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Unlike many previous studies that often focus on optimizing energy efficiency for buildings when detailed design drawings are available, this paper introduces a newly integrated model for energy-efficient building envelope design in the early stages (when detailed design drawings are not yet available). The newly developed model includes three main components: a simulation model, a predictive model, and an optimization model. The simulation model simulates the building's energy performance, considering different values for various envelope parameters. The predictive model employs machine learning algorithms, including RF, ANN, DNN, SVM, GENLIN, and GB (in which GB has been identified as the most suitable algorithm), boasting a very high R 2 (0.994) to assess energy consumption. The optimization model which uses AI optimization algorithms (such as NSGA II, DSE, and MOPSO) integrates the machine learning predictive model into the evaluation function during the evolutionary process, efficiently searching for Pareto-optimal building envelope solutions. Results show simultaneous savings in cost and energy, with savings of 7.52 % in cost and 8.48 % in energy, or 21.17 % in cost and 0.4 % in energy, for a case study in Vietnam. This model establishes a foundation by providing design solutions for stakeholders to assess, and can incorporate additional objectives at later stages. [ABSTRACT FROM AUTHOR]

In this paper, the integral performance indicator for selecting HVAC systems (ACPI) is applied to select the Air Conditioning (AC) system with better results in their life cycle for a typical building in Barranquilla, Colombia. The AC systems under study were: direct expansion system (Split and VRF), air-cooled system (VAC and VAV), and water-cooled system (Chiller). Of the six selection criteria of ACPI, the energy consumption index (EC) and thermal comfort (TC) were calculated through energy simulation of buildings, the regulations were used for IAQ and carbon emissions (CE), and were estimated the investment costs (IC) and operating and maintenance costs (OMC). The best-performance AC system for the building was the air-cooled AC system got the best ACPI values between 25 % and 22.4 %, followed by the water-cooled system with 22.3 %, and finally the direct expansion systems between 16.8 % and 13.5 %, influencing in this level of priority the IAQ and IC criteria. This study contributes to introducing in Colombia a multifactorial analysis to select the more proper AC system technology according to the building and location conditions. [ABSTRACT FROM AUTHOR]

The problem addressed in this work is the enhancement of energy efficiency in buildings, primarily focused on heating control. The paper highlights the importance of addressing this challenge, given that HVAC systems are responsible for over 60% of total energy consumption in buildings, making them the largest energy consumers in both the residential and nonresidential sectors. This paper presents a methodology for developing a model predictive control (MPC) system based on artificial neural network (ANN) models, with the aim of improving the energy efficiency of buildings. This approach involves the creation of a training dataset using dynamic thermal simulation tools, enabling the learning of the ANN model that is responsible for predicting future states within an MPC optimization loop. Additionally, the implementation leverages advanced technologies such as Field-Programmable Gate Arrays (FPGAs), specifically the PYNQ board, Wi-Fi modules, and MQTT communication to enhance scalability, deployment, and adaptability. The study evaluates the proposed Neural Network Model Predictive Control (NNMPC) strategy implemented on the PYNQ, reporting a substantial reduction of 38.53% in heating energy consumption in buildings compared to a basic On/Off control approach for 24-hour simulation. This outcome underscores the solutions significant potential for energy savings in building heating systems. [ABSTRACT FROM AUTHOR]

This comprehensive study analyses the energy demand for heating and cooling in the building stock across different climatic zones in Spain, incorporating the effects of weather evolution over the past 30 years (from 1992 to 2022). In evaluating 7200 cases across four climatic years and six climatic zones which include six Spanish cities, the analysis examines the construction characteristics of the building stock. The focus is on the thermal envelop properties under two scenarios: the current state and a renovated state that complies with the new Spanish building code (in agreement with the EPBD EU-Directive EU/2024/1275). The study's findings reveal potentially significant changes in energy demand due to climate. The heating demand decreases significantly due to increasing temperatures ranging from 17% in Madrid up to 37% in Almería. This effect is contrasted by a substantial increase in cooling demand, which has surged 223% in Barcelona, a surge closely linked to higher summer temperatures. The paper concludes that the current energy certification scheme fails to provide a real overview of the energy performance and needs of buildings in Spain. In particular, it underestimates actual sensible cooling demand by 56% in Barcelona and 41% in Almería. Additionally, the failure of existing building regulations to address the issue of indoor overheating is proven. [ABSTRACT FROM AUTHOR]

Understanding transient heat transfer in building assemblies is important for improving the energy efficiency of the built environment. This paper describes an inverse analysis to evaluate the field energy performance of a multilayer prefabricated wall. The purpose is to estimate the heat flux through the internal surface of a wall in an occupied lightweight house in Quebec City (Canada). The inverse problem modeling was based on one-year on-site temperature measurements which convey the in-use thermal behavior of the wall assembly. The inner surface experienced an outward heat flux for most of the year. The greatest heat loss was around 5.5 W m−2 in winter and the greatest heat gain was around 1.0 W m−2 in summer. In the heating period, the indoor environment lost about 18 kW h m−2 (6.5 × 107 J m−2) of thermal energy. There was a total thermal gain of around 1 kW h m−2 (3.5 × 106 J m−2) during the free cooling period. Based on the heat flux estimations, the effective thermal resistance of the assembly was found to be 6% lower than its theoretical value, but still in compliance with Canadian building standards. • The inner wall surface experienced heat losses for most of the year monitored. • Heat loss and heat gain peaks were around 5.5 W m−2 and 1.0 W m−2, respectively. • 18 kW h m−2 of thermal energy left indoors across the wall in the heating period. • 1 kW h m−2 of thermal energy entered indoors across the wall in the cooling period. • Effective R -value is 6% lower than the theoretical one and complies with the norms. [ABSTRACT FROM AUTHOR]

This paper aims to explore the feasibility of the silicon aluminum (Al–Si) alloy for usage as a thermoelectric tile on building roofs. Through the simulation of the heat conduction characteristics and temperature field distribution of the step-shaped Al–Si alloy sample, the effects of the thickness, material, and shape of the Al–Si alloy sample on its thermal conversion efficiency and temperature field distribution characteristics of continuous solar irradiation were studied. The energy conversion characteristics of the Al–Si alloy sample combined with a thermoelectric generator (TEG) were investigated by numerical analysis and experiment. The results show that the Al–Si alloy sample with a thickness of 10 mm had a good heat storage efficiency. Also, the Al–Si alloy tile with a plane shaped solar irradiation surface and the back-sun surface with a certain number of bosses has a better heat transfer efficiency. Through experiment and calculation demonstrate that an Al–Si alloy tile with 500 mm × 500 mm area could generate 1.64 W electric power. [ABSTRACT FROM AUTHOR]

In this paper, an artificial neural network (ANN) based system-level model predictive control framework is established for a variable air volume (VAV) system to improve its robustness and energy efficiency. The VAV system consists of three processes: the zone temperature process, the damper process and the supply air volume process of the air handling unit connecting the ductwork for all of the boxes. An ANN-based predictive controller is designed for the zone temperature process, and a PI controller is used for the damper process; they operate in a cascaded manner. Another ANN predictive controller tracks the total supply air volume subject to the cooling load constraints from the lower level VAV boxes and minimizes the fan energy consumption. The ANN controllers are optimized online by the Lagrange variational approach (LVA) to minimize the system cost function and implement a feedback receding horizon optimal control. With the LVA based gradient descent training algorithm, the weight convergence of the ANN predictive controllers and stability of the control system is obtained with small computational and storage needs. The modeling methodology, based on ANNs for the above processes, is developed and calibrated with actual data measured from a site. All of the data processing and control strategy implementations are based on extensive measurements collected from a laboratory building located in the campus of Beijing University of Civil Engineering and Architecture , Beijing , China. The experimental results show that an additional 6.12% energy savings is achieved. This is accomplished by introducing the fan control signal into the system cost function as the performance index of energy consumption with a 0.2 penalty coefficient. In the presence of un-modeled disturbances and modeling errors, the framework also reduces the temperature oscillation at least by approximately 60% compared with PI control. • A neural network-based predictive control strategy for VAV systems is designed. • Cascade predictive control is implemented for zone temperature and air flow rate. • The duct air volume process achieves total airflow predictive control with savings in fan energy consumption. • The predictive controller using neural network implementation, easy to achieve nonlinear system optimization. • The control strategy is robust to un-modeled disturbances and modeling errors. [ABSTRACT FROM AUTHOR]

[Display omitted] • The paper reviews 43 articles defining methodologies for climate classification. • The paper provides overview of climate classification and validation methods. • Need of standard methodology or nomenclature for climate classification. • The optimal approach for conducting climate zoning remains a topic of debate. Climate classification simplifies the representation of expected climate conditions by eliminating the need to describe each climatic parameter. Climate classification is frequently used as a basis for recommendations through codes and standards for buildings because a given climate has nearly similar design conditions. Furthermore, building energy efficiency programmes are designed based on the climatic classification to determine appropriate design strategies to eliminate the under-design or over-design of buildings for similar climatic regions. This necessitates the use of realistic and reliable climate classifications. Over the past two decades, numerous research studies have proposed climate classification methods. However, there is a lack of universal acceptance of climate classification methodology to balance complexity and accuracy. This research provides an overview of various climate classification methods and indicators used to assess the significance of climatic conditions. Moreover, this study highlights pressing issues, proposes a feasible climate classification methodology, and offers substantial possibilities for future study. This study organizes and evaluates the various classification and validation methods used by researchers, variables, and the granularity of data used for the classification. The usual criteria for defining a climate are temperature, relative humidity, cooling-degree days, heating-degree days, and solar radiation. About eighty-five percent of the classified climates are using at most three variables. The number and characteristics of climate zones vary with changes in the resolution of climate data, classification methods, and the inclusion of different sets of parameters. Clustering methods are becoming more important for climate classification as these methods can handle multiple variables more accurately. To tackle the complex relationship between climate and building thermal design, it is recommended to use climate variables with cluster analysis and validation based on thermal loads. This paper will give researchers an aerial perspective of the scope and direction of ongoing research in this field. [ABSTRACT FROM AUTHOR]

Buildings consume significant amount of energy for heating or air-conditioning in most countries. Therefore, educating the public and young generations to enhance their engagement and encourage them to reduce carbon emission and energy consumption in their daily life is becoming essential worldwide to drive continuous improvement towards more sustainable future. This paper presents an innovative educational tool to simulate energy performance and its use in educating university students and teaching school children about the subject. The paper outlines the developed educational tool and presents its benefits via two detailed case studies, with wide and diverse level of knowledge and learning outcomes. The educational technology includes a small-scale multi-layered model of buildings where insulation layers can be added to or removed from the building’s envelop to influence energy performance. Qualitative and quantitative research has been conducted. The results show that the technology is capable of engaging the young generation and to help them to understand the thermal performance and energy efficiency of buildings. [ABSTRACT FROM AUTHOR]

Due to the higher practicability and annual utilization, the dual-use heat pump systems are more popular in practical demonstrations. Although there are various kinds of designs for such system, most of them focus on the performance enhancement in heating mode and pay little attention to the cooling capacity. The proposed three-dimensional composite heat exchanger structure based on a concentrator plus fins could not only improve the total output in heating mode but also lower the condensing temperature by shading the solar energy with the concentrator to improve the cooling COP. Different from previous study, this paper focus on the improvement potential in cooling mode of the novel system. Experiments are carried out and used for the validation of mathematical model. By analyzing the physical state of the refrigerant during the cycle, the mechanism is revealed in detail and depth. Results show that the dryness decrease at evaporator inlet caused by the condensing temperature drop is the main reason for capacity improvement, while the mass flow rate also has crucial impact. With high mass flow rate, the mean cooling COP of proposed system could be as high as 3.1, 0.16 higher than the system without concentrator shading. • The paper presents the improvement impact in the cooling cycle. • Experiments are carried out for the validation of distributed parametric model. • The decreased dryness at the evaporator inlet explains for the increased cooling. • Lower condensing temperature may cause lower cooling energy with fixed throttling. • Proposed system could get a mean cooling COP of 3.1, 0.16 higher than irradiated system. [ABSTRACT FROM AUTHOR]

Although it is often stated that the energy consumption in buildings accounts for more than 30% of total global final energy use, only a few studies analyze updated data about the current building energy consumptions or focus on comparing different countries. Similarly, models that predict future trends in building energy demand often use contrasting algorithms which result in diverse forecasts. Scope of this paper is to present and discuss data taken from several studies about the building energy consumptions in US, EU, and BRIC (Brazil, Russia, India, and China) countries and to provide an updated inventory of useful figures. Comparisons among countries are used to show historical, actual, and future energy consumption trends. Data presented by the World Bank, the United Nations Environment Program, the Intergovernmental Panel on Climate Change, and the International Energy Agency are compared with national reports as well as with research studies. The variety of the approaches used in each of the previous sources was considered fundamental to allow a complete review. The paper shows that the total building energy consumptions in BRIC countries have already overcome those in developed countries, and the continuous increase in the building stock of the BRIC countries creates an urgency for promoting building energy efficiency policies in these countries. At the same time, the policies actually adopted in developed countries are insufficient to guarantee a significant reduction in their building energy consumption in the years to come. In the current scenario, at least a doubling of the global energy demand in buildings compared to today’s levels will occur by 2050. To avoid this forecast, cost-effective best practices and technologies as well as behavioral and lifestyle changes need to be diffused and accepted globally. [ABSTRACT FROM AUTHOR]

This paper evaluates the post-occupancy performance of 6 star houses in the hot and humid tropics of Darwin compared to unrated/lower rated control houses during the inactive/active phases (build-up/wet) of monsoon trough. Study is based on surveys of 61 respondents in the build-up and 44 respondents in the wet, indoor climatic measurements in 10 houses, and electricity consumption data. Actual mean vote ranged between -0.5 to 0.5 at a range of mean indoor conditions: air temperature 29.9-30.72 °C, relative humidity 50.42-72.96%, and air velocity 0.23-0.35m/s. Behavioural adjustment surveys showed that the percentage of occupants in 6 star rated houses who always utilise air conditioner increased from 36% in the build-up to 50% in the wet. While percentage of fan users remained around 90% during both periods. An impact of occupants’ behavioural adjustment, house star rating, and built environment on indoor climatic conditions is discussed through analysis of monthly mean temperature and relative humidity values. Mean monthly air temperature in living rooms of 6 star houses reached highest point of 30.8 °C in February 2016; while in control houses it reached 31.59 °C in January 2016. Highest mean relative humidity in 6 star rated houses was 74% compared to 81% in control houses. Analysis of electricity consumption of 36 households showed that the average half-hourly consumption of households in 6 star rated houses increased from 0.58 kWh in December 2015 to 0.72 kWh in February 2016, while consumption in control houses increased from 0.72kWh in December 2015 to 0.76kWh in January 2016, and reduced to 0.75kWh in February 2016. This paper presents findings for the build-up and wet seasons only. The results of this study provide insight into the impacts of the built environment, thermal preferences, and occupant behavioural adjustment on the thermal performance and electricity consumption of households in hot and humid tropical conditions. [ABSTRACT FROM AUTHOR]

Energy consumption and indoor environment of buildings are proved to be largely influenced by the presence and behaviors of occupants. The uncertainty caused by occupant behaviors accounts for a significant discrepancy between the predicted and actual energy usage. In a real world, building system operations and control will be directly affected by occupant behavior, which may lead to over thirty percent waste against building's designed performance. Therefore, the capability to seamlessly integrate occupant behavior in energy simulation tools and building management systems in the future is clearly important to optimize building energy use while maintaining the same level of services. However, research has not reached the phase that occupant behaviors could be effectively modeled. Thus, the traditional schedule based approach is not adequate to satisfy the needs of building efficiency. In this paper, a thorough survey of occupant behavior modeling and simulation state-of-the-art technologies and methodologies for building energy efficiency is conducted. The paper first identifies and discusses the significance and application scale of building occupant behavior model. Based on the information collected, some recent data acquisition technologies for behavior-related research and occupant behavior modeling approaches are summarized. The advantages and limitations of these modeling methods are compared and analyzed, as well as appropriate recommendations are made for the future research. The paper finally outlines the findings and potential development areas in the field of occupant behavior modeling for energy efficient buildings. [ABSTRACT FROM AUTHOR]

Climatic zoning is an essential element of most building energy efficiency programs, however there is no widely accepted scientific technique for its delineation. This paper reports an investigation on this issue, which comprised the review of climatic zoning methodologies for building energy efficiency programs adopted by 54 countries. The paper identified that the nature and magnitude of climatic variations are not the main elements in the definition of the number of climatic zones in a country. The number of climatic zones seems to be mainly driven by the expected simplicity of the final climatic zoning, respecting in most cases a maximum of 8 zones independent of the country size and climatic variations. A total of 19 different variables, techniques and parameters used in climatic zoning were identified, the most frequent being temperature, degree days, altitude, administrative divisions and relative humidity. However, around 80% of the countries analysed in this study used only up to three variables/techniques/parameters to define their climatic zoning. This simplicity comes at the cost of ignoring several aspects of climate and building energy performance. From the techniques identified in this review, only the combination of building performance simulation and cluster analysis seems to provide robust tools to tackle the complex relations between climate and building energy performance. Combined, these tools may provide the means to explore scenarios and support evidence-based decision making in energy policy. The lack of consensus in several aspects of climate zoning indicates the need for further research in this area. [ABSTRACT FROM AUTHOR]

The 2023 revision of the Energy Performance of Building Directive underlines the need to consider the whole life cycle emissions for buildings. The decarbonization targets could not be achieved if reduction of energy demand in the operational phase is accompanied by a high energy resource use in the whole life. This paper proposes a novel investigation of an energy renovation project, involving both building envelope components and space heating system. The adopted method is based on the life cycle assessment, in the variant cradle-to-gate with options, to analyze and compare the design data achieved through an analysis of product (embodied) and use (operational) stages. Different solutions for energy improvement of the building performance are identified, and the scenario with the lowest embodied energy was found to be more energy efficient globally. The most effective scenario, with energy and CO 2 savings of 39% and 40% is characterized by a weight of embodied energy and emissions of 6.5% and 6.9%, respectively. Given the rise of the weight of the embodied energy in the whole life cycle of future buildings, the life cycle assessment will become crucial for sustainable design and in the transition to an energy-efficiency built environment. [Display omitted] • The impact of life cycle analysis in the process of energy efficiency is investigated. • The "cradle-to-gate" with options approach is implemented. • The efficiency of walls and windows involves the greater use of energy resources. • The most energy-efficient scenarios from an operational and non-operational point of view are different. • The scenario identified in the analysis of A1-A4 phases allows a higher total energy saving. [ABSTRACT FROM AUTHOR]

Housing energy rehabilitation is currently a priority in Europe. In vulnerable neighbourhoods, improving energy efficiency and comfort conditions has an important impact on people living conditions. Rehabilitation strategies are usually designed according to standard scenarios, without taking into account variations related to the users or the type of building. Monitoring this type of housing offers valuable information to be able to select the best strategies based on a diagnosis of their real performance. In this paper we present one year data on energy consumption, hygrothermal comfort and CO 2 monitored for 22 dwellings in Madrid, located in six different vulnerable locations. In addition to normal periods, the monitoring campaign includes periods of extreme heat and cold, and two exceptional situations, the "Filomena" snowfall and the COVID pandemic period. The results report poor indoor environmental quality in these dwellings, both in the main rooms and in the bedrooms. Also poor building quality is observed. The recorded energy consumption is lower than that given as a reference in the standards or models, at the cost of a worse indoor environment. The analisys supports the importance of retrofit strategies that take into account the composition of the household, such as single-person households or those with children, the higher vulnerability of dwellings with higher demand, the subjective perception and the role of users, and the need to incorporate improvements in indoor air renewal. • One year monitored data for 22 social housing dwellings in Madrid is presented. • Energy consumption, hygrothermal comfort and indoor CO 2 concentration is discussed. • Improvements should take into account both energy efficiency and IEQ needs. • Key drivers are household composition, building quality, or user interactions. [ABSTRACT FROM AUTHOR]

Small commercial buildings, or those comprising less than 50,000 square feet of floor area, make up 90% of the total number of buildings in the United States. Though these buildings currently account for less than 50% of total energy consumption in the U.S., this statistic is expected to change as larger commercial buildings become more efficient and thus account for a smaller percentage of commercial building energy consumption. This paper describes the efforts of a multi-organization collaboration and their demonstration partners in developing a library of case studies that promote and facilitate energy efficiency in the small commercial buildings market as well as a case study template that standardized the library. Case studies address five identified barriers to energy efficiency in the small commercial market, specifically, lack of: (1) access to centralized, comprehensive, and consistent information about how to achieve energy targets, (2) reasonably achievable energy targets, (3) access to tools that measure buildings’ progress toward targets, (4) financial incentives that make the reduction effort attractive, and (5) effective models of how disparate stakeholders can collaborate in commercial centers to reach targets. The case study library can be organized by location, building type, project size, energy savings, end uses impacted, and retrofit measures. This paper discusses the process of developing the library and case study template. Finally, the paper presents next steps for the library and explores energy savings potential its widespread use. [ABSTRACT FROM AUTHOR]

Facility management has become increasingly challenging due to complex building systems that generate more diverse and complex maintenance issues. Facility managers and staff must deal with many daily maintenance requests despite various limitations, such as limited budgets and staff, which can cause delay in responding to some maintenance requests. A scheduling framework is proposed in this paper to assist in improving facility management. In practice, maintenance work is scheduled according to various priorities. For example, facility managers first consider the impact of each problem in terms of system failure and safety. In addition to those two factors, the framework proposed in this paper considers both energy efficiency and occupant satisfaction. It first quantified occupant satisfaction with data from current building maintenance work. An empirical study on occupant satisfaction was done based on classical disconfirmation theory and referenced post-occupancy evaluation (POE) research. A survey was designed to collect data to quantify occupant satisfaction. Based on the disconfirmation theory, an agent-based model was then developed to prioritize maintenance work to achieve maximum occupant satisfaction. Subsequently, a building energy model was simulated in EnergyPlus to quantify the impact of different aspects of a faulty HVAC system on energy consumption. Finally, the framework was tested through simulation and the results showed that occupant satisfaction level and building energy efficiency were improved by 30 and 97%, respectively, when using the framework. [ABSTRACT FROM AUTHOR]

Building Energy Efficiency Retrofit (BEER) is considered as a valuable way to improve energy efficiency of high-energy-consumption buildings. Sustainable BEER helps integrate sustainable development strategy into existing buildings and retrofit projects. To ensure BEER projects that can fulfill the sustainable development strategy, Energy Performance Contracting (EPC) is one possible market mechanism to deliver energy efficiency projects. Sustainable BEER under the EPC mechanism is a comprehensive system which involves the various demands of sustainable dimensions, performance criteria and groups of project success factors, making multi-criteria decisions become a challenging problem for decision makers. This paper aims to examine the interrelationships of sustainable BEER by focusing on an existing hotel building. EPC mechanism is applied in the case study and an effective Analytic Network Process (ANP) approach is also employed in the research. The result indicates that sustainable BEER in hotel buildings under the EPC mechanism is mainly determined by project control mechanism, available technology, organizing capacity of the team leader, trust, accurate Measurement and Verification (M&V), and team workers' technical skills. Decision makers should dedicate more attention to these aspects. From the research findings, several policy implications are proposed in this paper. [ABSTRACT FROM AUTHOR]

This paper analysed the results and the status of China's building energy efficiency, explored the new areas of building energy in future: the industrialized composite wall on construction. As China is engaginga process of rapid urbanization,it is believed thatlarge amount of construction will continue for 25-30 years, and all of new buildings must be strictly in accordance with the standards of energy-saving by 50% or 65% in the processes of design and construction. Chinese construction industry is currently implementing the “Four Savings and Environment Protection” policy, which requires energy, land, water and materials saving and environmental protection in every building project. In Heilongjiang Province, as other areas in China, the requirements of energy-efficient design have been comprehensively and strictly implementedon the new buildingssince 2000. By 2010, energy-efficient design has been completely popularized in all kinds of new buildings by 50% energy saving compared with the same type of buildings built in 1980s. According to the requirements of the Ministry of Construction, in the future the further energy efficiency targets should be increased from 50% to 65%, meanwhile the main field of building energyefficiencywill been changed from the initial entry points such as the thermal insulation of externalwall, roof, doors and windows to further wide areas, such as the Optimization of building material, component manufacturing, construction quality and method, all of which could be realized by the industrialized composite panels and walls completely. Industrialized composite panels and wallsbring thoroughgoing innovationson wall materials and construction, the improvementof the construction accuracy, so that the wall thermal insulation performance is much higher than traditional buildings. Due to the productionconcentrated in the factory and the batch processing, the energy consumption ofbuilding industrialization is much lower than the traditional human construction at the construction site. The industrialized composite panel and wall of buildings can reduce the loss of the main materials of construction,the assembling construction reduce the loss of Secondary buildingmaterials. Compared with traditional construction methods, building industrialization of the composite panelrealizesthe field fabricated construction, which greatly minimizes the generation of construction waste, building waste water emissions, construction noise interference, harmful gases and dust emissions, and so on. The Building industrialization could maximize the improvement of the quality of components and assembly precision, and effectively reduce the roof leaks, wall cracks, quality defects of wall and window such as cold air infiltration, so the architectural quality and accuracy can be improved significantly. Factory production and on-site assembling of prefabricated components can reduce the workers of construction site and management, saving a lot of labor costs. Building industrialization transfer most of the operation to production line, saving construction cost and schedule greatly. It is particularly important to the construction in cold areas. Moreover, three types of building composite walls and panel are introduced. In this paper, composite walls and panel include composite material, composite structure or both of them applied in the wall and panel. The first kind of composite wall is the straw board. The straw board is clean, which is made of natural straw or wheat straw as the main raw material. This kind of straw board is mainly used for internal and external walls of the building and roof of the building, etc. Straw board whichis regarded as wall materials generally does not work as load-bearing walls. When it comes to application, the surface should be decorated to ensure that its fire, moisture, fire-retardant abilities. Straw board is not only suitable for load-bearing frame structure buildings, including civil construction, light industrial plants, but also for the old buildings which need to be rebuild, storage buildings and temporary buildings, etc. It is a lightweight, high strength, thermal insulation board which is new and environmentally friendly, particularly suitable to use in cold regions construction. The second example is the HS-EPS core column structure system, whichis invented by Harbin Hong Sheng housing energy system research and development centre with the whole intellectual property patents. This system consists of base beam, EPS moulded wall composed with core column of reinforced concrete, eaves ring beam and roof trusses and other components, is suitable for various types of single storeybuildings.EPS module consists of polystyrene beads by heating and foaming, through a dedicated heat moulding equipment and moulds in the system with closed-cell structure of different types, different specifications and different shape. The modules are rectangular, which internal and external surfaces distribute the uniform dovetails. There are two bridges connecting the fixed plug door in the middle of three 200 mm × 240 mm rectangular hole, both inside and outside of the hole wall thickness is 50 mm. In 2010, itwas applied in Piaohe town as a pilot project and in Antu County as 800 post-disaster housing, where thissystem has been widely recognized. The third sample is Gao Ge Composite Panel of Husk Mortar, with the both advantages of composite material and composite structure. This panelis precast, made from light husk mortar, welded wire mesh and steel as the skeleton, and thermal, noise insulation layers. The husk mortar is made of cement, sand, husks and water by mixing. This panel can be used to the wall-bearing housing, and multi-storied and high-rise reinforced concrete frame construction as the envelope, its overall size is the same with the external wall of a room, as in Four sides of the panel are joined with the beams and columns of the buildings. The wall panel consists of two surface layer of husk mortar, and two insulation layer (benzene or rock cotton) and a air layer inside. The two surface layers are connected by the vertical and horizontal reinforced ribs, and the insulation layers are spliced inside by mortar, each small insulation board was totally fixed by insulation mortar from 5 surfaces. The cavities between two insulation layers are supported by the ribs. [ABSTRACT FROM AUTHOR]

Small commercial buildings, or those comprising less than 50,000 square feet of floor area, make up 90% of the total number of buildings in the United States. Though these buildings currently account for less than 50% of total energy consumption in the U.S., this statistic is expected to change as larger commercial buildings become more efficient and thus account for a smaller percentage of commercial building energy consumption. This paper describes the efforts of a multi-organization collaboration and their demonstration partners in developing a library of case studies that promote and facilitate energy efficiency in the small commercial buildings market as well as a case study template that standardized the library. Case studies address five identified barriers to energy efficiency in the small commercial market, specifically lack of: 1) access to centralized, comprehensive, and consistent information about how to achieve energy targets, 2) reasonably achievable energy targets, 3) access to tools that measure buildings’ progress toward targets, 4) financial incentives that make the reduction effort attractive, and 5) effective models of how disparate stakeholders can collaborate in commercial centers to reach targets. The case study library can be organized by location, ownership type, decision criteria, building type, project size, energy savings, end uses impacted, and retrofit measures. This paper discusses the process of developing the library and case study template. Finally, the paper presents next steps in demonstrating the efficacy of the library and explores energy savings potential from broad implementation. [ABSTRACT FROM AUTHOR]

Predictive control is an effective method for addressing the increasing demand for heating, ventilation, and air conditioning (HVAC) systems to operate with greater flexibility and efficiency. In this paper, the multi-objective problem of energy-efficient HVAC operation while tracking desired setpoints is addressed through an advanced control strategy, including a novel supervisory data-driven predictive control (DPC) and a local loop with a PI controller. The supervisory level is based on the integration of the DPC framework and the bilinear Koopman predictor. A deep neural network architecture is developed to realize the bilinear building thermal predictor. In addition, the integral input-to-state stability (iISS) constraint is enforced in the training procedure to obtain a global iISS control-oriented thermal predictor that enables the application of predictive control purely based on historical data. The effectiveness of the proposed approach is demonstrated through the simulation of a three-zone office in the transient system simulation software (TRNSYS). The proposed control configuration is implemented using a coupled TRNSYS-MATLAB simulation framework. It has shown significant potential for keeping the desired environment in line with energy conservation. Furthermore, a comparison is conducted between the proposed approach, the conventional controller, and another recent DPC approach, which demonstrates the suggested method's superiority. • Data-driven hierarchical control configuration for optimizing multi-zone HVAC systems. • Proposal of a DPC configuration using the Koopman operator and neural network. • Imposing iISS constraint on the predictor training algorithm. • Proposed method validation using the simulated three-zone HVAC system in TRNSYS. • Significant energy savings compared to the baseline controller and another DPC method. [Display omitted] [ABSTRACT FROM AUTHOR]

Abstract Semi-transparent photovoltaic (STPV) windows, which can not only generate electricity in situ, but also effectively reduce solar heat gain while utilizing natural daylight, have gained increasing popularity due to their energy and environmental benefits. However, the poor thermal insulation performance of single-glazed STPV windows has restricted their application in cold climate regions. PV insulated glass unit (IGU) is an alternative for STPV window applications. This paper presents a comprehensive assessment on overall energy performance of PV-IGUs with different PV glazing transmittance and rear glasses in comparison with conventional IGUs in five different climate zones in China. The results show that PV-IGUs can achieve energy savings in all the representative cities. The largest energy savings are observed in Kunming where heating and cooling demands are low but annual solar radiation level is high. In cold climate regions like Harbin, the PV-IGU with higher transmittance and rear low-e glass consumes less net source energy in comparison with that with lower transmittance and rear clear glass. Although the lighting energy demand of PV-IGU is larger than conventional IGU, the daylight quality of the room with PV-IGU is better due to the higher useful daylight illuminance (UDI) and lower daylight glare probability (DGP). Highlights • An integrated thermal, daylighting and PV power generation building energy model is developed. • Energy saving potential of PV-IGU is evaluated in comparison with conventional IGU. • Daylight analysis is conducted using daylight metrics – DA, UDI and DGP. • The optimum design of PV-IGU under different climate conditions is achieved. [ABSTRACT FROM AUTHOR]

Abstract China has launched the energy efficiency project (EEP) for its civil building sector beginning in the mid-1980s; however, its implementation has not been effective. To better promote the EEP for the Chinese civil building sector, the Chinese government issued the China Act on the Energy Efficiency of Civil Buildings in 2008. This is the first paper to present a review of this act's implementation over the past decade. Based on China Database of Building Energy Consumption and Carbon Emissions and official documents, the achievements of this act are assessed by examining a variety of indicators. The success of the act can be attributed to the following factors: 1) a strong and sustained government commitment to top policies of building energy efficiency (BEE); 2) extensive efforts to apply the BEE standards to newly built civil buildings; 3) various incentive schemes involving energy efficiency retrofitting for existing civil buildings; 4) the increasing adoption of renewable energy to the civil building sector and of systems and platforms of energy efficiency supervision to commercial buildings; and 5) the rapid development of green buildings. Nevertheless, the revised act must address several challenges in the upcoming phase. These challenges mainly include the following: 1) the "double-control" strategy for the civil building sector; 2) the substantial development of the EEP in rural China; 3) the further development of green buildings for the low-carbon civil buildings; 4) the improvement of official statistical data systems on energy consumption and carbon emissions for civil buildings; and 5) building industrialization and informatization. It's expected that our efforts as constituting significant guidance for evaluating the EEP in the Chinese civil building sector, and the efforts will also be treated as an example for other developing countries to evaluate and revise their BEE acts. Graphical abstract Energy-saving value assessment of the Chinese civil building sector based on an IPAT-LMDI approach. Unlabelled Image Highlights • Presented a decennial review of the act for the first time. • Proposed a decadal retrospection of building energy efficiency project in China. • Building energy savings in 2011–2015: 183 million tons of standard coal equivalent. • Means of revising the act were proposed. [ABSTRACT FROM AUTHOR]

Abstract Achieving low energy consumption and maintaining proper day-lighting environment is a challenge for large atrium building under cooling-dominant climates. Fortunately, aerogel glazing system has recently been considered to have great potential in energy-saving applications for architectural glass due to its special light transmission and thermal insulation properties. In this paper, eight aerogel glazing samples were prepared by filling aerogel particles with four different diameters into hollow glass with two different thicknesses (viz., 5 mm and 7.5 mm). The thermal and optical parameters of the aerogel glazing were experimentally measured and the day-lighting performance was calculated. A case study of the aerogel glazing installing at different positions in a large atrium building under cooling-dominant climates was carried out. The results indicate that installing aerogel glazing at the skylight with is more effective than at the outside windows. The envelope heat gain was reduced by 31% by replacing the single glazing with the HA-type aerogel glazing at skylight under the condition of indoor illumination. [ABSTRACT FROM AUTHOR]

Abstract A new analysis framework is developed and applied to assess the benefits of building energy efficiency policies and programs. One of the main advantages of the new energy productivity analysis is that it accounts for both economic and energy performances of energy efficiency actions using only one metric. Specifically, the approach applies the concept of energy productivity to the building sector and accounts for both value added and energy savings of energy efficiency measures. Moreover, the proposed analysis accounts for all quantifiable benefits of energy efficiency programs including economic, environmental, and social. In this paper, the general guidelines for the energy productivity analysis are first described. Then, the analysis is applied to evaluate energy efficiency renewable energy programs for both existing and new buildings in the Gulf Cooperation Council (GCC) countries. The analysis results indicate that retrofitting the existing building stock can provide significant benefits and can improve the energy productivity of the building sector in all GCC countries and free up large energy volumes and investment potentials to the development of other economic sectors. In particular, the analysis indicates that reduction in energy consumption, peak demand, and carbon emissions due to deep retrofit programs for the existing building stock can double the energy productivity of the GCC region. Highlights • A new analysis approach is presented to evaluate building energy efficiency policies. • The analysis is used to assess energy efficiency programs for new and existing GCC building stocks. • Retrofit of the existing building stocks can double the energy productivity in all GCC countries. [ABSTRACT FROM AUTHOR]

Abstract A growing literature has highlighted the variables and parameters that most affect the technical feasibility and the economic viability of the measures meant to improve building energy efficiency. This paper discusses the results of a literature review, which focuses on the studies that deal with three economic parameters: the price to be paid for the energy supply, the energy inflation rate, and the discount rate used to convert future cash flows to a present value, namely, an upfront lump-sum equivalent. A specific co-occurrence analysis of terms is performed on the titles and abstracts of the examined documents. The representation of the results allows recognizing several significant clusters and network relationships. Moreover, that literature review enables to identify two well-established research strands. The first involves the relationship between energy prices and the profitability of efficiency-related investments. The second research branch points at the pivotal role played by the discount rate when evaluating the investments in energy-efficient measures. [ABSTRACT FROM AUTHOR]

The membrane enthalpy exchanger (MEE) is a viable energy recovery device to alleviate building energy consumption. In this paper, a quasi-counter-flow MEE's energy-saving effect and frost risk under severe cold conditions is investigated experimentally and numerically. The experimental results demonstrate that frost occurs when the outdoor air temperature falls below −14 °C. At an outdoor temperature of −26 °C, the enthalpy effectiveness decreases from 63.8% to 43.3% after one hour of frosting, accompanied by a significant increase in the exhaust air's pressure drop by 2.7 times. Furthermore, the simulation results reveal that the lower latent effectiveness compared to sensible effectiveness contributes to the highest risk of saturation near the exhaust air outlet. Moreover, this study analyzes the influence of MEE's geometrical and physical characteristics on its recovery effectiveness and frost risk. The findings indicate that increasing the membrane spacing can prolong MEE's operation duration at the expense of recovery effectiveness. Specifically, the MEE's total energy recovery during the whole heating season in Shenyang, China, increases by 18% when the membrane spacing is extended from 2 mm to 5 mm with a membrane thickness of 70 μm. This study provides insights into the MEE design. • Membrane enthalpy exchanger has impressive total effectiveness higher than 60%. • Frost occurs in the exchanger when the outdoor air temperature is below −14 °C. • Frost formation causes surge of pressure drop and attenuation of effectiveness. • Higher resistance to moisture transfer than heat transfer aggravates the frost risk. • Optimizations of geometric and physical characteristics are discussed. [ABSTRACT FROM AUTHOR]

The high-altitude Central Asian communities (mainly from rural Tajikistan and Kyrgyzstan) face a high degree of energy complexity. The thematic knowledge clearly outlines that these communities hold special energy identity (information about energy requirements, energy consumption, classification of the building, energy resources, energy services, and challenges) and at the same time, energy poverty ironically exists. To mitigate energy poverty, there is an immediate need for sustainable energy transition through special energy planning. Though, the limited information about the energy identity of these communities restricts the energy transition process. The main aim of the paper was to outline the special and comparative energy profile of high-altitude Central Asian rural communities. To demonstrate the special energy profile, a novel correlative approach was developed which synthesises the information about energy context (current energy situation and critical issues), energy resources (available sustainable and non-sustainable energy and its usage) and energy services (available energy services to meet the energy need) by considering local boundary conditions. These various parameters were studied based on the extensive literature review, the author's interview with local people and the previous work of the authors. There is a large gap in the literature regarding energy information about high-altitude Central Asian communities. Based on the correlative approach, the presented article was the first attempt to develop a novel framework to interpret the energy identity of high-altitude Central Asian communities and thus contribute to knowledge. The derived special energy identity will serve as a profound base to develop an energy planning more effectively. The derived results categorised the spatial energy situation at the roof of the world. Even though access to electricity, the high-altitude Central Asian rural population suffers from unique and complex energy challenges articulated in the presented article. Energy is a costly and critical task for the local population. To resolve this issue, sustainable energy transition is an essential element for these settlements which ensures sustainable communities from the long-term perspective. This can be achieved by spatial energy planning for high-altitude communities (i.e. implementation of energy efficiency measures in combination with an energy supply system on a community level). • The high-altitude rural communities in Central Asia face unique energy challenges as significant energy required for heating due to old and uninsulated buildings, extreme cold climate and high-altitude terrain • A novel correlative approach was established to develop energy identity of communities situated at roof of the world • Guide for energy identity of high-altitude rural communities of Kyrgyzstan and Tajikistan is developed • This study demonstrates immedaite need of sustainable energy transition at roof of the world • The research suggests that building energy efficiency is a key parameter to achieve the complex sustainable energy transition at roof of the World. [ABSTRACT FROM AUTHOR]

In the early stage of building design, typical meteorological year (TMY) used for building energy consumption simulation which mainly representing average conditions, cannot reflect the building energy consumption under extreme weather conditions. Intensified climate change leads to global warming and frequent extreme events, therefore, generating meteorological years for simulating building energy consumption under extreme weather conditions is desperately needed. In this paper, a new method for generating extreme weather years—An extreme building energy year (EBEY) is proposed, which not only considers the influence of various meteorological parameters on building energy consumption, but also calculates the extreme intensity and occurrence time of multiple parameters using dynamic thresholds. The results show that the accuracy of using EBEY to simulate building energy consumption under extreme weather conditions is better than that of temperature-only extreme years, radiation-only extreme years, extreme meteorological years (EMY), typical cold years (TCY) and typical hot years (THY). In addition, this study verifies that combining TMY and EBEY data reduces the number of simulations without losing the accuracy of the simulation results. • The intensity and duration of extreme weather and many parameters are considered. • Use dynamic thresholds in determining the occurrence of extreme weather. • The combination of TMY and EBEY improves the accuracy of simulation results. [ABSTRACT FROM AUTHOR]

[Display omitted] • 30,000 full-text building-related articles have been extracted for text mining. • Data-science, energy efficiency, and lifecycle phases relations have been drawn. • Word embeddings model has been used to extract the relationship between keywords. • Gaps, opportunities, and potential future directions have been discussed. The ever-changing data science landscape is fueling innovation in the built environment context by providing new and more effective means of converting large raw data sets into value for professionals in the design, construction and operations of buildings. The literature developed due to this convergence has rapidly increased in recent years, making it difficult for traditional review approaches to cover all related papers. Therefore, this paper applies a natural language processing (NLP) method to provide an exhaustive and quantitative review.Approximately 30,000 scientific publications were retrieved from the Elsevier API to extract the relationship between data sources, data science techniques, and building energy efficiency applications across the life cycle of buildings. The text-mining and NLP analysis reveals that data sciences techniques are applied more for operation phase applications such as fault detection and diagnosis (FDD), while being under-explored in design and commissioning phases. In addition, it is pointed out that more data science techniques that are to be investigated for various applications. For example, generative adversarial networks (GANs) has potential in facilitating parametric design; transfer learning is a promising path to promoting the application of optimal building operation; [ABSTRACT FROM AUTHOR]

China consumes more energy and emits more carbon dioxide than any other country. The building sector accounts for nearly 1/3 of the total national energy consumption in China; thus, it is critical to find a solution for improving buildings’ energy efficiency. Under the market-oriented mechanism, constrained by the energy performance contracting (EPC) mode, energy service companies (ESCOs) play an important role in improving energy efficiency for high-energy-consumption industries, including the building sector. The aim of this study is to determine the strategy for boosting the building ESCO industry. By conducting a strength, weakness, opportunity, and threat (SWOT) analysis, this paper presented the status of the building ESCO industry in China and proposed alternative strategies. By utilizing a conventional multi-criteria decision-making method, namely, the Analytic Network Process (ANP), this study provides a quantitative basis to analytically determine the ranking of the factors in SWOT analysis and select the best strategy to promote the development of the building ESCO industry. The results showed that the ANP-SWOT is a viable and highly capable methodology that provides invaluable insights for strategic management decisions in the building ESCO industry, and a set of strategies for promoting ESCO development in the building sector were proposed based on this approach. [ABSTRACT FROM AUTHOR]

Highlights • Balance of cooling energy saving and heating energy penalty for solar reflective coating. • Calculated and tested equivalent thermal resistance of solar reflective coating. • Quantitative design method for solar reflective thermal insulation hybrid system. • Achievement was accepted by building energy efficiency design standard of Shanghai. Abstract Solar reflective coating applied on roof/wall surface is becoming an important passive cooling technology for building energy efficiency. Shanghai is located in the climate of hot summer and cold winter, so the hybrid system of solar reflective coating combined with thermal insulation materials on roof/wall should be an efficient way for building energy saving. In this paper, the thermal performance and design method of the hybrid system was discussed. Equivalent thermal resistance for solar reflective coating was put forward for thermal performance evaluation and energy efficiency design for the hybrid system. Equivalent thermal resistance considers not only reflectance of the material, but also the weather conditions, demand for indoor comfort, orientation and thermal performance of base wall/roof. Equivalent thermal resistance in typical summer day and winter day of Shanghai were theoretically calculated and tested. Annual equivalent thermal resistance which integrated the benefit in summer and the penalty in winter was achieved by linear regression algorithm of simulated energy, and the results were 0.07–0.40 m2·KW−1 for wall and 0.18–1.07 m2·KW−1 for roof. This means solar reflective coating is energy saving equivalent and replaceable with 7–23 mm thermal insulation layer on wall, and 14–107 mm on roof. This method was useful and accepted in the energy efficiency design standard of Shanghai. [ABSTRACT FROM AUTHOR]

Occupants are integral elements of a building ecosystem and their behavior can have a substantial impact on energy consumption in buildings. A wide range of energy feedback programs have been developed to make energy consumption more visible and interpretable to occupants and help them learn how to control and save energy. In this paper, we conduct a critical review of the literature related to energy feedback and identify four key methodological approaches to designing and studying energy feedback programs: experiments, analytics, surveys and simulation. Our meta-analysis reveals five research gaps and opportunities for future methodological fusion at the intersection between such approaches, including the analytics-survey, experiments-analytics, experiments-analytics-surveys, simulation-experiments and analytics-simulation interfaces. Future research at these crucial interfaces could provide the deeper understanding necessary to develop energy feedback programs that yield substantial and persistent energy savings. [ABSTRACT FROM AUTHOR]

In this paper a techno-economic evaluation method for deep renovation of buildings is introduced. We study the validation of an integrated design methodology based upon the creation of additional volume on existing buildings (Add-Ons) intended as roof-top or aside extensions, enclosures, parasites or façade transformations. Energy price uncertainty is modelled through a mean-reverting stochastic process, which well fits the data for natural gas prices, and the proposed evaluation method is based on real-option theory, which is an advancement of standard cost-benefit analysis, to be employed whenever uncertainty has a significant impact on the investment option. The new method to evaluate the economical feasibility of the Add-ons strategy for Deep Energy Renovation is tested through design experiments on a real case study of social housing in Reggio Emilia (Italy). [ABSTRACT FROM AUTHOR]

Climatic zoning for building energy efficiency applications is an important element in building energy policy and regulations. There are several methodologies available to conduct climatic zoning, providing significantly different results. Currently, there are no procedures to assess the validity of a proposed climatic zoning, hindering the decision to use one particular climatic zoning methodology instead of another. This paper introduces a quality index and a procedure to support the validation of climatic zoning. The procedure is based on building performance simulation results concerning the building stock that is targeted in the climatic zoning policy or program. Simulation results are used to calculate a new index, the Mean Percentage of Misclassified Areas (MPMA), which assesses the quality of the zoning under analysis. The capabilities of this procedure were demonstrated by the evaluation of four alternatives for the climatic zoning of Nicaragua, obtained using different methodologies and previously reported in the literature. The building stock used in this case study is composed of a few archetypes based on typical naturally ventilated dwellings in this country. Simulations were conducted using the program EnergyPlus for a total of 328 locations in Nicaragua. Degree-hours of discomfort based on the adaptive model of ASHRAE Standard 55 were used as a performance indicator. Results indicate that zoning obtained using cluster analysis and cooling degree-days may misclassify 1 out of 5 areas in Nicaragua (MPMA around 18–20%). This study concludes that the validation procedure and proposed index are useful for highlighting qualities and deficiencies of existing climatic zoning methods, particularly when these methods are used in less conventional applications, such as for policy making targeting naturally ventilated dwellings in tropical climates. The application of this procedure in more than 50 countries which adopt climatic zoning is foreseen as the next step in his area, substantially affecting the prescription of building materials and components worldwide. [ABSTRACT FROM AUTHOR]

Building operations account for the largest proportion of energy use throughout the building life cycle. The energy saving potential is considerable taking into account the existence of a wide variety of building operation deficiencies. The advancement in information technologies has made modern buildings to be not only energy-intensive, but also information-intensive. Massive amounts of building operational data, which are in essence the reflection of actual building operating conditions, are available for knowledge discovery. It is very promising to extract potentially useful insights from big building operational data, based on which actionable measures for energy efficiency enhancement are devised. Data mining is an advanced technology for analyzing big data. It consists of two main types of data analytics, i.e., supervised and unsupervised analytics. Despite of the power of supervised analytics in predictive modeling, unsupervised analytics are more practical and promising in discovering novel knowledge given limited prior knowledge. This paper provides a comprehensive review on the current utilization of unsupervised data analytics in mining massive building operational data. The commonly used unsupervised analytics are summarized according to their knowledge representations and applications. The challenges and opportunities are elaborated as guidance for future research in this multi-disciplinary field. [ABSTRACT FROM AUTHOR]

The advance in information technology has enabled the real-time monitoring and controls over building operations. Massive amounts of building operational data are being collected and available for knowledge discovery. Advanced data analytics are urgently needed to fully realize the potential of big building operational data in enhancing building energy efficiency. Data mining (DM) technology, which is renowned for its excellence in discovering hidden knowledge from massive datasets, has attracted increasing attention from the building industry. The rapid development in DM has provided powerful mining methods for extracting insights in various knowledge representations. Gradual pattern mining is a promising technique for identifying interesting patterns in big data. The knowledge discovered is represented as gradual rules, i.e., 'the more/less A, the more/less B'. It can bring special interests to building energy management by highlighting co-variations among building variables. This paper investigates the usefulness of gradual pattern mining in analysing massive building operational data. Together with the use of decision trees, motif discovery and association rule mining, a comprehensive mining method is developed to ensure the quality and applicability of the knowledge discovered. The method is validated through a case study, using the real-world data retrieved from an educational building in Hong Kong. It shows that novel and valuable insights on building operation characteristics can be obtained, based on which fault detection and optimal control strategies can be developed to enhance building operational performance. [ABSTRACT FROM AUTHOR]

Optimizing efficiency in the operation of the HVAC system of existing buildings requires the construction of a thermal dynamic model of the building, which may be challenging because architectural metadata may be missing or obsolete. Based on a suitable set of measured data, this paper presents a novel practical methodology to create and automatically derive thermal models of existing buildings in high-fidelity simulators for energy management. To this end, the philosophy of grey-box strategies is followed to simplify the modeling and avoid the requirement of architectural metadata, facilitating and expediting the process. First, a building model with a highly reduced number of parameters is constructed by exploiting the existing similarities in the materials of the buildings and simplifying their elements to a simple one-layer parameterization. Then, the parameters of the derived model are iteratively updated while minimizing the error between the real temperature evolution and that generated by the model being identified. For this purpose, data of the room air temperature, estimated occupancy, weather conditions, and variables of the HVAC system are assumed to be available in suitable zones of the building to apply the creation and identification processes of the model, allowing that a whole digital twin of the building is constructed. The methodology is presented by its application to a real case study: the Nimbus Research Centre building at Munster Technological University, located in Cork (Ireland). The high-fidelity simulator software TRNSYS is used for the modeling task, together with the GenOpt optimization program. The results demonstrate that the proposed methodology yields a highly accurate model of the building, capable of representing reality with RMSE values consistently below 0.6 C ∘ during open-loop validation periods of up to four days. The findings suggest that this methodology may outperform other modeling techniques reported in the literature. Importantly, the proposed technique is less complex and time-consuming to implement than many of the alternatives. • Thermal modeling of existing buildings avoiding the use of architectural metadata. • Novel integration of grey-box modeling methods with high-fidelity simulators. • The proposed method copes with the drawbacks of the models found in the literature. • Methodology validated with experimental data from the Nimbus Centre (Ireland). • Results show high accuracy of greatly simplified models—RMSE<0.6 °C in 4-day horizons. [ABSTRACT FROM AUTHOR]

High-rise buildings consume more energy and have greater environmental impacts, emphasising the need to adopt best practices during the design stage concerning BIM employment. However, despite strong support from the literature, little is known about the applications of BIM in high-rise buildings at the early design stage. Therefore, this paper aims to provide a holistic understanding of the current applications of BIM in high-rise buildings by analysing 60 studies. The findings identified seven research themes, including studies that used BIM for i) optimising building energy efficiency design; ii) collaborative design and planning; iii) life-cycle assessment; iv) designing net-zero energy buildings; v) integrating BIM with smart technologies for designing high-rise buildings; vi) cost analysis, and vii) structural design of high-rise buildings. Furthermore, this study highlights a number of challenges hindering the widespread application of BIM, alongside providing potential directions for the future development of BIM employment in high-rise buildings. [Display omitted] • A systematic review of BIM applications in high-rise buildings was conducted • Seven domains of BIM applications were identified • Challenges hindering widespread use of BIM in high-rise buildings were highlighted • Directions for future development of this research area were recommended [ABSTRACT FROM AUTHOR]

Zero-energy buildings have attracted interest worldwide as they consume less energy and can alleviate energy shortages caused by rapid economic development. This paper presents a review of the research and development regarding zero-energy buildings in China. First, it briefly introduces the evolution of the definition of zero-energy buildings and discusses the key influencing factors of such buildings in China. Then, envelope design, selection of mechanical and electrical equipment, and solar energy utilization aspects of zero-energy buildings are examined. Additionally, this paper discusses the development and application of zero-energy buildings in China, including project types, design methods, energy resources allocation, and energy operation management. Finally, this paper analyzes China's policies for zero-energy buildings, including incentive mechanisms, laws and regulations, and problems encountered, and provides suggestions for promoting zero-energy buildings in China. We expect this review to identify gaps and future directions for research and development, which will lead to new technologies, methods, policies, and standards that can be applied to zero-energy buildings. • Research and development of zero energy building in China is comprehensively reviewed. • Influencing factors and relevant zero-energy building design components are examined. • Development and application of zero-energy buildings in China are examined. • Zero energy policies in China are analyzed and suggestions for the promotion of zero-energy buildings are provided. [ABSTRACT FROM AUTHOR]

The thermal performance of building envelopes, including heat insulation performance and dynamic property in multiple heating operation conditions, was concentrated on this paper. The north wall of the experimental building has four kinds of envelope constructions, and thereby marked as the external insulation wall, internal insulation wall, intermediate insulation wall and solid brick wall, the lengths of which are all 650 mm in square. Results shown that the external insulation wall had the highest inner surface temperature and achieved the best indoor thermal comfort in the process of continuous heating, while the internal insulation wall had the fastest inner surface temperature change and obtained the best indoor thermal comfort during intermittent heating condition. Moreover, the closer to indoor low energy storage materials, the better thermal performance and energy efficiency of the envelope construction would achieve. [ABSTRACT FROM AUTHOR]

At present, many industrial parks promote the local economic growth, causing environmental pollution and waste of resources. Based on analyzing the 23 factors affecting industrial parks’ building energy efficiency and environmental protection by conducting a questionnaire survey and applying the principal component analysis (PCA) with SPSS 19.0 software as auxiliary tool, this paper identifies the 6 key influencing factors such as energy resources of the industrial park, energy recycling (waste heat) of the industrial park, renewable energy utilization of the industrial park, investment in the aspect of energy efficiency and environmental protection of industrial park, technology development and introduction in energy efficiency and environmental protection of industrial park. Some countermeasures and suggestions for promoting the industrial parks’ building energy efficiency and environmental protection are put forward, such as perfecting laws, incentive policies and implementation mechanisms of energy efficiency and environmental protection, and optimizing the parks’ energy structure and effectively utilizing resources. The research results are helpful to promote high-quality economic growth of Shenyang’s industrial parks. [ABSTRACT FROM AUTHOR]

A thorough assessment is critical for understating and enhancing building energy performance. This paper presents a three-level energy performance assessment method for information-poor buildings where very limited energy use data are available. Using this method, the energy performance of a building can be assessed at multiple levels (i.e., building level, system level and component level ) based on limited energy use data and few in-situ measurement and/or catalogue data of air-conditioning systems. The core part of this assessment method is a quantitative energy performance calculation method that consists of two basic energy balances, simplified models of air-conditioning components and an optimization algorithm based on the energy balances within buildings. The proposed assessment method is well validated in a high-rise building in Hong Kong by comparing the energy performance data from the proposed method with that from detailed measurements. Results show that this method can estimate the energy performance indicators quantitatively at three levels with acceptable accuracy. [ABSTRACT FROM AUTHOR]

This paper presents an optimization model to identity the best set of retrofitting measures applied to four different regions of Portugal; Lisbon, Porto, Bragança and Évora. The main objective is to maximize the annual energy savings, expressed in Euros, while minimizing the initial investment expressed also in Euros, considering the retrofit strategies as decisions variables and evaluating their effect in the usage of space heating and cooling and costs, depending on the chosen technology. A multi-objective genetic algorithm coded in MATLAB © to solve the optimization problem. Different energy efficiency measures are considered, such as the improvement of U-values in external walls and windows through the application of insulation materials, the change of lighting fixtures and refrigerator model to reduce the electricity consumption, and the usage of PV panels for self-consumption, and the use of Heat Pumps for space heating and cooling. The fitness function is subjected to different constraints related with the fulfillment of the demand, the physical limitation of household space, the capacity to comply with the heating and cooling needs, and the non-negativity nature of the variables. The best set of retrofitting options are presented, the budget to implement them and the amount of achieved energy savings. [ABSTRACT FROM AUTHOR]

In this paper, a representative office building zone with an electrochromic (EC) glazed façade was simulated in TRNSYS and Radiance/Daysim for a large number of different combinations of design parameters (i.e. location, façade orientation, window control, window-to-wall ratio, internal gains, thermal mass and envelope air tightness). Results of energy consumption, peak energy demand, useful daylight index (UDI) and predicted percentage of persons dissatisfied (PPD) for a total of 7680 scenarios were obtained and used in a sensitivity analysis considering the Main effect of the building parameters. The relative influence of the parameters is presented and the different designs improving the outputs are determined. Results have shown that the greatest total energy savings considering EC windows are for warmer climates with higher solar radiation exposures. The presence of an EC window mostly influences the cooling peak load and acts as an alternative solution to thermal mass from the perspective of peak reductions. While the choice of the specific window control strategy is having a limited impact on the energy savings and peak load reductions, the analysis revealed that this parameter has a larger impact on the visual comfort (UDI). The use of smart window does not appear to greatly influence the thermal comfort within the zone (small impact on the PPD). [ABSTRACT FROM AUTHOR]

Building sector accounts for significant portion of total final energy use in most countries. One way to reduce significantly building energy consumption is to adopt energy efficiency technologies and strategies. Due to environmental concerns and high cost of energy in current years there has been a renewed interest in building energy efficiency. Advanced control strategies provide a more efficient way of minimizing energy demand of buildings and maintaining indoor environmental quality in accordance with global principle of sustainability, which has also proven reliable for diverse applications such as Heating, Ventilation and Air Conditioning (HVAC) control and thermal comfort control etc. The objective of this paper is to review the control strategies in buildings, particularly focusing on low energy buildings (LEB), in recent 10 years. Present work consists of why to use control strategies in buildings, categories of control strategies, research literature for building performance affected by diverse control strategies from the perspective of theoretical modelling, physical experimental study and numerical simulation investigation. Following that, more than 20 parameters affecting control performance have been analyzed and evaluated. The literature has illustrated that the best overall performance of control strategy is proportional integral derivative control-model predictive control (PID-MPC); the effects of those parameters on control performance are completely different, depending on which exact initial conditions and the interaction between different factors. [ABSTRACT FROM AUTHOR]

Climatic zoning for building energy efficiency applications is a key element in many programs and policies to improve thermal performance of buildings. In spite of its importance, there is no consensus about the appropriate methodology for climatic zoning. Previous studies indicate a large variety of methods and parameters are currently used for climatic zoning: degree-days, cluster analysis and administrative divisions are some of the most widely used. This study reports and reviews results obtained with these three methodologies for Nicaragua, a small country in Latin America. Results indicate a high level of agreement between the different methodologies, but they also disagree on the appropriate classification of a significant proportion of the country (37% of Nicaragua’s territory). The three methodologies have strengths and weaknesses, and at present it is impossible to conclude which one is the most appropriate to support building energy efficiency programs and policies. Results of this paper highlight the need for procedures and performance indicators to assess the validity of climatic zoning (which shall be addressed by future studies). [ABSTRACT FROM AUTHOR]

Building-integrated photovoltaic (BIPV) windows provide the benefits of generating electricity, reducing building cooling and heating energy consumption, and efficiently utilizing daylight simultaneously. In this paper, the overall energy performance of a PV double skin façade (PV-DSF) and a PV insulating glass unit (PV-IGU) is studied through comparative experiments on a test rig in Hong Kong. The PV-DSF means ventilated PV-DSF by default, if not special mentioned. It is found that the average solar heat gain coefficients (SHGCs) of the PV-DSF and the PV-IGU are 0.152 and 0.238, while the U-values are 2.535 W/m 2 K and 2.281 W/m 2 K. The results indicate that the PV-DSF has better performance than PV-IGU in reducing solar heat gains, while it has worse performance regarding thermal insulation. With a lower PV module temperature, the energy conversion efficiency of PV-DSF is 1.8% better than PV-IGU. Simulation models for the PV-DSF and the PV-IGU are developed and validated against experimental data. Using the validated models, the overall energy performances of PV-DSF and PV-IGU in five different climates of China are investigated. The results show that the average energy saving potential of the PV-DSF and the PV-IGU are 28.4% and 30%, respectively, compared to the commonly used insulating glass window in five different climates. On average, the performance of PV-IGU was 2% better performance than the ventilated PV-DSF in the five representative cities. However, if an appropriate ventilation control scheme was adopted, PV-DSF can have a much better performance than the PV-IGU. The models developed in this study can be used for selecting suitable PV windows in the design process, and the results achieved can be used as a guideline for utilizing PV windows in different climates. [ABSTRACT FROM AUTHOR]

The advanced air distribution methods such as displacement ventilation and personalized ventilation attempt to seek a balance between better indoor air environment and energy efficiency. However, multiple demand scenarios including variable locations of occupants and indoor sources may exist in daily operation of the ventilation system. Most of existing airflow patterns are single mode and cannot always be efficient when responding to changeable scenarios. In this paper, a novel ventilation strategy, i.e., multi-mode ventilation (MMV), is proposed to address multiple scenarios. MMV is designed by the combination of several single airflow patterns and aims to utilize the individual advantages of each airflow pattern in controlling specific scenarios. The energy saving potential of MMV is demonstrated by numerical studies of a meeting room. An indexed local cooling load (LCL) is adopted to evaluate the performance of airflow patterns. As a key parameter in LCL calculation, the required supply temperature to maintain the set temperature at the target zone is determined by computational fluid dynamics (CFD) method. The results show that each single airflow pattern can only be efficient for part of 8 scenarios. MMV performs better by combining single airflow patterns 1 and 2 regardless of the changes of the location and magnitude of the occupied zone as well as the location of the heat source. MMV achieves a reduction rate of up to 56.8% in cooling load compared with airflow pattern 4. MMV may provide a reference for real projects in controlling temperature, humidity and contaminant concentration under changeable scenarios. [ABSTRACT FROM AUTHOR]