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• A novel MOF-based paper sheet was developed for passive indoor moisture control. • The MOF paper sheet has excellent moisture buffer capacity and mechanical properties. • A numerical model was developed to find the optimal thickness of the MOF paper sheet. • The energy-saving potential of wallpaper made of MOF paper sheet was investigated. Passive indoor moisture control is a meaningful way to reduce HVAC operation and improve building energy efficiency. Metal-organic frameworks (MOFs) have been considered one of the most promising sorbent materials for passive indoor moisture control. However, the powder form of MOF is challenging to use in the built environment. Typical shaping methods like pellets, beads, and coating can lead to problems like partial pore blocking, insufficient mechanical stability, amorphization, and low material utilization. Here, we report a new sustainable MOF paper sheet comprising 25% cellulosic fibers and 75% MOF MIL-100(Fe) powder. The porous polymer matrix provides good support and fixation for MOF particles, so it's more applicable in the built environment. The crystalline and pore structure characteristics of the MOF in the membrane are well preserved. Hydro characteristic test results show that MIL-100(Fe) paper sheet has high water vapor uptake, S-shape isotherm, mild regeneration condition, and high MBV. Then, a numerical model was developed to calculate the relation between a material's MBV and its thickness. MIL-100(Fe) paper sheet with the most efficient thickness was applied as wallpaper in a building energy simulation model. The simulation result shows that the MIL-100(Fe) paper sheet is promising for passive indoor moisture control. It can remove about 45%-55% of the latent cooling load in most European climate types. [ABSTRACT FROM AUTHOR]

To align the buildings sector with the 1.5°C climate change trajectory, enormous improvements in energy efficiency are needed. It is therefore crucial that the tools used to evaluate buildings' energy use undergo robust testing. This paper tests, for the first time, the outcome of the Passive House Planning Package (PHPP) and an author-modified version of the Radiant Time Series Method (RTSM), following the Building Energy Simulation Test (BESTEST). The results show that while the validity of the modified-RTSM is slightly superior to that of the PHPP, both tools pass less than 35% of the cases -- necessitating further calibration and challenging the widely-held belief that the PHPP is 'validated'. As the PHPP and the modified-RTSM present a relatively simple and quick way of evaluating buildings' energy performance, calibrating their methodologies so they pass the BESTEST cases could put them at an advantage over the fully dynamic and resource-intensive tools. [ABSTRACT FROM AUTHOR]

Lightweight concrete offers numerous advantages for modular construction, including easier construction planning and logistics, and the ability to offset additional dead loads induced by double-wall and double-slab features. In a previous study, authors proposed incorporating lightweight aggregate into foamed concrete instead of adding extra foam to achieve lower density, resulting in lightweight concrete with an excellent strength-to-density ratio. This paper further investigated the performance aspects of foamed concrete with lightweight aggregate beyond mechanical strength. To evaluate the effect of aggregate type and foam content, three mix compositions were designed for the lightweight concrete. Specimens were prepared for experimental tests on thermal conductivity and drying shrinkage of lightweight concrete. Results showed that while both the increase in foam volume and the incorporation of lightweight aggregate led to higher drying shrinkage, they also contributed to improved insulating properties and reduced potential of cracking. Using typical multi-storey modular residential buildings in Hong Kong and three other Chinese cities as case studies, simulations were performed to assess potential savings in annual cooling and heating loads by employing the proposed lightweight concrete. These findings demonstrate the practical benefits of using foamed concrete with lightweight aggregate in modular construction and provide valuable insights for further optimization and implementation. [ABSTRACT FROM AUTHOR]

Featured Application: Our study introduces an innovative application through the deployment of the Totem Outdoor DELUX interactive kiosk, complemented by a user-friendly web application. This dual-component system is not solely a cutting-edge piece of smart furniture centered on hardware; it also encompasses a specially designed web application to engage the citizens of Balaguer. Together, they form a comprehensive infrastructure aimed at enhancing environmental awareness and promoting civic participation. This kiosk is a dynamic platform for displaying real-time data from sensors across the city, facilitating interactive questionnaires, and providing essential information about the city and town hall. The application of this technology directly contributes to several Sustainable Development Goals (SDGs) by fostering public awareness and participation in critical issues such as climate action, health and well-being, gender equality, innovation in infrastructure, and reducing inequalities. Specifically, the interactive totem allows for the collection and analysis of data regarding citizens' perceptions of their living conditions, environmental impact, and social inequalities. This practical application of our work exemplifies how technological innovation can be leveraged to enhance civic engagement, support sustainable development, and foster a more informed and participatory urban community. The concept of a smart city is becoming increasingly popular to improve citizens' quality of life. Institutions are also committed to enhancing the sustainability of cities by implementing the Sustainable Development Goals (SDGs). This paper presents a Balaguer case study investigating energy demand monitoring, decreasing energy demand, and citizen acceptance in a municipality district. The study collected data from three sources: (1) quantitative data coming from on-site sensors; (2) quantitative data from a simulation of the area; and (3) qualitative data from questionnaires developed with a totem located in the city center. This study shows the importance of citizen science in contributing towards the increased awareness of energy demand, renewable energy, and climate change. But it also shows how citizen science can improve research quality involving the municipality authorities. This study also was instrumental in contributing to the increase in awareness among municipality authorities and capacity building on the topic. This activity may also contribute towards the implementation of actions to reduce the energy demand in public buildings and helping them in deploying policies to decrease energy demand in buildings, increase the use of renewable energy, and increase awareness among citizens. The government will use the information gathered to develop policies for citizen improvement. [ABSTRACT FROM AUTHOR]

Reducing heat losses through the building envelope is one of the most important aspects to be met if the targets set by the European Union are to be achieved. In order to obtain a more realistic energy demand, dynamic heat transfer simulations are used to calculate the energy consumption of buildings, since steady-state calculations do not take into account the thermal mass in buildings. These dynamic simulations employ methods based on analytical models since numerical models are unsuitable for longer time periods. The analytical models used herein fall into the category of conduction transfer functions (CTFs). Two methods for computing CTFs that are addressed in this research are the Laplace method and the State-Space method. The objective of this paper is to verify the efficiency of the Laplace and State-Space methods for calculating the energy demand of a building in the case of heavyweight building elements and shorter sampling times, and to provide a means for improving the algorithms used by these methods. The Laplace and State-Space method algorithms were implemented in Mathematica, and the results were compared to EnergyPlus and TRNSYS, which use similar algorithms to calculate energy demand. It was shown in this paper that for the heavyweight wall element and a time step of 0.25 h, the difference between the total energy transferred through the inner surface was about 31% for EnergyPlus and 78% for TRNSYS compared to the reference solution. For the lightweight wall element, the results were stable for the time step of 0.25 h, but for the time step of 0.1 h, the differences were 45.64% and 303% between EnergyPlus, TRNSYS and the reference solution, respectively, compared to the State-Space and Laplace methods for which the maximum difference was 12.03% with a time step of 0.1 h. While dynamic heat transfer simulations are better than calculations based on steady-state boundary conditions, they also have their limitations and could lead to unsatisfactory results for short sampling times and if not applied properly. [ABSTRACT FROM AUTHOR]

The climate data used for dynamic energy simulation of buildings located in urban regions are usually collected in meteorological stations situated in rural areas, which do not accurately represent the urban microclimate (e.g., urban heat island effect), and this might affect the simulation accuracy. This paper aims at quantitatively evaluating the effects of heat island on a high-rise building's energy performance based on the microclimate simulation tool ENVI-met and the building energy simulation tool COMFIE. However, the computation of microclimate models is time consuming; it is not possible to simulate every day of a year in a reasonable time. This paper proposes a method that generates hourly "site-specific climate data" to avoid long microclimate simulation times. A coupling method of ENVI-met and COMFIE was developed for more precise building energy simulation, accounting for the heat island effect. It was applied to a high-rise building in Wuhan, China. The results showed that the yearly average urban heat island effect intensity at the height of 3 m was estimated to be 0.55 °C and decreased with height. Compared to the simulation considering the outdoor temperature variation with the height and orientation, using the original climate data collected in rural areas led to an overestimation of the heating load by around 5.8% and an underestimation of the cooling load by around 8.7%. Compared to the weather file at the height of 3 m near the north facade neglecting the temperature variation along the height, the heating load was overestimated by 8.2% and the cooling load was underestimated by 10.8%. The methods proposed in this paper can be used for the more precise application of urban building energy simulation. [ABSTRACT FROM AUTHOR]

The process of urbanization resulting from population growth is causing a transformation of natural landscapes into built environments, and contributing to a significant rise in air and surface temperatures in urban areas, resulting in what is known as the urban heat island (UHI). Ignoring the UHI effect and use of weather data from open fields and airport locations for energy and thermal comfort analysis can lead to over- and underestimation of heating and cooling loads, improper sizing of equipment, inefficiencies in the mechanical systems operation, and occupants' thermal discomfort. There is a need for computationally efficient urban canopy temperature prediction models that account for the urban morphology and characteristics of the study area. This paper presents the development and application of an artificial neural network (ANN)-based method for generating hourly urban canopy temperature and local wind speed for energy simulation. It was used to predict the urban canopy temperature of a neighborhood in downtown Vancouver and the resulting building energy consumption and indoor temperature in a typical building in the area. The results showed that the UHI effect increased the total cooling energy demand by 23% and decreased the total heating energy consumption by 29%, resulting in an overall negative effect on the total energy demand of the building, which was 18% higher in the urban area. The UHI effect also increased the number of hours of indoor temperature above the cooling set point by 7.6%. The methodology can be applied to determine the urban canopy temperature of neighborhoods in different climate zones and determine the varying urban heat island effects associated with the locations. [ABSTRACT FROM AUTHOR]

This paper presents controlling and optimizing the energy performance of buildings using smart shadings. Simulations are carried out using EnergyPlus and multi-objective optimization is performed by jEPlus+EA through NSGA-II algorithm. Optimization of control strategies is performed for a typical office room on the middle floor of a building in Tehran. Slat angle, solar radiation, and the material of smart windows are selected as decision variables. Also, the annual total building energy consumption, the predicted percentage of dissatisfaction (PPD), and the discomfort glare index (DGI) are considered as three objective functions minimized simultaneously. The weighted sum method to select the final answer of Pareto solutions is used. In the first strategy, a comparison of the results of optimization with the initial values when the angles of slats are constant and equal to 45 °showed that the total annual energy consumption, DGI, and PPD indexes reduced up to 11.74%, 6.4%, and 46.6%, respectively. In the second strategy, the reductions were 28.73, 56.50, and 34.05%, respectively, in comparison with the double-glazing window. The results clearly show how the correct selection of architectural parameters and control strategies can greatly prevent energy losses while providing the thermal and visual comfort of the building occupants. [ABSTRACT FROM AUTHOR]

Hygrothermal properties of building materials, climatic conditions and energy performance are interrelated and have to be considered simultaneously as part of an optimised building design. In this paper, a new approach to evaluate the energy consumption of residential buildings in Morocco is presented. This approach is based on the effect of coupled heat and moisture transfer in typical residential buildings and on their responses to the varied climatic conditions encountered in the country. This approach allows us to evaluate with better accuracy the response of building energy performance and the indoor comfort of building occupants. Annual energy consumption, cooling and heating energy requirements were estimated considering the six climatic zones of Morocco. Based on the results, terms related to coupled heat and moisture transfer can effectively correct the existing energy consumption calculations of the six zones of Morocco, which currently do not consider energy consumption due to coupled heat and moisture transfer. [ABSTRACT FROM AUTHOR]

Building's energy and water consumption and associated utility costs can be significantly reduced if proper energy and water-efficiency upgrades are applied. Due to the limitations of the upgrade budgets and the availability of a wide range of energy and water-efficiency measures, decision makers are always faced with a challenging task to identify optimal sets of building upgrade measures. This paper presents the development of a new model that is capable of identifying an optimum selection of building upgrade measures to minimize equivalent annual cost (EAC) while maintaining the performance of existing buildings and complying with available upgrade budgets. The model is developed in three main phases: (1) formulation phase, where decision variables, objective function, and constraints are identified and formulated; (2) implementation phase that performs the model computations and specifies the model input and output data; and (3) performance evaluation phase where two case studies of university buildings are analyzed to demonstrate the capabilities of the model. Furthermore, a case study from the literature is used to verify the model performance and document its new capabilities. The primary contributions that this research adds to the body of knowledge are: (1) developing new model that can identify optimal selection of building upgrades while complying with user-specified requirements for building operational performance and available upgrade budgets in short computation time, (2) modeling a wide range of upgrade measures for building fixtures and equipment as well as envelope components, and (3) integrating updatable databases from vendors and suppliers to generate up-to-date and practical recommendations. The model is designed to use OpenStudio to analyze combinations of feasible alternatives such as HVAC systems, wall and roof insulations, window types, and water heaters to calculate the corresponding building energy consumption. The model is designed to perform its computations using binary linear programming to identify global optimum solutions in short computational time. The results of the case studies illustrated the capabilities of the model in optimizing building upgrade measures to reduce the building utility costs up to 38% while complying with specified upgrade budgets. [ABSTRACT FROM AUTHOR]

Climate change and its effects are becoming clear on a global scale either from the perspective of global warming and the increase in the rate of occurrence of weather events of extreme magnitude. This has impacts also for sure on the standard building performance analysis approach, since the buildings designed today are supposed to withstand for the following decades climate impacts that may be different than those they were designed for.The paper proposes a simple, easy to use and freely available building simulation utility which performs morphing of existing weather data files and, by connecting to the Energy Plus simulation routine, allows to perform future climate building simulation analyses. Users are required to select one of the ASHRAE buildings models or provide one of their own choosing and to input the original weather data file. The tool will generate a future weather data file with the preferred assumptions (e.g. RCP scenarios, time frame) and elaborate results in terms of heating and cooling required for air conditioning.The paper proposes also an implementation of the tool to a case study aimed at showing the potential of the application proposed. A typical office building model from the ASHRAE library was simulated in two different locations under different climate change assumptions up to the year 2090. The analysis of the results in the two locations of Palermo (Italy) and Copenhagen (Denmark) highlight relevant increases in the current century of up to +20% of cooling requirements and similar reductions for heating in both case studies, if compared to current levels.The research targets a specific limit in the investigation of climate resilience of buildings and follows the principles described by SDSN in the definition of SDGs and the interest at the EU level towards climate neutral and innovative cities.In this context, the paper may contribute to the limited availability of easy to use and free tools available for practitioners to investigate the design of climate resilience buildings.

Double skin façades are façade technologies that have the perspective of reducing energy use and improving comfort in buildings due to their adaptable nature. Exhaust-air façades offer the possibility to utilize solar energy by recovering heat from the façade cavity. However, the cavity overheating can be detrimental on the summer performance. Predicting performance and optimizing the system during the design phase is a challenge, especially when the cavity-air is integrated into the HVAC system. Whole-building energy simulation (BES) software tools are an adequate tool for calculating whole building performance, although these can have limitations in the accurate replication of complex building elements. The paper analyses the available and applied modelling approaches within a BES tool, and compares the outputs in terms of cavity temperature, horizontal and vertical temperature profiles, and heat flux through the façade. The sensitivity of the results on the modelling approach is evaluated. Results can serve as a guide for practitioners on the selection of the modelling approach for a given task. [ABSTRACT FROM AUTHOR]

As the built environment is among the main contributing sectors to climate change, it is needed to investigate new paradigms to push decarbonization efforts towards the ambitious objectives defined internationally. It is a shared understanding that shifting the perspective from the single building to the district perspective is required to fully take into consideration the complexity of all interactions undergoing within the built environment, thus the concept of Positive Energy District emerged as a district with annual net zero energy import and net zero CO 2 emission working towards an annual local surplus production of renewable energy. In this framework, this paper explores the investigation of the potential for achieving the level of Positive Energy District in a group of non-residential buildings in Balaguer, Catalonia, Spain. These buildings, occupying 8,825 m2 in the city centre, require significant refurbishment for improved energy performance. The analysis includes building energy modelling and simulation, renovation studies, several alternative balance calculations, and carbon emissions assessment. The paper also considers mobility and embodied energy and their impact on energy/carbon balances. The results show that Positive Energy Districts carbon and primary energy balances are not met with rooftop PV installations when retrofitting an existing district towards the Positive energy target but further significant PV areas (roughly + 50%) are required to meet merely the use stage balances: negative results are traced when mobility and embodied energy are computed. A formulation alternative to the simple mathematical balance to facilitate the diffusion of Positive Energy District as catalyst of urban decarbonisation could be needed, including context factors and alternative systems (e.g., rating systems). [ABSTRACT FROM AUTHOR]

Recently, there has been a growing interest in sustainable agricultural methods aimed at reducing energy consumption and mitigating environmental impacts. Among these methods, the integration of rooftop greenhouses into buildings has emerged as a promising solution for urban agriculture, offering various advantages such as energy-saving effects on both the host building and the rooftop greenhouse, improved resource use efficiency, enhanced food security, and reduced environmental impacts. However, there has been limited research on the energy-saving impact of rooftop greenhouses under different conditions and detailed heat transfer analysis based on actual buildings and rooftop greenhouses. The objective of this study is to investigate the energy benefits of building-integrated rooftop greenhouses by evaluating various operating scenarios for both the building and the greenhouse. A container and upper rooftop greenhouse structure were constructed, and building energy simulation models for the target system were developed. Four different operating scenarios for the greenhouse and three different operating scenarios for the building were compared. Depending on the operating scenarios, the total energy loads of the container and RTG were reduced by 18.4% to 24.7% and 0.7% to 6.3%, respectively. The findings of this study can be utilized for the development of optimized greenhouse control strategies. [ABSTRACT FROM AUTHOR]

The impacts of climate change, excessive greenhouse gas emissions, and the current energy crisis have motivated the European Union to adopt mitigation and adaptation strategies. These strategies primarily focus on the building sector due to its crucial role in addressing these issues. Among the strategies, the implementation of resilient technologies for the building envelope, such as vertical greenery systems (VGSs) is gaining ground. The literature analysis shows that existing models are not sufficiently detailed in their description of the overall thermo-physical phenomena of VGSs. The aim of this work is to overcome the research gaps by selecting and improving two mathematical models for green façades and living walls. A dedicated calculation code to estimate the effect of VGSs on a building's energy performance and indoor thermal comfort has been developed and implemented within the EnergyPlus calculation software (version 23.2). A BESTest Case from ASHRAE 140 was chosen to test the models and to assess benefits of VGSs. The results show that adopting green solutions for the building envelope can contribute to achieving the building's energy efficiency goals and that the modelling of these technologies can be easily carried out within a dynamic energy simulation of the building. [ABSTRACT FROM AUTHOR]

• A theoretical framework is proposed to consider non-equilibrium configurations at the macroscopic scale. • The new formulation is validated using a full dual-scale model of coupled heat and mass transfer. • With the new model, a very good accuracy is obtained with a huge reduction of CPU time. • Dual-scale diffusion and molecular relaxation can be considered additively in the modified macroscopic formulation. • This framework can be applied to other configurations, such as coupled transfer in packedbeds. This paper proposes a macroscopic formulation of coupled heat and mass transfer that can consider non-local equilibrium often encountered in biosourced building materials (wood- and plant-fiber based materials). Transferring dual-scale effects and molecular relaxation at the macroscopic level involves a kernel function acting in a convolution product. To ease the computational solution of the set of equations, the memory function is decomposed as a series of exponential functions. Each function yields an internal variable that obeys a simple ordinary differential equation (ODE). This paper first describes the macroscopic and dual-scale formulations used as reference solutions. Subsequently, the modified macroscopic formulation of coupled transfer and its computational solution are presented in detail. The major outcomes of the present study, validated against reference solutions obtained with a comprehensive dual-scale model, are as follows: • Dual-scale diffusion can be approached accurately by two exponential functions, • Even though the dual-scale phenomenon and molecular relaxation do not occur at the same scale, both can be considered in the modified macroscopic formulation of coupled transfer additively, • The new macroscopic formulation, together with the computational procedure proposed in this study, can be applied to various configurations, namely coupled heat and mass transfer in packed beds. [ABSTRACT FROM AUTHOR]

Highlights • A new experimental procedure to test PCM-enhanced components is presented. • A modified Dynamic Heat Flow Meter Apparatus is used to perform the tests. • The thermal conductivity of PCMs is measured in different phases (solid-liquid). • Indications to solve the issues related to building PCM-specimens are provided. Abstract The implementation, in Building Performance Simulations (BPS) tools, of robust models capable of simulating the thermophysical behaviour of a Phase Change Material (PCM) represents a fundamental step for an appropriate thermal evaluation of buildings that adopt PCM-enhanced envelope components. Reliable and robust measuring procedures are essential, at a material and component level, to provide experimental data for the empirical validation of software tools. The traditional laboratory tests that are generally used for the validation of models present some limitations, because PCMs are usually subjected to conditions that may be very different from the real boundary conditions of the building components in which PCMs are applied. Furthermore, in many experimental full-scale mockups, the relatively small quantity of installed PCM and the combination of several thermal phenomena do not allow software tools to be tested in a reliable way. In this paper, an experimental procedure, based on a modified Heat Flow Meter Apparatus, has been developed to test the behaviour of PCM-enhanced components; the procedure, which is based on the measurement of the sinusoidal response, has been set up to provide data for the comparison and testing of numerical models and of BPS tools. Moreover, general indications and guidelines are provided to solve some issues related to building specimens that contain bulk PCM in order to obtain a more accurate measurement of their performance. The experimental results presented in this paper were obtained from two different bulk PCMs (organic and inorganic). It was found that it is important to evaluate different PCM typologies and different thermophysical boundary conditions, including partial and full phase transitions, to test simulation codes that implement PCM modelling functions. In fact, some phenomena, such as hysteresis and subcooling effects are more evident when partial phase transition takes place. The results related to the characterization of the thermal conductivity of a paraffin-based PCM have shown a significant increase (up to 42%) of the equivalent thermal conductivity from a solid to a liquid state, with an upward heat flux, thus highlighting that further investigations and improvements are needed to measure the equivalent thermal conductivity in the different PCM phases. [ABSTRACT FROM AUTHOR]

Abstract Building Information Modeling (BIM) initially emerged as a capability to transfer information and allow interaction or interoperability of various software tools used for architectural, structural, mechanical, electrical design, and building construction. Its application from developing 3D models, structural analysis, cost estimation, and mechanical analysis has now expanded to other applications such as energy simulation. Multiple computer-aided design (CAD) tools work as BIM authoring tools to generate BIM files in different formats containing various types of building information. In addition, there are various building energy modeling (BEM) tools capable of importing these BIM files to perform energy simulation. However, such tools have various capabilities and limitations and need to be investigated and categorized in order to facilitate choosing a proper tool for design professionals in different phases of project and purposes. In addition, interoperability and data exchange issues between BIM and BEM tools should be understood in order to find solutions such as developing proper corrective middleware tools to rectify them. This paper reviews the challenges, issues, and shortcomings in BIM-to-BEM interoperability process (BBIP) by proposing a detailed classification for these issues and studying the available solutions. The paper also explains how a corrective middleware, which is developed by the authors using Python, can be utilized to modify a gbXML file prior to adoption in energy simulation to resolve the issues related to building envelope in BBIP. To do so, initially a review is presented on research studies focused on different types of BIM schemas such as IFC and gbXML and energy simulation tools capable of reading these files such as Green Building Studio (GBS), DesignBuilder, Integrated Environmental Solutions-Virtual Environment (IES), and OpenStudio. In addition, some of the challenges in the application of BIM for energy simulation such as interoperability issues, lack of standards, and lack of easy solutions for extending existing BIM schemas and available corresponding solutions are also reviewed. With the focus on building envelope in mind, three case studies are discussed to observe the challenges and issues with respect to BBIP using Revit, GBS, and OpenStudio. Moreover, these case studies provide an opportunity to investigate the application of corrective middleware tools similar to what is developed in the study presented. Highlights • A brief review of Building Energy Modeling (BEM) tools is provided • Building Information Modeling (BIM) file types are reviewed and compared • Existing challenges, issues, and shortcomings in BIM to BEM interoperability process (BBIP) are identified • Existing solutions for issues in BBIP are reviewed and a corrective tool is developed and proposed to solve issues related to gbXML files involved in BBIP • A comprehensive categorization is proposed for issues in BBIP. [ABSTRACT FROM AUTHOR]

Occupancy is one of the main factors affecting building energy consumption. The occupancy data, which refer to the occupancy number in this paper, has been widely used in the building simulation field. However, due to the stochastic nature of occupant behavior, it is hard to predict and measure how many people stay in a given building. The rapid development of mobile Internet technology provides an efficient and convenient option for occupancy detection. This paper proposes a concept of typical occupancy data (TOD), which are extracted from real-time occupancy data collected by mobile devices. K -means algorithm is employed to generate the TOD data through cluster analysis. An energy performance model of an office building is used as a case study to demonstrate the effectiveness of the TOD data. [ABSTRACT FROM AUTHOR]

The building information modeling - BIM is a technology developed toward creation of computer based information model that encompasses whole building lifecycle. Toward that goal a number of information technology standards have been developed that enable different professions in AEC to cooperatively develop electronic building model. The paper gives overview of essential technologies, discusses their intended purpose, and gives outline of the currently achieved functionality. [ABSTRACT FROM AUTHOR]

Reducing heat losses through the building envelope is one of the most important aspects to be met if the targets set by the European Union are to be achieved. In order to obtain a more realistic energy demand, dynamic heat transfer simulations are used to calculate the energy consumption of buildings, since steady-state calculations do not take into account the thermal mass in buildings. These dynamic simulations employ methods based on analytical models since numerical models are unsuitable for longer time periods. The analytical models used herein fall into the category of conduction transfer functions (CTFs). Two methods for computing CTFs that are addressed in this research are the Laplace method and the State-Space method. The objective of this paper is to verify the efficiency of the Laplace and State-Space methods for calculating the energy demand of a building in the case of heavyweight building elements and shorter sampling times, and to provide a means for improving the algorithms used by these methods. The Laplace and State-Space method algorithms were implemented in Mathematica, and the results were compared to EnergyPlus and TRNSYS, which use similar algorithms to calculate energy demand. It was shown in this paper that for the heavyweight wall element and a time step of 0.25 h, the difference between the total energy transferred through the inner surface was about 31% for EnergyPlus and 78% for TRNSYS compared to the reference solution. For the lightweight wall element, the results were stable for the time step of 0.25 h, but for the time step of 0.1 h, the differences were 45.64% and 303% between EnergyPlus, TRNSYS and the reference solution, respectively, compared to the State-Space and Laplace methods for which the maximum difference was 12.03% with a time step of 0.1 h. While dynamic heat transfer simulations are better than calculations based on steady-state boundary conditions, they also have their limitations and could lead to unsatisfactory results for short sampling times and if not applied properly.

Improved energy efficiency in the building sector is a central goal in the European Union and renovation of buildings can significantly improve both energy efficiency and indoor environment. This paper studies the perception of indoor environment, modelled indoor climate and heat demand in a building before and after major renovation. The building was constructed in 1961 and renovated in 2014. Insulation of the façade and attic and new windows reduced average U-value from 0.54 to 0.29 W/m²•K. A supply and exhaust ventilation system with heat recovery replaced the old exhaust ventilation. Heat demand was reduced by 44% and maximum supplied heating power was reduced by 38.5%. An on-site questionnaire indicates that perceived thermal comfort improved after the renovation, and the predicted percentage dissatisfied is reduced from 23% to 14% during the heating season. Overall experience with indoor environment is improved. A sensitivity analysis indicates that there is a compromise between thermal comfort and energy use in relation to window solar heat gain, internal heat generation and indoor temperature set point. Higher heat gains, although reducing energy use, can cause problems with high indoor temperatures, and higher indoor temperature might increase thermal comfort during heating season but significantly increases energy use. [ABSTRACT FROM AUTHOR]

The climate data used for dynamic energy simulation of buildings located in urban regions are usually collected in meteorological stations situated in rural areas, which do not accurately represent the urban microclimate (e.g., urban heat island effect), and this might affect the simulation accuracy. This paper aims at quantitatively evaluating the effects of heat island on a high-rise building’s energy performance based on the microclimate simulation tool ENVI-met and the building energy simulation tool COMFIE. However, the computation of microclimate models is time consuming; it is not possible to simulate every day of a year in a reasonable time. This paper proposes a method that generates hourly “site-specific climate data” to avoid long microclimate simulation times. A coupling method of ENVI-met and COMFIE was developed for more precise building energy simulation, accounting for the heat island effect. It was applied to a high-rise building in Wuhan, China. The results showed that the yearly average urban heat island effect intensity at the height of 3 m was estimated to be 0.55 °C and decreased with height. Compared to the simulation considering the outdoor temperature variation with the height and orientation, using the original climate data collected in rural areas led to an overestimation of the heating load by around 5.8% and an underestimation of the cooling load by around 8.7%. Compared to the weather file at the height of 3 m near the north facade neglecting the temperature variation along the height, the heating load was overestimated by 8.2% and the cooling load was underestimated by 10.8%. The methods proposed in this paper can be used for the more precise application of urban building energy simulation.

The paper presents an energy simulation-based study to investigate the impacts of climate change on energy consumptions of an office building located in five different cities, United States. Annual energy consumption of a medium-size office building was predicted by building energy simulation software—EnergyPlus using TMY3 weather data and future climate data. In this study, we have used two sets of further climate data with different climate models including (1) Hadley Centre Coupled Model, version 3 (HadCM3), and (2) NCAR Community Earth System Model version 1 (CESM1) with the Community Atmosphere Model version 5 (CAM5). A morphing method was applied to downscale the monthly weather forecast to hourly forecast for use in building energy simulation for the two General Circulation Models (GCMs): HadCM3 and CESM1. Using the generated future weather files, HVAC operation related mitigation measures including adjustment of thermostat setpoints, reduced HVAC operation hours, reduced VAV box minimum flow setting, and mixed-mode ventilation were simulated to compare with ASHRAE Standard 90.1 baseline simulated using TMY3 weather data. Simulation results on predicted whole building, heating and cooling energy consumptions were examined. The paper highlighted the importance of efficiently operating mechanical systems in buildings to ensure a more sustainable future. [ABSTRACT FROM AUTHOR]

To align the buildings sector with the 1.5°C climate change trajectory, enormous improvements in energy efficiency are needed. It is therefore crucial that the tools used to evaluate buildings’ energy use undergo robust testing. This paper tests, for the first time, the outcome of the Passive House Planning Package (PHPP) and an author-modified version of the Radiant Time Series Method (RTSM), following the Building Energy Simulation Test (BESTEST). The results show that while the validity of the modified-RTSM is slightly superior to that of the PHPP, both tools pass less than 35% of the cases—necessitating further calibration and challenging the widely-held belief that the PHPP is ‘validated’. As the PHPP and the modified-RTSM present a relatively simple and quick way of evaluating buildings’ energy performance, calibrating their methodologies so they pass the BESTEST cases could put them at an advantage over the fully dynamic and resource-intensive tools.

Globally, a considerable amount of energy is consumed by the building sector. The building envelope can highly influence the energy consumption in buildings. In this regard, innovative technologies such as thermal energy storage (TES) can help to boost the energy efficiency and to reduce the CO 2 emissions in this sector. The use of phase change materials (PCM), due to its high heat capacity, has been the centre of attention of many researchers. A considerable number of papers have been published on the application of PCM as passive system in building envelopes. Researches have shown that choosing the PCM melting temperature in different climate conditions is a key factor to improve the energy performance in buildings. In the present paper, a simulation-based optimization methodology will be presented by coupling EnergyPlus and GenOpt with an innovative enthalpy-temperature (h-T) function to define the optimum PCM peak melting temperature to enhance the cooling, heating, and the annual total heating and cooling energy performance of a residential building in various climate conditions based on Köppen-Geiger classification. Results show that in a cooling dominant climate the best PCM melting temperature to reduce the annual energy consumption is close to the maximum of 26 °C (melting range of 24–28 °C), whereas in heating dominant climates PCM with lower melting temperature of 20 °C (melting range of 18–22 °C) yields higher annual energy benefits. Moreover, it was found that the proper selection of PCM melting temperature in each climate zone can lead to notable energy savings for cooling energy consumption, heating energy consumption, and total annual energy consumption. [ABSTRACT FROM AUTHOR]

In this paper we propose an algorithm to find optimal design of skylight for a one-storey office building while saving source energy consumption. The algorithm simultaneously couples daylighting with energy performance and compares different ratios of skylight to floor area based on both lighting and HVAC loads. Our method integrates different simulation tools with numeric optimization and exhaustive search to find the optimal ratio. More specifically we implemented EnergyPlus as a thermal engine and Radiance as a daylight engine, both of which are embedded in Ladybug and Honeybee. As Ladybug and Honeybee is a plugin for Grasshopper, we developed the algorithm in Grasshopper environment. We used Python and Grasshopper to integrate different simulation tools and implemented two methods of numeric optimization (gradient descent) and exhaustive search (parametric analysis) in order to validate the final result. After applying the proposed algorithm for a small office building in San Francisco, both methods coincide that the optimal skylight to floor ratio is 5.5–6% while decreasing the energy demand by 19%. The experiments show that the energy efficiency only occurs for skylight ratios of 3–14%. In addition, we used sDA and UDI metrics to analyze daylighting performance of each parametric scenario. We infer that only a specific range of skylight ratios that are energy efficient (5–10%) provide adequate daylight and avoid glare. The integrative process and optimization method proposed in this paper enable designers to find a robust energy efficient skylight design. [ABSTRACT FROM AUTHOR]

Building simulation tools have been widely used for performance assessment. However, many studies [1] have reported that a performance gap exists between the reality and simulation output, mainly caused by unknown simulation inputs. Therefore, model calibration needs to be introduced. Calibration attempts can fail for the following reasons: coarse initial simulation model, long sampling time, uncertainty in the model, and sensor errors. The aim of this paper is to address the abovementioned issues. For this study, an existing office building was selected and two calibration approaches were presented: deterministic vs. stochastic. For stochastic calibration, a Gaussian Process Emulator (GPE) was introduced as a surrogate of the EnergyPlus model. The stochastically calibrated model performs better than the deterministically calibrated model. It is concluded in the paper that (1) the calibration quality is influenced by the degree of the details of the initial model, (2) the accumulated measured data under a sampling time of up to one day (e.g. gas energy consumption) might be unsuitable for calibration work due to the lack of ‘time-series trend’, and (3) the calibration quality is also influenced by sensor errors and further calibration needs to take these into account. [ABSTRACT FROM AUTHOR]

The building operation sector in China represents 22% of the national energy consumption and 22% of the carbon emission, of which urban residential buildings accounted for 24% in 2019. Such figures for the housing sector are projected to increase sharply in the near future, while China aims to peak CO2 emissions by 2030 and reach neutrality before 2060. To reduce the impacts of the urban housing sector and address the energy use and waste generated by large-scale demolition and reconstruction, the central government started promoting the energy retrofit of urban residential buildings, raising such policies to the national strategic level. Jiangsu Province is one of the most urbanised, with a rapid growth in the energy consumption of residential buildings. The Multi-Danyuan and Single-Danyuan Apartment built in 1980–1999 are the most representative residential types in its urban areas. While still adequate functionally, they were designed and built to low energy standards and show significant potential for energy retrofit. Nonetheless, their current performance and energy-saving potential are under-researched, while more detailed and reliable data would be critical to support retrofit design and policy making. This study investigates and characterises the typical use and energy performance of the two building types. Additionally, seven measures and six retrofit scenarios were identified based on the optimal energy reductions and regulations from selected countries. The simulations indicate that, without intervention, the energy consumption of the typical urban residential buildings can reach 122 kWh/m2 under the typical high-energy user scenario. By selecting a set of effective energy-saving measures, the operational energy use for heating and cooling can be reduced by up to 52.4%. Current local standards prove cost-efficient, although less effective in reducing energy use compared to international best practices, indicating potential improvements to the contribution of building retrofit towards achieving the national carbon reduction goals. [ABSTRACT FROM AUTHOR]

This study investigates the impact of an active workstation on heating and cooling energy consumption in commercial buildings. The improved performance and health of office workers are well-known and supported by several surveys and studies. However, the preferred and revised indoor air temperature for different activities of the employees, such as standing and walking, directly impacts the energy consumption of the building. Therefore, this study systematically quantifies the impact of indoor environments on building energy consumption using a simulation tool. Based on literature reviews with multidisciplinary fields, revised setpoint temperature, metabolic rate, and required outdoor air rate due to the level of active workstation (standing and walking) are applied to EnergyPlus reference building models. The impact on heating and cooling energy consumption is analyzed by considering several representative cities in the United States. Their average sensitivity was found to be 7.28% lower and 14.28% higher for heating and cooling energy, respectively. The total increment of $13,887 represents approximately 0.16% of the total profit of the corporation. This increment can be justified given the benefits to workers' health, which include lower insurance costs and improved performance. This suggests that it is economically desirable to deploy active workstations widely. [ABSTRACT FROM AUTHOR]

This publication is considered the most promising path leading to the creation of energy-efficient engineering solutions for various buildings. This path begins with the first design calculations. The foundation for creating cost-effective heating and ventilation systems is carried out at the stage of forming the heat and mass balances of the premises as building components. Besides drawing the heat and mass balances must be closely connected with the study of the geometric parameters of premises and the thermal performance of the building envelope. In this paper a special way of heat load computing of heating and ventilation systems is considered. It is shown that considered method allows refining the calculations of heat losses of the building. The application of the proposed method to determine the transmission heat losses with the elemental approach is considered. The calculating method of ventilation heat losses with different variations of accounting the infiltration component is shown. Way of the joint account of heat energy consumption factors in a single mathematical apparatus is presented. The method of optimizing of heat loads during extreme operating conditions is reviewed. The paper shows further way application of accurate method in the design of buildings and the results of calculations. Some conclusions are suggested as a conclusion of this article. [ABSTRACT FROM AUTHOR]

Building energy models (BEMs) are typically used for design and code compliance for new buildings and in the renovation of existing buildings to predict energy use. The increasing adoption of BEM as standard practice in the building industry presents an opportunity to extend the use of BEMs into construction, commissioning and operation. In 2009, the authors developed a real-time simulation framework to execute an EnergyPlus model in real time to improve building operation. This paper reports an enhancement of that real-time energy simulation framework. The previous version only works with software tools that implement the custom co-simulation interface of the Building Controls Virtual Test Bed (BCVTB), such as EnergyPlus, Dymola and TRNSYS. The new version uses an open standard interface, the Functional Mockup Interface (FMI), to provide a generic interface to any application that supports the FMI protocol. In addition, the new version utilizes the Simple Measurement and Actuation Profile (sMAP) tool as the data acquisition system to acquire, store and present data. This paper introduces the updated architecture of the real-time simulation framework using FMI and presents proof-of-concept demonstration results which validate the new framework. [ABSTRACT FROM AUTHOR]

Lightweight concrete offers numerous advantages for modular construction, including easier construction planning and logistics, and the ability to offset additional dead loads induced by double-wall and double-slab features. In a previous study, authors proposed incorporating lightweight aggregate into foamed concrete instead of adding extra foam to achieve lower density, resulting in lightweight concrete with an excellent strength-to-density ratio. This paper further investigated the performance aspects of foamed concrete with lightweight aggregate beyond mechanical strength. To evaluate the effect of aggregate type and foam content, three mix compositions were designed for the lightweight concrete. Specimens were prepared for experimental tests on thermal conductivity and drying shrinkage of lightweight concrete. Results showed that while both the increase in foam volume and the incorporation of lightweight aggregate led to higher drying shrinkage, they also contributed to improved insulating properties and reduced potential of cracking. Using typical multi-storey modular residential buildings in Hong Kong and three other Chinese cities as case studies, simulations were performed to assess potential savings in annual cooling and heating loads by employing the proposed lightweight concrete. These findings demonstrate the practical benefits of using foamed concrete with lightweight aggregate in modular construction and provide valuable insights for further optimization and implementation.

Energy simulation, the virtual representation and reproduction of energy processes for an entire building or a specific space, could assist building professionals with identifying relatively optimal energy conservation measures (ECMs). A review of current work revealed that methods for achieving simultaneous high accuracies in different levels of simulations, such as building level and zone level, have not been systematically explored, especially when there are several zones and multiple HVAC units in a building. Therefore, the objective of this paper is to introduce and validate a novel framework that can calibrate a model with high accuracies at multiple levels. In order to evaluate the performance of the calibration framework, we simulated HVAC-related energy consumption at the building level, at the ECM level and at the zone level. The simulation results were compared with the measured HVAC-related energy consumption. Our findings showed that MBE and CV (RMSE) were below 8.5% and 13.5%, respectively, for all three levels of energy simulation, demonstrating that the proposed framework could accurately simulate the building energy process at multiple levels. In addition, in order to estimate the potential energy efficiency improvements when different ECMs are implemented, the model has to be robust to the changes resulting from the building being operated under different control strategies. Mixed energy ground truths from two ECMs were used to calibrate the energy model. The results demonstrated that the model performed consistently well for both ECMs. Specific contributions of the study presented in this paper are the introduction of a novel calibration framework for multi-level simulation calibration, and improvements to the robustness of the calibrated model for different ECMs. [ABSTRACT FROM AUTHOR]

This study used a simulate based approach for calculating building energy consumption using monitoring data. This calibration was carried out on a building situated in Gurgaon, Delhi. Software used for dynamic simulation was E-Quest 3.65. The objective function was set to minimize the difference between calculated data and simulated data. The evaluation of the model accuracy, the mean bias error (MBE) and the Coefficient of Variation (Cv RMSE) were calculated. Through this paper show the real behavior of people in a building simulation, there may be differences up to 30% [1]. This paper shows the possibility of energy, money and time saving. The schedule of simulated building is same as per actual building.

Studies have demonstrated the energy savings potential of mixed-mode ventilated office buildings. Yet, it is important to widen the knowledge about how those buildings have been designed and built in practice, and which design parameters have greater influence on its energy performance. The aim of this paper was to evaluate how building envelope design parameters influence the energy performance of cellular mixed-mode office buildings, in order to identify key design variables. The analysis presents a comparison among literature research studies and typical construction practices from a sample of buildings located in the city of Sao Paulo, Brazil. According to a base case model, established based on the real buildings sample, three sensitivity analysis techniques were performed to obtain relative parameter sensitivity to thermal loads: OFAT, Morris and Monte Carlo. Results showed the importance of the window opening effective area and the reduced impact of the window-to-wall ratio on the energy performance of mixed-mode office buildings. By applying a multivariate regression model, it showed significant in predicting 78.1% of the variance in annual thermal loads. The accurate determination of annual thermal loads into mixed-mode office buildings can be used to optimize the envelope characteristics based on a combination of input data and the building geometry. Findings from this study could also be applied to other locations, provided that similar climatic environment and urban context are taken into account. • We evaluate the energy performance of mixed-mode office buildings. • A base case and its characteristics were defined based on a sample. • Typical construction practices versus theoretical studies were compared. • Three sensitivity analysis methods were applied and compared. • Multivariate regression model predicted 78% of the variance in annual thermal loads. [ABSTRACT FROM AUTHOR]

Bayesian calibration of building energy simulation (BES) has gained growing attention for its capability to tackle uncertainties and narrow the gap between simulated and measured results using expert knowledge. However, how output or parameter correlations influence single-output Bayesian calibration (SOBC) and multiple-output Bayesian calibration (MOBC) for BES has not been investigated and compared. Hence, this paper intends to determine the impacts of output or parameter correlations and data informativeness on BC of BES. Aiming to leverage multiple outputs' correlations while comparing with traditional SOBC in calibration performance and computation cost, we also developed the MOBC model. Compared to including weakly correlated outputs or parameters, the results show that strongly correlated outputs or parameters in MOBC reduce the Coefficient of Variation of the Root Mean Squared Error (CVRMSE) by 5.56% and 4.729% respectively and bring notably better Continuous Ranked Probability Score (CRPS) results. Conversely, including strongly correlated parameters in SOBC causes worse model performance. These results reflect that SOBC has parameter identifiability issues that MOBC can solve. The findings contribute to our better understanding of the impacts of (1) output or parameter correlations and (2) different data streams' informativeness on the calibration performance of SOBC and our developed MOBC for BES. • Employed multiple-output Bayesian calibration (MOBC) on building simulation. • Quantified the impacts of parameter and output correlations separately. • More data does not mean better building energy model calibration performance. • The single-output has parameter identifiability issues, which MOBC can ease. • Output/Parameter correlations can be exploited by MOBC for better performance. [ABSTRACT FROM AUTHOR]

Energy simulation models are crucial to estimate the energy demand of buildings, especially for prospective planning on a district or city scale. As required input data is not available in many cases, an automated model generation workflow is needed. Existing workflows have several disadvantages, including: (i) dependence on large input datasets of existing buildings; (ii) no 3D representation to support the planning process; (iii) they are proprietary solutions. The pipeline 'SHP2SIM' is an open-source python pipeline enabling enrichment and generation of building energy simulation models based on little input data for district and urban scale. The pipeline is tested by simulating the heat load for a district with 27 buildings and validated for one building: R squared is 0.9825, CV(RMSE) is 22.10%, and NMBE is 4.06% on a monthly basis. To enable reproducibility and encourage open science, input data, output models, and the pipeline are openly available (). [ABSTRACT FROM AUTHOR]

Accurate prediction of building energy need plays a fundamental role in building design, despite the high computational cost to search for optimal energy saving solutions. An important advancement in the reduction of computational time could come from the application of machine learning models to circumvent energy simulations. With the goal of drastically limiting the number of simulations, in this paper we investigate the regression performance of different machine learning models, i.e., Support Vector Machine, Random Forest, and Extreme Gradient Boosting, trained on a small data-set of energy simulations performed on a case study building. Among the XX algorithms, the tree-based Extreme Gradient Boosting showed the best performance. Overall, we find that machine learning methods offer efficient and interpretable solutions, that could help academics and professionals in shaping better design strategies, informed by feature importance. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents the key factors methodology that supports energy managers in determining the optimal building operation strategy in relation to both energy consumption and thermal comfort. The methodology is supported by the utilization of calibrated building energy simulation models that match measured data gathered by an extensive measurement framework. Building management systems, do not allow energy managers to test the impact of changes in control settings of energy systems on energy consumption and thermal comfort. The proposed methodology and prototype tool chain enables energy managers to virtually develop and test the impact of proposed changes to the control settings in the building energy systems prior to their implementation in the physical building. The paper outlines the proposed methodology defining the underpinning concepts and illustrating the performance metrics required to capture the effect of different building operation strategies. A case study is discussed to demonstrate the application of the methodology. [Copyright &y& Elsevier]

Abstract: This paper reports the use of an internationally recognized validation and diagnostics procedure to test the fidelity of a simplified calculation method. The case study is the simplified model for calculation of energy performance of building envelopes, introduced by the Brazilian regulation for energy efficiency in commercial buildings. The first step of the assessment consisted on evaluating the simplified model results using the BESTEST. This paper presents a straightforward approach to apply the BESTEST in other climates than the original one (Denver, USA). The second step of the assessment consisted on applying the simplified model to evaluate four building typologies, and compare the results with those obtained using a state of the art building energy simulation (BES) program. For some BESTEST cases, the simplified model presented results inside of a confidence interval calculated by the authors. However, the simplified model was found to yield significant difference in the four building typologies analysed. Moreover, in all four building typologies analysed, the simplified model led to a lower energy efficiency label when compared to the label obtained using BES. The paper concludes that the simplified model may require improvements to properly indicate the actual energy performance of commercial building envelopes. [Copyright &y& Elsevier]

Abstract Building energy consumption accounts for 30% of the overall energy end use worldwide. This number is even much higher in urban areas. With rapid urbanization in China, cities are expanding with new constructions. It is essential to create an updated urban-scale building energy consumption database to represent energy use for different types of buildings in China, which could help urban planners, managers and decision makers to understand temporal and spatial building energy consumption distribution and ensure required electricity and/or gas supply. However, such urban-scale database is rarely found in China. This paper creates baseline EnergyPlus models for residential, small office and large office buildings and validates the baseline models using survey data from literature. Parametric simulations are conducted to consider different design factors, such as building enclosure, lighting power density, equipment power density, HVAC schedule, etc. In total 351 EnergyPlus models are generated to cover different energy use intensity scenarios. Data-driven regression analysis is conducted to predict building energy consumption using building price/rent. The prediction results are expected to provide design decision support for urban planning and power distribution for new constructions. [ABSTRACT FROM AUTHOR]

Highlights • Our equivalent wall method uses the structure factors and harmonic heat fluxes. • The method is tested on three 2-D thermal bridges. • The comparison is based on numerical simulations results. • For a realistic, severe or step evolution of outside temperature, results are precise. • Equivalent walls results are much better than those for a classic 1-D evaluation. Abstract This paper presents a mixed method to determine a 1-D three-layer wall having the same static and dynamic behaviours as a multidimensional thermal bridge. It is based on the calculations of thermal resistance, heat capacity, structure factors and an objective function using harmonic heat fluxes features. This mixed method is applied to three 2-D details. The heat flux through inner surface is analysed over time for a step solicitation and for given boundary conditions: a sinus evolution of the inside temperature and a severe or a more realistic evolution of the outside temperature. Results are really satisfactory, evolution of heat flux through the thermal bridge is close to that of the corresponding equivalent wall. For an outside temperature profile (T e) close to real data, the error on integral value of heat flux is less than 1% in each case. The results for equivalent walls are significantly better than for a classic 1-D evaluation: for a severe evolution of T e the average error is 6 to 28 times lower in the tested cases. [ABSTRACT FROM AUTHOR]

Abstract: Building energy simulations are key to studying energy efficiency in buildings. The state-of-the art building energy simulation tools requires a high level of multi disciplinary domain expertise from the user and many technical data inputs that curb the usability of such programs. In this paper an IT tool is presented, which has the capability of predicting a building''s energy utilization configuration based on the reported annual energy and a few non-technical inputs from the user; and correspondingly generates cost effective energy conservation measures for the intended savings. The approach first identifies the system variables that are critical to a building''s energy consumption and searches for the combination of these parameters that would give rise to the annual energy consumption as reported by the facility. Genetic algorithms are utilized to generate this database. A statistical fit is formulated between the system variables and the annual energy consumption from the database. Using this correlation, system configuration for the target energy efficiency is determined with corresponding energy conservation measures. A cost analysis is carried out to prescribe the most cost effective energy conservation measures. Competency of the tool is demonstrated in the paper through case studies on three geographies with different climate conditions. [Copyright &y& Elsevier]

Abstract Parallel fan-powered terminal units (FPTUs) are widely considered more energy efficient compared with series FPTUs because of the intermittent terminal unit fan operation. Recent studies found that the energy savings potential of parallel FPTUs may be overestimated due to the primary air leakage through the backdraft dampers when terminal unit fans are not operating. However, the lack of an effective modeling approach in building simulation programs has prevented the thorough investigation of how the primary air leakage from parallel FPTUs affects the energy consumption of variable air volume (VAV) systems. In this paper, a modeling approach was developed and implemented in EnergyPlus using the Energy Management System (EMS) for the comparative analysis of energy impact of primary air leakage from parallel FPTUs. A series of building energy simulations were also conducted at four air leakage levels under five different U.S. climates. Although the percentage energy increases caused by the primary air leakage vary with local climates and leakage levels, simulation results show consistent increases in the energy consumption of central cooling coil, central supply fan, and FPTU supplemental heating throughout all the climates as the air leakage level increases. Compared with series FPTUs, the energy savings potential of parallel units significantly decreases as air leakage level increases. At the highest air leakage level of 15% simulated in this study, series FPTUs may use less energy than parallel FPTUs. [ABSTRACT FROM AUTHOR]

In the era of post-Coronavirus Disease 2019, the dedicated outdoor air system (DOAS), which provides 100% outdoor air for the building, is widely acknowledged as it can ensure acceptable indoor air quality by delivering fresh outdoor air to occupied space. The DOAS with a proper design and operation can provide sufficient ventilation and dehumidification while achieving energy efficiency. Nonetheless, there is limited guidance in determining the optimal control sequence of the DOAS for the designers and operators to implement in practice. Accordingly, in practice, a number of issues have been acknowledged in the design and control phases of DOAS, including insufficient ventilation and dehumidification, and increasing supply air dry-bulb temperature in fear of over-cooling, which might cause significant discomfort and energy waste. There have been efforts to develop high-performing DOAS controls for better energy efficiency. However, such controls are often complex, or difficult to interpret, for building designers and operators to consider in practice. In this regard, this paper explores a simulation-based framework for generating a supply air temperature control sequence of the DOAS not only to ensure improved energy-saving potential but also to guarantee the implement-ability of the control logic. The U.S. Department of Energy prototype primary school with dynamic occupancy profiles was modeled with a whole building simulation program, EnergyPlus. The model consists of a DOAS with an exhaust air energy recovery system for ventilation and fan-coil units for space cooling and heating. Then, a Genetic Algorithm was adopted to find the true optimal supply air temperature control sequence in terms of minimizing the energy cost of the heating, ventilation, and air conditioning system operation. Lastly, Decision Tree was adopted to extract rules out of the optimums to derive an implementable sequence of operation for the DOAS supply air temperature. A total of 12 week-simulation including four weeks of heating, cooling, and shoulder seasons, separately, under the weather condition of New York City was conducted for the case study. This case study identified that the optimization-informed rule extraction-based control, when compared to conventional outdoor air temperature-based reset control, could save about 13% of energy cost and 25% of energy consumption throughout the heating, cooling, and shoulder seasons. It is notable that the energy-saving was mainly achieved by reducing the heating energy consumption. Importantly, it nearly corresponds to the true optimal control result, which reduces approximately 14% of energy cost and 27% of energy consumption. From the results, it can be highlighted that the optimization-informed rule extraction can be as energy effective as the optimal control, while significantly reducing the complexity of the control. [ABSTRACT FROM AUTHOR]

Building energy requalification in Italy and Europe has been much discussed in recent years due to the high percentage of existing buildings with poor energy performance. In this context, it is useful to obtain a user-friendly and fast tool to predict the thermal energy demand (TED) for space conditioning and the related primary energy consumption (PEC) as a function of climatic stress. In this study, the SLABE methodology (simulation-based large-scale uncertainty/sensitivity analysis of building energy performance) is used to simulate representative Italian buildings, varying parameters such as geometry, envelope and HVAC (heating, ventilating and space conditioning) systems. MATLAB® in combination with EnergyPlus is used to analyze 200 buildings belonging to two structural types (multi-family buildings and apartment blocks) built in 1961–1975. Nine scenarios (as-built scenarios and eight retrofit ones) are investigated in 63 climatic locations. A regression analysis shows that the classical HDDs (heating degree days) approach cannot give an accurate prediction of TED because solar radiation is not accounted for. Thus, new climatic indices are developed alongside solar radiation, including the heating stress index (HSI), the cooling stress index (CSI) and the yearly climatic stress index (YCSI). The purpose of our work is to obtain climatic stress curves for the prediction of TED and PEC. Testing of this novel approach is performed by comparison with another building energy simulation tool, showing a low discrepancy, i.e., the coefficient of variation of the root mean square error is between 12% and 28%, which confirms certain reliability of the approach here proposed. [ABSTRACT FROM AUTHOR]

Dense cities usually experience the urban heat island (UHI) effect, resulting in higher ambient temperatures and increased cooling loads. However, the typical lack of combining climatic variables with building passive design parameters in significant evaluations hinders the consideration of the UHI effect during the building design stage. In that regard, a global sensitivity analysis was conducted to assess the significance of climatic variables and building design features in building energy simulations for an office building. Additionally, this study examines the UHI effect on building energy performance in Qatar, a hot-arid climate, using both measurement data and computational modeling. This study collects measurement data across Qatar and conducts computational fluid dynamics (CFD) simulations; the results from both methods serve as inputs in building energy simulation (BES). The results demonstrate that space cooling demand is more sensitive to ambient temperature than other climatic parameters, building thermal properties, etc. The UHI intensity is high during hot and transition seasons and reaches a maximum of 13 °C. BES results show a 10% increase in cooling energy demand for an office building due to the UHI effect on a hot day. The results of this study enable more informed decision-making during the building design process. [ABSTRACT FROM AUTHOR]