, heat transfer coefficient, and heat storage coefficient on building energy consumption was established through the implementation of orthogonal design experiments. The EnergyPlus software (v9.0.1) was utilized to simulate building energy consumption across diverse climatic regions in China, providing essential benchmarks for the orthogonal design. The results of the range analysis consistently indicate that, barring regions characterized by extremely cold climates, solar reflectance emerges as the predominant factor exerting an influence on building energy consumption. As geographical latitude increases, the impact of the heat transfer coefficient becomes progressively larger, while the weight of thermal reflectance concurrently diminishes. Drawing upon the principles rooted in the gradient refractive rate theory and the concept of atmospheric window radiation, a range of high-reflectance and high-emittance cool roof coatings in various colors were meticulously developed. A spectrophotometer was employed to precisely quantify their reflectance properties, and simulations were subsequently conducted to scrutinize their energy-saving characteristics. The results demonstrate that the cool roof coatings that were developed using the methodology described in this paper exhibit substantial enhancements in reflectance, with increases of 0.24, 0.25, 0.37, and 0.35 for the yellow, red, blue, and green cool roofing materials, respectively, in comparison to conventional colored coatings. Under typical summer conditions, these enhancements translate to significant reductions in roof temperatures, ranging from 9.4 °C to 14.0 °C. Moreover, the simulations exploring the cooling loads for the roofs of differing colors consistently revealed remarkable energy savings. These savings were quantified to be 4.1%, 3.9%, 5.5%, and 5.4%, respectively, when compared to conventional coatings of the corresponding colors. These findings offer valuable insights into strategies for optimizing the energy efficiency of buildings through the application of high-reflectance cool roofing materials. [ABSTRACT FROM AUTHOR]

China's Hot Summer and Cold Winter zone, with a 550 million population, accounts for 45% of China's building energy consumption; as such, building retrofits could offer substantial energy savings. This paper presents results from a dynamic thermal modeling study of a typical urban multistory residential building under three types of air conditioning (A/C) operating schedules. Seven energy-saving retrofit measures (external wall insulation, roof insulation, double-glazing, air infiltration control, window shading, communal staircase design, and energy-efficient A/C) were evaluated, and the retrofit strategy with the highest annual energy savings and lowest thermal discomfort was identified. This retrofit strategy was subsequently evaluated for other flats (apartments) with different orientations and positions in the typical building. The annual space-conditioning energy could be reduced by 59%–68%, depending on the flat location, orientation and A/C operating schedule. The findings were then scaled up to estimate the potential energy savings in the city of Chongqing. More than 320 multistory residential buildings were represented by 12 archetypes. Space-conditioning energy consumption was reduced by up to 58% (18.8 TWh). This work provides evidence of the potential energy savings of city-scale retrofit that could aid China in reducing building energy consumption and achieving net-zero carbon emissions by 2050. It was possible to explore a wide range of refurbishment options for China's highly energy-consuming Hot Summer and Cold Winter zone with hot, humid summers and mild, chilly winters using dynamic thermal models. The simulation models developed in this paper revealed that double-glazing with air infiltration control is the most effective retrofit measure for middle-floor flats, but for top-floor flats, roof insulation is the most effective; south-facing flats consume more high energy consumption than north-facing flats. Furthermore, high-rise buildings consume less energy than low-rise buildings per square meter, and one-bedroom flats consume more energy than three-bedroom flats per square meter. This study also demonstrated the procedure to develop thermal comfort evaluation methods, A/C operating schedules, and construction parameters from literature in this climate zone when there were no standards or databases available. Findings offer a tangible, clear retrofit strategy that considers different A/C operating schedules, flat locations, and building archetypes. It can assist decision-making by practitioners and homeowners aiming to upgrade the building stock of this climate zone which covers 3.4 billion m2 with a 550 million population to reduce energy consumption and improve occupant comfort. [ABSTRACT FROM AUTHOR]

"Carbon neutrality" refers to the total amount of carbon dioxide or greenhouse gas emissions directly or indirectly produced by a country, business, product, activity or individual over a period of time. Through afforestation, energy saving and emission reduction, etc., to offset the carbon dioxide or greenhouse gas emissions generated by itself, to achieve positive and negative offset, to achieve relative "zero emissions", which belongs to the same term as "carbon peaking" in energy saving and emission reduction. "Carbon" means carbon dioxide, and "neutralization" means a positive and negative balance. The carbon dioxide or greenhouse gas emitted is offset by afforestation, energy saving and emission reduction, which is called "carbon neutrality". Goal decomposition is the process of gradually completing the overall goal according to multiple fields to form a goal system. Target decomposition should be carried out according to the principle of integration and integration. That is, the overall goal is decomposed into sub-goals of different levels and departments, and the synthesis of each sub-goal reflects the overall goal and ensures the realization of the overall goal. This paper aims to study the decomposition of building carbon neutrality goals to sustainable energy development strategies, combining energy conservation and emission reduction with the building industry to reduce environmental pollution and energy waste. Based on the theory of sustainable development, combined with the development characteristics of China's new energy industry, this paper makes a theoretical analysis of the sustainable development of the new energy industry from the three systems of economy, society and ecology. Using the new growth theory and the dissipative structure theory, the restricting effect of the depletion of basic energy on economic development and the influence on the alternation of industrial structure are discussed. The experimental results of this paper show that the building energy consumption intensity will reach 1.43tC/10,000 yuan, 1.25tC/10,000 yuan in the ideal scenario, and 1.1tC/10,000 yuan in the low-carbon scenario. [ABSTRACT FROM AUTHOR]

Urban planning and design, with the objectives of energy efficiency and climate adaptation, is receiving more and more attention as urban energy consumption keeps rising. As technical representatives with large spans and high difficulties, sports stadia have a broad range of energy conservation and emission reduction compared with traditional buildings and have an extremely close relationship with the energy consumption of the building environment and urban microclimate, so it is necessary to study the climate adaptation design strategy of sports stadia. However, climate adaptive design has not given much thought to sports stadia nowadays. And the energy-saving strategies of sports stadia rely mostly on engineering expertise without taking into account the effect of sports stadia layout, shape, and structure on the urban microclimate. This paper investigates the energy-saving and climate-adaptive design techniques of sports stadia in the hot summer and cold winter zone of China using the layout of sports stadia as the research object. Firstly, we construct a climate adaptive design framework of sports stadia of "layout-shape-structure" based on the characteristics of sports stadia. Secondly, combined with typical examples of large-scale sports stadia in hot summers and cold winters, we establish an abstract model of architectural layout, shape, and structure based on climatic environment. In order to provide climate-adaptive design methods for sports stadia in hot summer and cold winter zones, the ventilation of the external and internal spaces of sports stadia is simulated, quantified, and compared using CFD software. The study's findings suggest that the layout of sports stadia should take into account the direction of the local wind, that the goal of low energy consumption should guide the choice of building form, and that the internal wind and temperature environment should be stabilized during construction. The study's findings can serve as a guide for comparable designs that aim to construct sports stadia with reduced carbon footprints. [ABSTRACT FROM AUTHOR]

In tropical areas of China, energy saving is an important part of architectural design, and the energy-saving potential of residential buildings has attracted extensive attention. This paper studies the daylighting, ventilation, and building energy consumption in tropical areas to find out the best energy-saving performance parameters. The building model is established by grasshopper, and the parameters of daylighting, ventilation performance and cooling load are simulated. The octopus plug-in in grasshopper is used to calculate the target value iteratively, so as to find the relative optimal value of multiobjective. Finally, the optimized design value is compared with the initial value. The results show that the refrigeration energy consumption is greatly reduced from 188.20 kwh/m2 to 163.02 kwh/m2, the Daylight Autonomy (DLA) is reduced from 60.71% to 58.56%, and the ventilation wind speed is increased from 0.62 to 0.63 m/s. It can be seen from the results that although the daylighting objectives was reduced, the cooling energy consumption is greatly reduced, and the optimized daylighting layout is more balanced and reasonable. Therefore, on the basis of reasonable layout, this optimization study effectively reduces the refrigeration energy consumption and achieves the goal of green energy saving. [ABSTRACT FROM AUTHOR]

The energy consumption of office buildings has increased sharply since the 21st century with the increasing urbanization coverage. At this stage, the energy consumption of office buildings in China mainly comes from air conditioning and lighting. This paper obtains the regression equation of natural lighting illumination and radiant heat gain under different curtain conditions through experiments and simulations, and gives the theoretical calculation process of curtain regulation of office thermal and light environment and energy consumption. DeST and Ecotect software were used to analyze the thermal and light environment and energy consumption of the office. The results show that setting curtains in the room can effectively improve the indoor thermal light environment, the higher the transmittance of curtains the lower the lighting energy consumption, the higher the number of high temperature hours of natural room temperature and the greater the radiant heat gain. The room with thick curtains has the lowest energy consumption for air conditioning in summer, followed by the room with thin curtains, and the room without curtains has the highest energy consumption for air conditioning. The room without curtains has the lowest energy consumption for artificial lighting, the room with thin curtains has the second lowest, and the room with thick curtains has the highest electricity consumption for artificial lighting. The air conditioning energy consumption accounts for the main building energy consumption, followed by the lighting energy consumption. After setting curtains in the office, the air conditioning energy consumption caused by the solar radiation heat entering the room through the exterior windows is smaller than the lighting energy consumption caused by artificial lighting. Therefore, the installation of internal shading with moderate transmittance and good thermal insulation performance can make the energy saving of lighting and air conditioning energy consumption reach the optimal value. [ABSTRACT FROM AUTHOR]

Current requirements for residential energy-efficient design solutions in China are relatively homogeneous, requiring only improvements in overall building energy performance, often ignoring the energy differences between different residential housing units. This paper proposes a multi-objective research framework based on an occupant behavior model of air conditioning and a Non-dominated Sorting Genetic Algorithm-II (NSGA-II) to study energy-efficient design solutions for residential envelopes. The optimal energy-saving design scheme has a 22.56% and 35.34% reduction in energy consumption difference between residential units and overall building energy consumption, respectively, both of which have been optimized substantially. Moreover, the overall energy performance of the building can be improved when the "energy performance difference between housing units" (EDH) is reduced, which verifies that EDH is an important criterion for improving the energy performance of residential housing units. [ABSTRACT FROM AUTHOR]

With the rapid development of the economy, carbon neutral and carbon peak are on the agenda in China, and the reform of intelligent construction and assembly building is in full swing in the Chinese construction industry. In order to further explore and study the relationship between the textural structural issues of the envelope structure and the overall energy consumption situation of the house, and further bridge the gap between the actual energy-saving design scheme and the actual application scheme, therefore, this paper takes a certain place as a research object to study the phenomenon of design assembly energy saving, based on dozens of assembly building enterprises researched, selected samples of envelope components studied, selected BIM technology for premodeling optimization, used neural network algorithm for analysis of influencing factors, and studied the application in the study of energy-saving optimization of assembly building envelope in the western Sichuan plain area, and used OpenStudio was used to build a model to simulate the heating and air conditioning load of the assembled building numerically and to fit the quantitative relationship between the variable factors and the building energy consumption. On this basis, the relationship between multifactor and single-factor variables is identified and evaluated using relevant variables means. [ABSTRACT FROM AUTHOR]

The goal of reaching the peak of carbon in the construction industry is urgent. However, the research on the feasibility of realizing this goal and the implementation of relevant policies in China is relatively superficial. In view of the historical data of energy consumption and building CO2 emission from 1995 to 2019, this paper establishes a BP neural network model for predicting building CO2 emissions. Moreover, the influencing factors, such as population, GDP, and total construction output, are introduced as the parameters in the model. Through the scenario analysis method explores the practical path to accomplish the peak of building CO2 emissions. When using traditional prediction methods to predict building carbon emissions, the long prediction cycle will increase the possibility of significant errors. Therefore, this paper constructs the calculation model of building carbon emission and forecasts the future carbon emission value through the BP neural network to avoid the error caused by the nonlinear relationship between influencing factors and predicted value. It will effectively predict the feasibility of the carbon peak and the carbon-neutral target set by government, and provide a useful predictive tool for adjusting the new energy structure and formulating related emission reduction policies. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Engineering Management / Gongcheng Guanli Xuebao is the property of Journal of Engineering Management Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

As an important public facility, the number, area, and scale of hospital buildings are growing rapidly. The efficiency of nurses' rounds to beds is an important indicator of the efficiency of nursing units in ward buildings. Ward buildings occupy a very important position in the overall energy consumption of hospital building complexes. The type and scale of nursing unit floorplans are some of the key factors affecting the energy consumption of ward buildings. In this paper, three typical floorplan layout types of hospital ward buildings in cold regions of China are selected. The relationships between rounding efficiency, building energy consumption, floorplan layout, and building size were quantified using Origin based on linear regression and non-linear regression. The study showed that at 60 beds, the efficiency of nurse rounds was 35.68% higher in the double-corridor layout compared to the single-corridor. At 44 beds, the difference in average bed energy consumption between the double-corridor type and the single-corridor type is the greatest, with a 9.02% saving in energy consumption. This result confirms that the layout and scale of the ward building has a significant impact on the efficiency of nursing unit rounds and building energy efficiency. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to present a tri-optimization approach to optimize design solutions regarding the building shape and envelope properties considering their implications on thermal comfort, visual comfort and building energy consumption (EN). The optimization approach has been applied to obtain the optimal design solutions in five typical cities across all climatic regions of China. Design/methodology/approach: The method comprises a tri-optimization process with nine main steps to optimize the three objectives (thermal comfort, visual comfort and building EN). The design variables considered are four types of building shape (pyramid, rectangular, cylindrical and dome shape) and different envelope properties (insulation thickness [INS] of external walls/roof, window type [WT] and window-to-envelop surface area ratio [WESR]). The optimization is performed by using the Taguchi and constraint limit method. Findings: The results show that the optimal design solutions for all climatic regions favor cylindrical shape and triple-layer low-E glazing window. The highest insulation level of 150 mm is preferred in three climatic regions, and the INS of 90 mm is preferred in the other two climate regions. In total, 10% WESR is preferred in all climatic regions, except the mild region. When the constraint limit of lighting intensity requirement by Leadership in Energy and Environmental Design (LEED) is applied, the rectangular shape building is the optimal solution for those with 10% WESR. Research limitations/implications: The method proposed in the paper is innovative in that it optimizes three different objectives simultaneously in building design with better accuracy and calculation speed. Practical implications: Building designers can easily follow the proposed design guide in their practice which effectively bridges the gap between theory and practice. The optimal design solutions can provide a more comfortable living environment and yet less EN, which can help achieve the sustainability requirement of green buildings. Social implications: The solutions presented in the paper can serve as a useful guide for practical building designers which creates economic and commercial impact. In addition, the theory and practical examples of the study can be used by building regulators to improve the energy-efficient building design standard in China. Originality/value: The research is the first attempt that adopts tri-optimization approach to generate the optimal solutions for building shape and envelope design. The tri-optimization approach can be used by building designers to generate satisfactory design solutions from the architectural viewpoint and meanwhile to find combinations of the building shape and envelope properties that lead to design solutions with optimal building performance. [ABSTRACT FROM AUTHOR]

Massive energy consumption data of buildings was generated with the development of information technology, and the real-time energy consumption data was transmitted to energy consumption monitoring system by the distributed wireless sensor network (WSN). Accurately predicting the energy consumption is of importance for energy manager to make advisable decision and achieve the energy conservation. In recent years, considerable attention has been gained on predicting energy use of buildings in China. More and more predictive models appeared in recent years, but it is still a hard work to construct an accurate model to predict the energy consumption due to the complexity of the influencing factors. In this paper, 40 weather factors were considered into the research as input variables, and the electricity of supermarket which was acquired by the energy monitoring system was taken as the target variable. With the aim to seek the optimal subset, three feature selection (FS) algorithms were involved in the study, respectively: stepwise, least angle regression (Lars), and Boruta algorithms. In addition, three machine learning methods that include random forest (RF) regression, gradient boosting regression (GBR), and support vector regression (SVR) algorithms were utilized in this paper and combined with three feature selection (FS) algorithms, totally are nine hybrid models aimed to explore an improved model to get a higher prediction performance. The results indicate that the FS algorithm Boruta has relatively better performance because it could work well both on RF and SVR algorithms, the machine learning method SVR could get higher accuracy on small dataset compared with the RF and GBR algorithms, and the hybrid model called SVR-Boruta was chosen to be the proposed model in this paper. What is more, four evaluate indicators were selected to verify the model performance respectively are the mean absolute error (MAE), the mean squared error(MSE), the root mean squared error (RMSE), and the R-squared (R2), and the experiment results further verified the superiority of the recommended methodology. [ABSTRACT FROM AUTHOR]

The building sector is one of the largest energy user and carbon emitters globally. To increase the utilization rate of renewable energy and reduce carbon dioxide emissions, the optimal technical scheme of active public institutions and coupled utilization of renewable energy is studied. In this study, the energy consumption of three types of public institutions in various regions of China was simulated by using DeST building energy consumption software, combined with energy conversion efficiency and data released by the National Bureau of Statistics, and the total energy demand and total energy supply of public institutions were predicted using the load density method. Based on the coupling mechanism of the MARKAL model, the optimal proportion of renewable energy in the energy supply of public buildings in different regions is determined. Through the study of the number of public institutions in various regions of China, energy consumption characteristics, construction area, and other related data, the reverse energy flow method is creatively proposed, and the active and renewable energy coupling algorithm from the energy demand side of public institutions to the energy supply side is established. The results show that the central region has the highest utilization rate of renewable energy in the public sector, reaching 36.18%. The use of renewable energy in public buildings in hot summer and warm winter zones decreased to 35.08%, and it was 12.82% in cold zones. By 2025, the proportion of renewable energy resources in China is expected to reach 29.2%. The energy coupling model and algorithm constructed in this paper can provide a basis for the coupling macro configuration of renewable energy in public institutions in China. [ABSTRACT FROM AUTHOR]

Occupant behavior has an important impact on building energy consumption, and the accuracy of an occupant behavior model directly affects the reliability of energy consumption simulation results. Ultra-low energy buildings are crucial to achieving building energy conservation and carbon dioxide reduction in China. In order to effectively promote the development of ultra-low energy buildings in Hot Summer and Cold Winter Climate Zones. where most residents adopt a "part-time, part-space" pattern of intermittent energy use behavior, and to solve the problem of poor indoor thermal environments and the high incremental cost of ultra-low energy, the study described in this paper takes Changsha as an example to carry out a multi-objective optimization study on ultra-low energy housing using a probabilistic behavioral model. On the basis of a probability model representing the residents' actual behavior in Changsha, the optimization objective indicators, key variables and the technology benchmarks for ultra-low energy building were determined, then multi-objective optimization was carried out for a range of energy efficient technologies to obtain the Pareto optimal solutions. The results showed that the set of optimal solutions could reduce energy demand by 50.2 to 60.2% and reduce indoor thermal discomfort time by 3.52–11.09% compared with those of a reference base case, which just meets the requirements of the current design standard for energy efficient domestic buildings. An optimum solution for energy savings and indoor thermal comfort, along with economic costs, was identified, which can assist in decision-making by providing different preferences and provide useful reference for the design of ultra-low energy buildings in Hot Summer and Cold Winter Climate regions. [ABSTRACT FROM AUTHOR]

Green buildings (GBs) can effectively reduce building energy consumption and alleviate energy problems. However, as green building projects swell, the development process of GBs in China has gradually exposed many problems, among which the greenwashing behavior of construction enterprises is the more serious. The government needs to adopt some appropriate policies to prevent problems in GBs. This paper uses the evolutionary game theory to construct models and proposes four policy combinations: static reward and static punishment, static reward and dynamic punishment, dynamic reward and static punishment, dynamic reward and dynamic punishment. We compare the impact of four combinations on construction strategy and analyze the inner mechanisms of the behavior evolution of government departments and construction enterprises. Our results revealed no evolutionary stabilization strategy in the game system under the static reward and punishment policy. Under the combination of dynamic subsidies and static penalty policy, the green construction effect of construction enterprises is the best. Furthermore, dynamic reward policy has a more obvious restraining effect on construction enterprises. The government should dynamically adjust rewards and punishments according to the construction quality and determine the appropriate upper limit of rewards and punishments to improve the policies' applicability and effectiveness. This study provides theoretical support for the healthy development of green buildings. [ABSTRACT FROM AUTHOR]

Nearly zero-energy-consumption buildings are the inevitable trend of future buildings. There have been a large number of studies on nearly zero building technology issues. However, there is no detailed study on how to effectively promote the development of nearly zero-energy consumption buildings according to China's national conditions. Here, by establishing an evolutionary game model, this paper discusses the dynamic game scheme selection and stability strategy of three stakeholders, namely local government, real estate companies, and construction consumers, related to the development of nearly zero-energy-consumption buildings in the development process. The conditions required for evolutionary stabilization strategies were identified. Finally, Matlab data simulation analysis is used to further illustrate the stability and equilibrium strategies of each subject and the sensitivity analysis of the main influencing factors at various stages in the development process of nearly zero-energy-consuming buildings. The research results show that the government plays a leading role in the early stage of the development of nearly zero-energy consumption buildings, and as the market matures, government intervention gradually withdraws from the market; furthermore, if the cost of supervision is prohibitively high, the government's willingness to supervise the market will be reduced. This will hinder consumers and developers from choosing nearly zero-energy-consuming buildings and if the penalties and subsidies are too low, it will be meaningless to the evolution of the optimal solution of the three parties. On this basis, targeted promotion programs are established to realize the rapid development of China's nearly zero-energy-consumption building sector. Our research results can provide important scientific basis for the development of the nearly zero-energy building industry in China. [ABSTRACT FROM AUTHOR]

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

China accounts for more than 22% of the total energy consumption worldwide. Building energy consumption, among which consumption in public buildings was about 40% took the second place. With the problems of high energy waste, error rate and complexity of the control systems available, an indoor intelligent lighting system based on occupants' location is proposed in this paper to improve the energy efficiency of the current lighting systems indoors. The transmission model of electromagnetic wave in free space is optimized in both aspects of reference signal strength and attenuation coefficient radiation in complex environment dynamically based on which occupants' positions are obtained. The smart lighting system will turn on or off corresponding lights adaptively to provide a more energy efficient platform. Experimental results show that the proposed system is able to improve the energy efficiency of indoor lighting by at least 15%, with a lower error rate below 2% compared with the existing lighting systems based on voice control. [ABSTRACT FROM AUTHOR]

Based on the emission factor method and LMDI-LEAP model, this paper systematically studies the current situation, influencing factors and changing trend of carbon emissions from rural buildings in a typical village located in southern China. The results showed that (1) the per capita carbon emissions generated by the energy consumption of rural buildings is 2.58 tCO2/a. Carbon emissions from electricity consumption in buildings account for about 96.07%; (2) the per capita building area, building area energy intensity, population size, population structure and carbon emission coefficient affect rural building carbon emissions, with contribution rates of 70.13%, 31.27%, 0.61%, −1.21% and −0.80%, respectively; (3) from 2021 to 2060, the carbon emissions of rural buildings are expected to increase first and then decrease. In 2021, the base year, carbon emissions from buildings were 2755.49 tCO2. The carbon emissions will peak at 5275.5 tCO2. Measures such as controlling the scale of buildings and improving the utilization rate of clean energy can effectively reduce carbon emissions, in which case the peak can be reduced to 4830.06 tCO2. Finally, the countermeasures and suggestions about rural building energy saving and emission reduction are proposed, including improving the construction management, raising energy efficiency standards in buildings, increasing the proportion of clean energy and raising residents' awareness of energy conservation. [ABSTRACT FROM AUTHOR]

Copyright of Architectural Journal / Jian Zhu Xue Bao is the property of Architectural Journal Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

With the continuous improvement in China's economy, the construction industry has developed and rampantly progressed. Besides the wastage of resources and energy, the development has caused serious pollution to the environment. This makes the construction industry a high energy-consuming and highly polluting industry. There is a pressing need to reduce the wastage of resources and to adequately manage consumption of energy throughout the life cycle of buildings. This paper explores an effective method of building life cycle energy management by appropriately utilizing information system and the emerging deep learning technology. To achieve energy saving in buildings, a feasible model is proposed for predicting, analyzing, and building energy consumption based on neural networks. By analyzing the massive data stored in the building information system, the operation of each subsystem in the building is guided and regulated to achieve energy deployment and build energy optimization. Focusing the key meters, the average generalization ability of the proposed model (R-Squared = 1.9, MSE = 1.02) is better than the other contemporarily used models, LightGBM, LSTM, and SVR. Moreover, the method can effectively predict the energy consumption of the whole life cycle of the building and has higher prediction accuracy. The method proposed has great significance in research related with improving building energy performance and designing decision support tool. [ABSTRACT FROM AUTHOR]

Northern China is vigorously promoting cogeneration and clean heating technologies. The accurate prediction of building energy consumption is the basis for heating regulation. In this paper, the daily, weekly, and annual periods of building energy consumption are determined by Fourier transformation. Accordingly, a period-based neural network (PBNN) is proposed to predict building energy consumption. The main innovation of PBNN is the introduction of a new data structure, which is a time-discontinuous sliding window. The sliding window consists of the past 24 h, 24 h for the same period last week, and 24 h for the same period the previous year. When predicting the building energy consumption for the next 1 h, 12 h, and 24 h, the prediction errors of the PBNN are 2.30%, 3.47%, and 3.66% lower than those of the traditional sliding window PBNN (TSW-PBNN), respectively. The training time of PBNN is approximately half that of TSW-PBNN. The time-discontinuous sliding window reduces the energy consumption prediction error and neural network model training time. [ABSTRACT FROM AUTHOR]

In order to achieve China's energy conservation and emission reduction goal of peaking carbon dioxide emissions around 2030, it is of great significance. An important means of building energy conservation and emission reduction is the fine management of building energy consumption, which is based on the accurate prediction of building energy consumption, so as to support the optimal management of building operation and achieve the goal of energy conservation and emission reduction. This paper puts forward the evaluation indexes of the results of the building energy consumption prediction model, uses MAPE and RMSE indexes to evaluate the accuracy of the prediction results of the model, and uses the prediction time and input parameter dimensions to evaluate the time cost of the prediction model. Then, using the three building energy consumption prediction models based on machine learning algorithm established above, the prediction of energy consumption of four types of public buildings in different seasons is completed, and the prediction results are evaluated and analyzed. According to the prediction results and the requirements of related work on the accuracy of building energy consumption prediction model, the adaptation relationship between different types of buildings and different machine learning algorithm prediction models is summarized. [ABSTRACT FROM AUTHOR]

The number of studies considering building performance optimization (BPO) in the building design phase is steadily growing, but many of the existing studies do not consider the applicability of many-objective optimization algorithms when increasing the objective dimensions. This article first compares the NSGA-II, IDBEA, MSOPS-II, and NSGA-III algorithms. Then, the algorithm most suitable for many-objective optimization is combined with Artificial natural network(ANN) and TOPSIS-AHP to complete the optimization of four dimensions of building energy consumption (EC), useful daylight illuminance (UDI), comfort time ratio (CTR) and energy-saving envelope cost (ESEC) for village houses in cold regions of China. The results show that the NSGA-III algorithm performs well in terms of convergence speed, convergence, diversity, and uniformity when solving many-objective problems compared to the other three algorithms. Finally, four optimization strategies were selected using the TOPSIS-AHP method. [ABSTRACT FROM AUTHOR]

Windows are responsible for the largest amount of energy loss related to building envelope. Past studies on the energy consumption of windows have mainly focused on residential and commercial buildings, while few studies have explored the energy consumption of windows in educational buildings. The sizes and locations of classroom windows affect not only the building energy consumption but also the indoor environment quality, which is an issue that needs to be balanced. This paper takes a classroom in Guangzhou as the object. Under the premise of meeting the lighting standards of the classroom, two parameters—window height and sill height —were simulated in different corridors of north–south and east–west classrooms to analyse the impact of their changes on the indoor environment as well as energy consumption based on the parametric platform Grasshopper and its plug-ins Ladybug and Honeybee. The energy consumption of a number of fenestration combinations on both sides of the classroom was optimized automatically by genetic algorithm, and the sizes and positions of windows that benefitted energy savings were obtained. In the best case ~16.6% of energy consumed in a whole year can be saved compared with the worst case. This conclusion can provide a quick decision-making process for the design of window shapes for the purpose of energy savings in the early design stage of educational buildings in the Pearl River Delta such that energy savings can be quickly and clearly guaranteed in the subsequent window configuration. [ABSTRACT FROM AUTHOR]

Under the requirement of energy savings and emission reduction in China, building energy consumption, which occupies a rising proportion of the total energy consumption in society, has become the focus of energy conservation research. Public buildings with a high-energy consumption level have become the most important part of energy conservation research. It is of great practical significance and social value to study energy conservation in large public buildings. In this paper, a large office building is taken as an example. First, a simulation model is constructed by using the energy consumption simulation analysis method, and the reliability of the model is verified by a comparison with the actual energy consumption. Second, based on the model, the thermal design parameters of six building envelope structures, including the external wall heat transfer coefficient, are analyzed in the order of energy-saving sensitivity. Based on the results of the sensitivity analysis, suggestions for each factor are presented. Finally, considering the mutual influence of each parameter on the building energy consumption, the orthogonal design method is used to arrange the test, and the optimal scheme combination of the energy-saving effect is analyzed, which can provide decision support for the energy saving of public building envelopes. [ABSTRACT FROM AUTHOR]

Copyright of South Architecture / Nanfang Jianzhu is the property of South Architecture Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The PV/T-GSHP heating control system is proposed to address the energy consumption problem of building heating in northern China. By using TRNSYS to establish an automatic control model, the control of the heat pump start/stop, water supply temperature on the load side of the tank, and high temperature water return to the building can achieve the purpose of being energy saving, providing stable heating, and providing control of high temperature heating. The results show that the PV/T-GSHP control system has an annual fluctuation range of 0.01~0.17 kW in the heating period for a typical building heat supply and building heat load, and the system energy efficiency and energy consumption are increased by 14.5% and 33.91%, respectively, compared with the GSHP system, and the annual value of cost is reduced by 8.49% and 19.09% compared with the GSHP and traditional coal-fired boiler system, which shows that the PV/T-GSHP control system is more economical. It can be seen that the PV/T-GSHP control system has better heating stability, energy efficiency, and economy, and it provides theoretical significance for the current clean heating automatic control scheme in Chinese northern areas. [ABSTRACT FROM AUTHOR]

China is facing the challenge of high building energy consumption, especially for rural housing, because of the backward construction technology. This issue could be solved by net-zero energy rural housing. Therefore, the passive energy-saving procedures and energy-efficient building service systems of rural housing are needed to be studied apart from renewable energy adoption. Older people with unique thermal acceptability and adaptability become the primary residents in Chinese rural buildings, which calls for the redefinition of the indoor environment. This paper firstly conducted an overall questionnaire about the indoor environment sensation and expectations of the rural elderly in Sichuan province. Field surveys and measurements were carried out in a typical self-built rural house to investigate the thermal comfort of the local order people and the indoor thermal environment variations. Furthermore, the fuzzy analytic hierarchy process was used to propose a three-layer assessment model for the rural elderly living environment to find retrofit strategies. Results showed that: (1) the thermal environment of rural buildings could not meet the thermal comfort range of older people in summer. (2) The adaptive coefficient (λ) in the adaptive Predicted Mean Vote model was 0.065 for the rural elderly, which was lower than the value of 0.21 in the Chinese standard, indicating their poor thermal adaptability. (3) The summer living environment evaluation was "A little bad", and the most effective optimization method was to decrease the indoor temperature. (4) Based on the thermal comfort of older people, architectural and construction optimizations were proposed, which could achieve an energy-saving of 52.15 %, contributing to net-zero energy rural housing. • Environment improvement and energy saving of rural housing were studied. • The age-based metabolic rate of the elderly was proposed in aPMV. • The adaptive coefficient for the rural elderly was 0.065. • The evaluation model of rural living environment satisfaction was built by FAHP. • Passive retrofit procedures were proposed to achieve NZERH. [ABSTRACT FROM AUTHOR]

In this paper, 16 cities representing four major architectural climate zones of China were selected, and the heating and cooling loads of office building during the period of 1961–2017 were simulated by using TRNSYS software. Daily extreme heating and cooling loads were determined by percentile methods, and the climate change impact on extreme loads was analyzed. The results showed that the days of extreme heating load of office building significantly decreased in almost all the selected cities, whereas there were no significant changes in the days of extreme cooling load. The daily extreme heating load was dominantly affected by the temperature (R2 = 0.43–0.79), but the daily extreme cooling load was related to multiple climate factors, including temperature, relative humidity, and solar radiation. Single temperature can only explain 3–37% of the changes of daily extreme cooling load, and the combination of multiple climate factors can explain 58–85%. Importantly, the effect of temperature on extreme cooling load showed decrease from the cold to hot climate zones, but the impacts of relative humidity and solar radiation gradually increased. These results suggest that the maximum design capacity of heating systems can properly decrease, and the design capacity of cooling systems may not largely increase with the climate warming. In addition, the combined effect of multiple climate factors rather than the single temperature, as well as the different responses of extreme cooling energy consumption to climate change in different climate zones, should be considered when making measures for improving operating efficiency of air-conditioning system. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Beijing University of Technology is the property of Journal of Beijing University of Technology, Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A recent trend in China has seen super high-rise residential buildings spreading to severe cold regions. These buildings face tough challenges concerning building energy consumption and the thermal environment due to their stack effect. The stack effect is greatly influenced by air infiltration, but current guidance on component airtightness is often neither specific nor consistent for different buildings. This paper presents field measurements and numerical simulations of airtightness performance and stack pressure distribution for a a 106.7-m high-rise residential building in Harbin, Northeast China. An airtightness field test was performed using the fan pressurisation method, and measured values were utilised as the input data for predictions. The numerical analysis was implemented by applying CONTAMW, and the simulation results were compared to measurement data. The results demonstrated that the measured components were all leakier than the current standards allow. The greatest stack pressure difference on the ground floor reached 51.5 Pa, considered a severe stack effect. Furthermore, the influences of the location and airtightness of different staircase doorways on the stack effect were studied and analysed. This research assists in clarifying the significance of building airtightness in cold climates and in reducing the stack effect of high-rise buildings. [ABSTRACT FROM AUTHOR]

Copyright of Guangdong Architecture Civil Engineering is the property of Guangdong Architecture Civil Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The rapid development of urbanization in China inevitably leads to a sharp increase in building energy consumption, and Passive House (PH) have received much attention in China in recent years. In this paper, the annual energy demand (AED) and summer discomfort hours (SUH) of PH are used as optimization objectives to establish a set of design solutions for multi-objective optimization (MTO) and economic analysis of a PH in Shandong Province, China. It is found that (1) the algorithm based on nearest neighbor component analysis (NCA) feature extraction applies to the sensitivity analysis of multivariate nonlinear high-dimensional data, and the NCA-GA-RBF neural network technique is proposed, which has significantly improved the goodness of fit and generalization ability for AED and SUH. (2) The NSGA-II genetic algorithm is used for the optimization search, and the results show that the overall improvement rates of AED and SUH are 25.5% and 21.6%, respectively, among the nine solutions after comprehensive evaluation; (3) Finally, the optimal scheme of energy saving and the optimal scheme of the economy are selected for economic evaluation. By comparing the economics of the two options and the improvement rates of AEDs and SUHs, the guidelines for design decision-makers are provided. In summary, the design scheme of this paper is forward-looking and reference-oriented and provides some reference suggestions for the development of PH in China. • The NCA algorithm is suitable for multivariate nonlinear sensitivity analysis. • NCA-GA-RBF has stronger and more stable generalization ability and accuracy. • In this paper, climate is the main factor affecting thermal parameters. • Global costs have a stronger economic interpretation. [ABSTRACT FROM AUTHOR]

The operational state of energy-efficient ultra-low energy consumption buildings is very important to achieve energy savings and emission reductions, which are currently necessary considerations for the development of the building industry. To date, studies on the implementation of ultra-low energy consumption have been based mainly on the analysis of the effects of certain technologies, and few studies have examined the regional implementation paths at different energy consumption levels. Based on an analysis of actual data obtained from energy consumption monitoring, verification of energy-saving renovations and green building evaluations in Chongqing, this paper suggests setting the target value for ultra-low energy consumption buildings in hot summers and cold winters areas at 29.04 kWh/(m2.a), proposes a technology system that includes the practical application of data for seven active energy-efficient technologies, and establishes an implementation path for the integrated application of active and renewable energy technologies. Then, a set of strategic models for the construction of implementation paths for ultra-low energy consumption buildings that can be promoted in different climatic areas and building types is proposed. The recommendations based on this model are of practical value for guiding policy makers in promoting the development of ultra-low energy consumption buildings. • Determined ULEB target value based on actual Chongqing energy consumption data • Proposed energy-efficient technology system based on effect and cost analysis • Proposed replicable strategic models for implementation path of ULEBs construction [ABSTRACT FROM AUTHOR]

Passive house standard buildings (PHSBs), characterized by exceptional airtightness, present a promising technology for attaining carbon neutrality by 2060. The level of building airtightness is closely associated with air infiltration, which significantly impacts building energy consumption. However, there has been insufficient analysis of air infiltration in highly airtight buildings across diverse climatic regions. The present study involves the numerical simulation of the air infiltration rate (AIR) in an airtight building under varying design conditions during winter and summer, followed by a comprehensive analysis of the corresponding energy demand associated with air infiltration. The simulation results indicate that the building's AIR ranges from 125 to 423 m3/h, with an average of 189 m3/h under summer design conditions, and from 40 to 344 m3/h, with an average of 198 m3/h under winter design conditions. The statistical findings demonstrate distinct distribution patterns for AIR and energy demand across various climatic regions, exhibiting significant variations in values. The discussion emphasizes the substantial heating load associated with air infiltration, even at a building airtightness level of 0.5 h−1, highlighting the necessity of considering its impact in the design of highly airtight buildings. Furthermore, it is recommended to establish specific airtightness limits for buildings in different climatic regions of China. This study offers theoretical guidance for the airtightness design of highly airtight buildings. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Harbin Institute of Technology. Social Sciences Edition / Haerbin Gongye Daxue Xuebao. Shehui Kexue Ban is the property of Harbin Institute of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Double skin facades (DSFs) have overheating problems in warm seasons which may increase the cooling loads in buildings. A previous study has developed an integrated phase change material (PCM) blind system and proved its capacity of mitigating the overheating phenomenon in DSFs. This paper focuses on the effect of design parameters on the thermal performance of such systems by conducting a simulation study of a DSF integrated with a PCM blind with different material properties, positions in cavity, and tilt angles of blades. The results indicate that the performance of the integrated PCM blind system can be optimised with careful geometric design and proper thermophysical properties of the PCM. [ABSTRACT FROM AUTHOR]

Currently, many airports in China are being built or retrofitted. Reducing energy consumption in airport terminals is of the utmost urgency. This paper describes on-site measurements of indoor thermal environment and air infiltration of a hub airport in winter in southwest China. Air velocity measurements with air volume balance check and thermal balance check were applied to assess air infiltration rates in terminal buildings. In unsecured halls, air infiltration rates were 0.61 air change per hour (ACH) (6.6 m3/(h m2)) and 0.28 ACH (3.0 m3/(h m2)) when space heating was on and off, respectively; while in secured piers, those two air infiltration rates were 0.42 ACH (2.6 m3/(h m2)) and 0.24 ACH (1.5 m3/(h m2)). Air infiltration consumed 66–92% of heat supplied by space heating systems, showing that winter air infiltration significantly affects indoor thermal environment and energy consumption in terminal buildings where air flows out through the doors of service walkways and open skylights on the roof. Furthermore, influences of building characteristics, space heating systems and outdoor temperatures on winter air infiltration in large space buildings were analysed. This research helps to clarify the key issues influencing indoor thermal environment and proposes solutions for energy saving in terminal buildings. [ABSTRACT FROM AUTHOR]

A city is an area highly concentrated in buildings, but is also an important place for energy consumption and waste generation, so the development of buildings with low energy consumption and less pollutant emissions is an important way to achieve energy conservation and emission reduction, and sustainable development of cities in China. On the basis of systematically combing and broadly absorbing the relevant research results of sustainable development and urban greening, and combining with the mathematical methods such as variation coefficient and intuitionistic fuzzy analytic hierarchy process, urban housing buildings are taken as the subject of evaluation. With sustainable development as the evaluation background, the aim of study is to systematically and comprehensively evaluate and analyze the building greening level. Based on the analysis of green building theory and predecessors' research results, the influence of economic, political, technical and other factors on the development of green building in nearly 300 cities in China is analysed. And combined with the actual development examples of Shenzhen City, it is further discussed. It is concluded that the research method used in this paper is correct, and Shenzhen is selected as an example to provide reference for the sustainable development of other cities [ABSTRACT FROM AUTHOR]

In response to extreme climate change, China has set a goal of reaching emission peak by 2030 and achieving carbon neutrality by 2050. Energy conservation and emission reduction of building heating in northern China are key to achieving this goal. Based on building area prediction and energy consumption intensity, this paper establishes a model for calculating heating energy consumption and carbon emissions in northern residential buildings at the macro level, which provides a basis for formulating policies related to heating and emission reduction in northern buildings. Based on the research method of scenario projection, combining the carbon emission subsets and future heating energy mix projections in northern China, the heating energy consumption in northern China decreases to 175, 149 and 135 Mtce in 2050 under the baseline, medium control and strict control scenarios, respectively. The heating energy consumption in the northern region should be controlled at least under the medium control scheme. Under this scenario, building heating carbon emissions in the north could be reduced to 450 MtCO2 by 2050, or 280 MtCO2 if more stringent abatement technologies are adopted. In order to achieve this goal, a combination of energy-saving technologies must be used. The use of biomass and solar technologies should be emphasized in rural heating, while envelope renovation makes the greatest contribution to heating energy savings, with envelope renovation contributing up to 92 Mtce to urban heating. [ABSTRACT FROM AUTHOR]

When modeling the energy performance of existing buildings, model calibration always serves as an essential and necessary step to ensure the accuracy and applicability of building models. Model calibration for detailed energy models, which is also known as calibrated simulation (CS), refers to the process of tuning model's input parameters to narrow down the mismatch between the simulation result and the real-monitored data of building energy consumptions. Two major problems of current CS are: (1) a successful calibration requires HVAC domain knowledge of modelers. (2) Traditional building calibration process is labor-intensive and time-consuming. To solve these problems, a normative energy modeling based quick auto-calibration approach is proposed in this study. This approach is able to reduce the modeling time and simplify the calibration procedures. Firstly, this paper demonstrates the working principles and the credibility of Normative Energy Modeling (NEM). Then, the methodology of the proposed quick auto-calibration approach is elaborated. The energy performance model of a large hotel located in Shanghai, China with NEM is used as a case study to investigate the effectiveness of the proposed quick auto-calibration approach. The simulation result of the case study suggests that the proposed approach can significantly simplify the procedures of model calibrations while still achieve a good accuracy specified by ASHRAE Guideline 14 [1]. Besides, the results further confirm that such method requires much less time and computational power for modeling, compared with other counterparts (e.g., “Autotune” calibration [2]). With the advantage of speed and accuracy, the auto-calibration proposed in this paper is promising to be applied in both engineering and research field. [ABSTRACT FROM AUTHOR]

With the rapid development of urbanization in recent years, the area and energy consumption of public buildings are also growing rapidly. As a special comprehensive public building, hospital buildings are characterized by high energy consumption, complex structure and high power of equipment. With China's "carbon neutral, carbon peak" goal and the continuous upgrading and improvement of the medical environment, how to reduce the energy consumption of hospitals is also increasingly important. This paper analyzes the climatic characteristics of the hot summer and warm winter region and the energy consumption characteristics of hospitals in this region, then evaluates them and proposes two energy-saving and carbon-reducing measures, namely, photovoltaic power generation and roof greening. Finally, EnergyPlus simulation is used to study the specific cooling savings of using green roofs and analyze the carbon reduction under different percentages of photovoltaic power generation. The results of the thesis have certain application value for energy saving and carbon reduction in general hospitals in hot summer and warm winter areas. • Characteristics of energy consumption of general hospital in hot summer and warm winter region are analyzed. • The carbon emissions of these hospitals were calculated and analyzed and energy saving options were proposed. • Use EnergyPlus to simulate its green roof and calculate its cooling savings and carbon reduction. • Green roofs can save up to 11.7% of cooling. • Photovoltaic (PV) power generation can reduce total carbon emissions, and when the share of PV power generation varies from 10% to 20%, the total carbon emissions can be reduced by 13.79% to 27.43%. [ABSTRACT FROM AUTHOR]

Ultra-low-energy buildings in China are still in the early stage of development. In the guide documents of the 13th plan of five-year national development published by Science and Technology Ministry, an energy consumption limit of 15kWh/m2 for heating, cooling and ventilation throughout the year was pointed out for residential buildings in hot summer and cold winter region. In this paper, current situation of winter heating in Shanghai was investigated, including analysis of heating energy consumption of more than 40,000 households, a large number of questionnaires about heating status, and the actual indoor heating environment monitoring. This paper also investigated the indoor ventilation environment under real living conditions, taking a typical residence in Shanghai as the research subject via continuous field measurements. The indoor CO2 concentration, air temperature and relative humidity were monitored and two behavior-related parameters, the electricity consumption of air conditioner and the open/closed state of the window/door were recorded from summer to spring. Based on the investigation, the questionnaires and the monitored data for winter heating, heating strategies in winter for residential buildings in Shanghai will be discussed, from the perspective of gap analysis. [ABSTRACT FROM AUTHOR]

Building energy consumption in China accounts for 45% of the total national energy consumption, with air conditioning energy consumption representing approximately two-thirds of that. Therefore, energy efficiency in buildings is of utmost importance. This study focuses on a chemical industrial park located along the Fujiang River and compares three heating and cooling supply schemes: the river water source heat pump system, which utilizes river water as the heat source and heat sink; the water cooling unit and boiler system, which uses water-cooled electric compression chillers for cooling and an oil-fired boiler system for heating; and the split air conditioning and gas water heater scheme, which relies on refrigerants such as fluorine-containing compounds for cooling and a gas water heater for heating. By calculating the energy consumption of the above three schemes and conducting a comparative analysis, it is found that the river water source heat pump system exhibits significantly higher energy efficiency throughout the year compared to the water cooling unit and boiler system and the split air conditioning and gas water heater scheme. This highlights the notable energy efficiency advantage of the river water source heat pump system. [ABSTRACT FROM AUTHOR]