Building Energy Simulation Research Articles

Impact of Spatial Layout Design on Energy Consumption of Ice Rinks in Cold Regions

The differentiated physical environment requirements within the internal space of ice rinks in cold regions result in a complex heat exchange process, which becomes the primary cause of high energy consumption. Therefore, analyzing the impact mechanisms of spatial layout parameters on the energy consumption of ice rinks is crucial during the early design stages. This study employed the Delphi method to identify the key parameters affecting the total energy consumption of ice rinks. It conducted single-factor experiments using building performance simulations to quantify the relationship between each layout parameter and the energy consumption. Based on the single-factor experiment results, orthogonal experiments were conducted to develop an energy-efficient spatial layout combination. The study indicates that the height-to-width ratio and the mixed area width are the most significant parameters. By adjusting the values of these parameters, the total energy consumption can be reduced by approximately 18% to 31%. The spatial layout strategy for ice rinks in cold regions proposed in this study will help architects make more effective decisions during the early design stages.

Investigating the influence of uncertainty on office building energy simulation through occupant-centric control and thermal comfort integration

Buildings with occupant-centric control (OCC) systems can adjust heating, ventilation, and air conditioning (HVAC) operations based on occupant status to minimize unnecessary energy use. However, because occupant behavior is stochastic rather than constant, and preferred setpoints can vary across occupant groups, this randomness significantly impacts energy use in buildings with OCC systems.This study used a stochastic simulation approach to model the uncertainty inherent in occupancy patterns and evaluate its impact on the energy consumption of an office building with OCC. In this case, the setpoint temperature was determined based on the Predicted Mean Vote (PMV) method so that each zone could be controlled to the preferred temperature according to the occupant group.The results showed that the uncertainty of the annualized sum of electricity consumption for heating and cooling was 4.3 % and 1.8 %, respectively, with 95 % confidence intervals. Notably, a negative correlation was observed between the number of occupants and the uncertainty of energy consumption. Thus, as the uncertainty in the setpoint temperature increased during periods of low occupancy, the uncertainty in the energy consumption of the HVAC system also tended to increase. These insights underscore the significant influence of occupancy-related factors on building energy utilization.

Quantifying Uncertainty with Conformal Prediction for Heating and Cooling Load Forecasting in Building Performance Simulation

Quantifying Uncertainty with Conformal Prediction for Heating and Cooling Load Forecasting in Building Performance Simulation

A GIS-Based Approach for Urban Building Energy Modeling under Climate Change with High Spatial and Temporal Resolution

The energy demand and associated greenhouse gas (GHG) emissions of buildings are significantly affected by the characteristics of the building and local climate conditions. While energy use datasets with high spatial and temporal resolution are highly needed in the context of climate change, energy use monitoring data are not available for most cities. This study introduces an approach combining building energy simulation, climate change modeling, and GIS spatial analysis techniques to develop an energy demand data inventory enabling assessment of the impacts of climate change on building energy consumption in Shanghai, China. Our results suggest that all types of buildings exhibit a net increase in their annual energy demand under the projected future (2050) climate conditions, with the highest increase in energy demand attributed to Heating, Ventilation, and Cooling (HVAC) systems. Variations in building energy demand are found across building types. Due to the large number of residential buildings, they are the main contributor to the increases in energy demand and associated CO2 emissions. The hourly residential building energy demand on a typical hot summer day (29 July) under the 2050 climate condition at 1 p.m. is found to increase by more than 40%, indicating a risk of energy supply shortage if no actions are taken. The spatial pattern of total annual building energy demand at the individual building level exhibited high spatial heterogeneity with some hotspots. This study provides an alternative method to develop a building energy demand inventory with high temporal resolution at the individual building scale for cities lacking energy use monitoring data, supporting the assessment of building energy and GHG emissions under both current and future climate scenarios at minimal cost.

Research on the Design of Green Roofs for Office Buildings in Xuzhou Based on Building Energy Consumption Evaluation

The roof is the part of a building that is exposed to solar radiation for the longest period, making green roofs particularly effective in reducing air conditioning energy consumption during the summer. This study aims to assess the advantages of modular green roofs in terms of energy savings and cost reduction during the summer in Xuzhou. By conducting field measurements and surveys under both air-conditioned and non-air-conditioned conditions and utilizing building energy simulation tools, the performance of green roofs with different parameters was compared. Using EnergyPlus, factors such as soil thickness, thermal conductivity, and leaf area index were simulated. The results indicated that green roofs have superior thermal performance in summer, with the daily cooling load per unit area for top-floor rooms being 1.05 kWh/m2, 0.21 kWh/m2 lower than that for bare roofs, achieving an energy saving rate of 16.7%. It is recommended that soil thickness not exceed 0.3 m and insulation thickness not exceed 0.05 m or be set to 0 m. Take building no. 2 of the Xuzhou material market as an example: with the optimized green roof, the energy saving rate increased to 27.0%, which is 12.4% higher than that of the original green roof. The suggested cost for modular green roofs is 204 RMB/m2.

Thermal Performance and Building Energy Simulation of Precast Insulation Walls in Two Climate Zones

Traditional concrete buildings exhibit low energy consumption and high heat loss, which results in a larger environmental problem. Precast insulation walls are proposed for strengthening thermal insulation efficiency and mitigating heat loss. Numerous studies have investigated the thermal performance of insulation walls over the past decades. However, gaps remain in practical engineering applications. This study aims to bridge these gaps by providing practical design recommendations based on experimental research. Nine different types of precast insulation walls were tested to examine the thermal performance, and the parameters of the insulation material, insulation form, insulation layer thickness, and concrete rib width were investigated. Then, numerical models of these walls were developed for simulating the thermal performance of the tested specimens. Finally, a six-story student apartment model using designed walls was developed to assess energy consumption in two distinct climate zones: the hot summer and cold winter zone of Changsha City, and the cold zone of Harbin City. The results indicate that the precast insulation wall with external insulation form shows better thermal performance than the sandwich insulation form. It is recommended to use precast insulation walls with 50 mm extruded polystyrene (XPS) external thermal insulation form in Changsha City and 80 mm XPS external thermal insulation form in Harbin City. Furthermore, buildings using precast insulation walls can significantly reduce energy consumption by 49.25% in Changsha and 49.38% in Harbin compared to traditional concrete wall buildings. Based on these findings, suitable design suggestions for this precast concrete wall panel building composed of insulation walls are given.

Towards Climate, Bioclimatism, and Building Performance—A Characterization of the Brazilian Territory from 2008 to 2022

Representative weather data are fundamental to characterizing a place and determining ideal design approaches. This is particularly important for large countries like Brazil, whose extension and geographical position contribute to defining diverse climatic conditions along the territory. In this context, this study intends to characterize the Brazilian territory based on a 15-year weather record (2008–2022), providing a climatic assessment based on a climatic and bioclimatic profile for the whole country. The climate analysis was focused on temperature, humidity, precipitation, and solar radiation, followed by a bioclimatic analysis guided by the Givoni chart and the natural ventilation potential assessment. In both situations, the results were analyzed using three resolutions: country-level, administrative division, and bioclimatic zones. This study also identified representative locations for the Brazilian bioclimatic zones for a building-centered analysis based on the thermal and energy performance of a single-family house with different envelope configurations. The results proved that most Brazilian territories increased above 0.4 °C in the dry bulb temperature and reduced relative humidity. The precipitation had the highest reduction, reaching more than 50% for some locations. The warmer and drier conditions impacted also the Köppen–Geiger classification, with an increase in the number of Semi-Arid and Arid locations. The bioclimatic study showed that ventilation is the primary strategy for the Brazilian territory, as confirmed by the natural ventilation potential results, followed by passive heating strategies during the year’s coldest months. Finally, building performance simulation underlined that, in colder climates, indoor thermal comfort conditions and air-conditioning demands are less affected by solar absorptance for constructions with low U-values, while in warmer climates, low solar absorptance with intermediary U-values is recommended.

Optimization framework for daylight and thermal environment of retractable roof natatoriums based on generative adversarial network and genetic algorithm

This paper proposes a framework for multi-objective optimization of indoor daylighting and thermal comfort in natatoriums with retractable roofs, using genetic algorithms and building performance simulation. The goal is to balance daylight illumination and thermal comfort under different roof opening states. Efficiency of computational fluid dynamics simulation is improved by a multi-objective optimization framework based on non-dominated sorting genetic algorithms, integrating a generative adversarial network to learn the environmental map. The study analyses the impact of different roof opening ratios on environmental objectives and establishes regression equations to support optimization and accurate decision-making. In the optimal opening state, compared to a fully closed roof, the daylight factor and natural airflow velocity increase by up to 3.9 and 5.3 times, respectively, while the universal thermal climate index decreases by 1.0 °C. The introduction of a generative adversarial network proxy model significantly improves computational efficiency, accelerating natural airflow velocity calculation by 70–100 times and reducing simulation time by 98.6 %. This study expands predictive models from the urban scale to the building scale, enhancing simulation efficiency and promoting the application of deep learning models and genetic algorithms in climate-responsive building environment assessment and prediction.

Assessing the validity of simplified heating and cooling demand calculation methods: The case of Passive House Planning Package (PHPP) and Radiant Time Series Method (RTSM)

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.

Thermal performance of shaded roofs: investigating the impact of material properties and efficacy of building performance simulation

This research investigates the thermal performance of shaded roofs in the composite climate of Roorkee, India, by examining four shading materials (three opaque, one translucent) over an unobstructed roof for eight consecutive days. Using ‘Designbuilder’ software simulations and a mathematical model, the study meticulously triangulates experimental, simulated, and modelled data. The hourly temperature profile of the roof under different shades is analysed and the results showed negligible differences among opaque shading materials, while the translucent material significantly altered the roof’s thermal performance due to solar transmittance. Opaque shades reduced peak heat gain through the roof by up to 77% and 71.5% on cloudy and sunny days, respectively, and reduced nighttime heat loss by 40% and 33%, respectively. This research underscores the importance of considering shading material properties in sustainable building design and confirms the reliability of simulation tools. Highlights The study finds that in parasol roofs, the shading material's thermal properties do not impact the roof's thermal performance, but the solar transmittance does. The study also found that opaque shading could reduce the hourly peak heat gain through the roof by up to 77% and 71.5% on a cloudy day and sunny day, respectively, and reduced the nighttime hourly peak heat loss from the roof by up to 40% and 33%, respectively. Despite considering shading elements in BPS tools to be thermally inactive, the tools perform valid energy simulations.

Informing building retrofits at low computational costs: a multi-objective optimisation using machine learning surrogates of building performance simulation models

Machine learning (ML) algorithms are increasingly used as surrogates for building performance simulation (BPS) models to leverage their energy predictive capabilities while reducing computational costs. In parallel, researchers are developing optimisation methods to inform building design and retrofit strategies but rarely employ ML-based BPS surrogates for this purpose. This study proposes a coupled modelling approach that leverages the capabilities of ML-based BPS surrogate models and multi-objective optimisation to inform holistic design and operation retrofits at low computational costs. The proposed methodology is demonstrated using an archetypal office building in Ottawa, Canada. The developed models achieved competitive predictive accuracies (adjusted R2: 0.90–0.99), identifying total and peak energy saving measures with up to 34% improvement in occupant thermal comfort at computational speeds 1266 times faster than a traditional BPS-based optimisation approach. Results offer a promising modelling workflow for design applications requiring extensive computations and scenario analyses, such as net-zero energy retrofits.

Performance Assessment of an Integrated Low-Approach Low-Temperature Open Cooling Tower with Radiant Cooling and Displacement Ventilation for Space Conditioning in Temperate Climates

Cooling towers, by producing chilled water and by integration with radiant and displacement cooling systems, offer a possible alternative method for space conditioning of office buildings in temperate climates. This present study examines the operational feasibility of a cooling tower in conjunction with a radiant and displacement ventilation cooling system for office conditioning in four temperate climates. The climates are: cool and semi-humid (Birmingham, UK), cool and dry (Helsinki, FI), warm and humid (Paris, FR) and warm and dry (Prague, CZ). The system is capable of producing chilled water between 14 and 20 °C, with low approach tower temperatures (1–3 K). A mathematical model of the cooling tower system was developed and integrated with an office building energy simulation model. Using the integrated simulation model, assessment was carried out based on ASHRAE design day specifications, as well as a complete cooling seasonal analysis. Moreover, the performance of the system is benchmarked against a variable-air-volume cooling system. Energy savings for the system when benchmarked against a variable-air-volume air conditioning system, where the chiller COP (coefficient of performance) varies from 2.75 to 6.5, were 62% to 37% in Paris, 56% to 30% in Prague, 52% to 28% in Helsinki and 45% to 13% in Birmingham, respectively.

Assessing thermal resilience to overheating in a Belgian apartment: impact of building parameters

Globally and in European Union, climate change and heatwaves (HWs) challenges the thermal resilience performance (buildings’ ability to withstand and recover from a shock) of airtight, highly insulated buildings with no cooling strategies. Ensuring thermal resilience in buildings is crucial for maintaining habitability amid climate change uncertainties. This study, under the framework of IEA EBC Annex 80, aims to explore the impact of design parameters (thermal mass, window to wall ratio (WWR), operation of solar shading and natural night ventilation) on the thermal resilience in a Belgian apartment. Although a number of recent studies explored impact of building design on overheating, there is still a lack in the state-of-the-art exploring and varying ranges of the design parameters that impact the thermal resilience performance of apartments during short-term shocks such as heatwaves. In order to reach the aim of this study, building energy simulations were performed. Initially, the default apartment was evaluated during current weather scenario varying the parameters. Results showed overheating risk in default apartment during current weather scenario. Then the worst, improved and, the optimized variation of the building is evaluated against 6 days HW. The apartments’ thermal resilience performance assessment conclude that high window-to-wall ratios (WWR >30%) without solar shading and lighter thermal mass decrease thermal resilience during shocks, highlighting WWR’s significance. For short-term overheating events, heavy thermal mass improves the thermal resilience by pro-longing the absorptivity time (withstanding capability) of the excess heat. However, if excess heat is absorbed by the building (higher WWR resulting in higher solar gains), lighter thermal mass enhances the thermal resilience performance (recovery capability) by flushing out the excess heat. Solar shading and passive cooling strategy like natural night ventilation aids in temperature management, improving the buildings’ thermal resilience performance by prolonging the absorptivity and speeding the recovery from the shock.

BIM/BES INTEROPERABILITY: A CASE STUDY BETWEEN REVIT®, DESIGNBUILDER®, IES-VE®, AND E-QUEST®

Objective: This study proposes a BIM/BES interoperability test through a case study involving Revit® and three BES software programs: DesignBuilder®, IES-VE®, and e-Quest®. Theoretical Framework: For thermo-energy analyses, a recognized combination is the BIM (Building Information Modeling) / BES (Building Energy Simulation) pair. This requires data transfer from one software to another. To export the virtual model, it is necessary to generate the energy analytical model in BIM and use transfer protocols for BES software. Various studies have indicated failures in this process. Method: A case study was used to analyze the interoperability between the software programs, through a 58m² single-family residence. The geometric model was created with its dimensions and layers, input data such as location, thermal properties of materials, and usage data, generating the energy analytical model and exporting it to each BES software. Interoperability was tested based on data transfer analysis, establishing seven criteria. Results and Discussion: The results indicated failures in interoperability, as none of the software programs exported all the criteria correctly. The BES software with the best results was IES-VE®, with 70.90% of the criteria exported, followed by e-Quest® (65.45%) and DesignBuilder® (45.45%). Research Implications: The results of this study demonstrate that interoperability challenges limit the potential of the BIM/BES pair. Originality/Value: Despite studies on this topic, interoperability challenges remain, representing a gap to be filled.

Comparison of EnergyPlus inside surfaces convective heat transfer coefficients algorithms for energy modelling of high-density controlled environment agriculture

Energy modelling of high-density controlled environment agriculture (CEA-HD) spaces using a building performance simulation (BPS) tool and a crop energy balance model is emerging as a method to conduct load calculation and energy analysis. However, the modelling hypotheses used in BPS tools have yet to be tailored for CEA-HD spaces and might not be suitable for this specific application. This paper investigates the convective heat transfer coefficient (CHTC) algorithms for inside surfaces included in EnergyPlus to examine their applicability to CEA-HD spaces. The influence of these inside surfaces CHTC algorithms on relevant variables are quantified, with computational fluid dynamics (CFD) computed CHTCs as a reference. The results revealed that certain algorithms (Simple, TARP, and ASTMC1340) are ill-suited to model CEA-HD production spaces compared to CFD-computed reference values. Furthermore, due to the modelled flow rate, the Adaptive Convection algorithm resulted in an aberrant value for the ceiling CHTC. This paper highlights the importance of exercising caution when using BPS tools for energy modelling of CEA-HD spaces.

Comparative carbon emission assessment of vertical and modular ground source heat pump systems

The urgent need to address climate change necessitates a reduction in carbon emissions, particularly within the building sector. To achieve carbon neutrality, innovative technologies such as carbon capture, renewable energy systems, and carbon-neutral materials have been developed. However, there remains a dearth of research quantitatively analyzing carbon emissions through a life cycle assessment while implementing these technologies in real-world building scenarios. Additionally, Ground-source Heat Pumps (GSHPs) demonstrate superior efficiency compared to Air-source Heat Pumps (ASHPs) by leveraging stable ground temperatures, yet their widespread adoption is hindered by high initial investment costs. This study compares and analyzes the carbon emissions of GSHPs with Modular Ground Heat Exchangers (MGHXs), designed to mitigate initial investment barriers, alongside Vertical Ground Heat Exchangers (VGHXs) and ASHPs. The primary objective is to evaluate technology adoption feasibility from a carbon equivalent perspective, focusing on energy demand through building energy simulation. Results indicate that MGHXs exhibit a 6.7 % reduction in carbon emissions compared to VGHXs during production and construction (stage A). However, MGHXs generate 0.57 CO2-eq more per square meter per year during building operation (stage C). The implementation of geothermal energy systems in new buildings across South Korea could potentially achieve a maximum reduction effect of 11.6 % concerning the country's NDC (Nationally Determined Contributions) 2030 carbon reduction target.

Prefabricated Envelope Green Remodeling Potential of Public Office Buildings in Korea

The public sector should reduce energy consumption and carbon emissions from the building stock, thereby serving as a role model for the private sector. In Korea, public buildings are leading the green remodeling business initiative as part of a carbon-neutral strategy. Building envelope retrofitting is essential for the green remodeling of existing buildings because it significantly affects the buildings’ aesthetic appearance, occupant comfort, and energy usage. From the perspectives of constructability and cost, prefabricated envelope systems offer various advantages and can contribute to the growth of the green remodeling business. To develop an effective prefabricated envelope system, a thorough analysis of the existing building stock must be conducted. Therefore, this study aims to investigate existing public office buildings in Korea to obtain a better understanding of the considerations necessary for developing prefabricated envelope systems. The survey utilized the image search and road-view functions of map services, following an appropriate sample design. Based on the survey results, the characteristics of the building types and envelopes, as well as considerations for developing prefabricated envelope systems are discussed. Furthermore, this study quantitatively analyzed the energy conservation potential through building energy simulations.

Quantifying the decarbonization potential of mobile heat battery in low-temperature district heating

This research assesses the potential of a mobile thermochemical storage system, the mobile heat battery (M-HB), for decarbonizing a low-temperature district heating (DH) system in the Netherlands. The assessment is built on a case study where the M-HB is used to transport waste heat from different sources to a neighborhood interface of a DH system. This case study utilizes a simulation-based methodology to calculate the emissions from grid electricity, DH, and M-HB transport and charging. Building performance simulation is used as the main experimental method in combination with both empirical data and theoretical assumptions. Various system operational strategies and uncertain factors are explored, and waste heat sources are screened by different decarbonization targets. Findings indicate that using the M-HB can reduce the operational carbon emissions by up to 80 %, from approximately 60–70 KgCO2/GJ of the system without M-HB to around 13 KgCO2/GJ in optimal scenarios. Emissions from M-HB transport and charging are identified as more influential to the decarbonization potential than other considered factors, which addresses the significance of choosing proper waste heat sources. Despite some limitations from data availability and assumptions, this work identifies both opportunities and challenges for using M-HB to decarbonize DH systems.

Integrating energy simulations and analytical hierarchy process procedure in multi-criteria evaluation of heating systems for industrial buildings

Industrial buildings in Italy are generally aged and widely outdated from an architectural, technological, and environmental perspective. Despite the current limitations affecting both envelope and system installations, enhancement strategies are not frequently debated in the literature or addressed recurring to not adequately comprehensive approaches. This research examines space heating options for integrated retrofit interventions of manufacturing facilities using a novel methodology that combines multi-criteria decision analysis based on the Analytic Hierarchy Process (AHP) with building energy simulations. Interviews with representatives from medium-sized companies in Tuscany provide insights into the exigencies of industrial buildings, while on-site surveys identify common features of industrial buildings in the region leading to the identification of a representative case study building. This facility is examined producing several energy models to account for the different heating system alternatives to be evaluated according to criteria including economic, environmental, comfort, space, and reliability. Both qualitative judgments and quantitative outputs from energy simulations are considered to rank the technological alternatives encompassed in the analysis. In addition, sensitivity analyses are carried out to highlight the impact of boundary conditions on optimal configuration selection. Economic considerations weigh heavily for industrial owners, often outweighing environmental concerns due to higher initial investment requirements for low-impact solutions. Consequently, gas boiler generators and hot-water fan heaters emerge as preferred options for their flexibility, low initial cost, and ease of installation.

A contextual approach to estimate household activities in instrumented dwellings

Occupants and their activities are important in computer-aided systems such as energy management or energy simulation in residential buildings. Numerous studies have extensively examined detailed household activities at the population level using time-use surveys. Despite the considerable influence of contexts on occupants' activities, a limited number of studies focus on individual households due to the constraints imposed by private policies on collecting occupants' activities. This article proposes an approach to detect detailed occupants' activities (e.g., cooking, entertaining) based on measurements in specific households. Firstly, a camera-free mobile application is proposed to support the data collection process due to the restriction of cameras. Then, relevant features are determined for each activity. Finally, Bayesian networks were built to represent human-understandable relationships between determined features and related activities. An instrumented dwelling with five individuals is tested, and a 4-month dataset is used to evaluate the model quality. Results show that the model can estimate most of the studied activities (e.g., cooking, washing dishes) with a F1-score between 0.77 and 0.92. The approach is better than the statistical approach with time-use surveys in building household activity profiles, which is important in energy simulation and verification. In addition, this approach is replicable for different households, providing them with context-specific and highly useable information to enhance smart energy management systems and occupants’ energy behavior.