Building Performance Simulation Tools Research Articles

Impact of outdoor heat adaptation on indoor thermal conditions – Combining microscale urban climate and building performance simulation

To what extent can outdoor heat adaptation measures in urban districts help to reduce high indoor temperatures in buildings and thus enhance indoor thermal conditions? To answer this question microscale meteorological simulation (MMS) and building performance simulation (BPS) are combined in a model chain approach. Two existing residential German districts with different urban designs are modelled in the MMS tool ENVI-met. For both districts, a representative residential building (one from the Wilhelminian period and one large panel construction type) is modelled using the BPS tool IDA-ICE. Different scenarios of heat adaptation measures are applied to analyse how changes in urban and building design (e.g. white (cool) roofs (high albedo), white traffic areas (high albedo), intensive green roofs, urban trees, facade insulation or facade greening) affect outdoor and indoor temperatures. The MMS results highlight that the district from the Wilhelminian period is less heat resilient and that the efficacy of heat adaptation measures on heat reduction in open space depends on the urban design and the daytime. Regarding the efficacy of heat adaptation measures on indoor thermal conditions, our findings indicate that the larger share of the indoor cooling effect is not caused by the outdoor air temperature reduction by the outdoor heat adaptation measures but by the change of the building physics in the BPS model (e.g. changing the surface reflectance of the white roofs). White roofs and intensive green roofs show the largest cooling effect by reducing the operative room temperature by more than 1 Kelvin. Our findings also demonstrate that facade insulation can act as both, climate adaptation and mitigation measures.

Investigating Advanced Building Envelopes for Energy Efficiency in Prefab Temporary Post-Disaster Housing

Prefabricated temporary buildings are a promising solution for post-disaster scenarios for their modularity, sustainability and transportation advantages. However, their low thermal mass building envelope shows a fast response to heat flux excitations. This leads to the risk of not meeting the occupant comfort and HVAC energy-saving requirements. The literature shows different measures implementable in opaque surfaces, like vacuum insulation panels (VIPs), phase change materials (PCMs) and switchable coatings, and in transparent surfaces (switchable glazing) to mitigate thermal issues, like overheating, while preserving the limited available internal space. This paper investigates the energy and overheating performance of the mentioned interventions by using building performance simulation tools to assess their effectiveness. The optimization also looks at the transportation flexibility of each intervention to better support the decision maker for manufacturing innovative temporary units. The most energy-efficient measures turn to be VIPs as a better energy solution for winter and PCMs as a better thermal comfort solution for summer.

Energy modeling, calibration, and validation of a small-scale greenhouse using TRNSYS

Greenhouse energy modeling is a prevalent tool for optimizing greenhouse energy consumption. However, for a model to serve its intended use, it is imperative to have a high level of confidence in the precision of its predictions. In this paper, a validated greenhouse energy model for a typical small-scale greenhouse in a cold climate is developed. The model is created using TRNSYS, a building performance simulation tool, with detailed energy modeling components and a user-defined crop model. The model is calibrated to fix uncertain parameters. A sensitivity analysis is used first to identify sensible uncertain parameters, followed by a multi-stage automated calibration. The automated calibration method uses a multi-objective genetic algorithm to adjust the uncertain parameters, calibrating the model for the measured indoor air temperature and relative humidity. The model performed well during the free-floating and ventilated stages (56 days) with a combined root mean square error (RMSE) of 1.6 °C for indoor air temperature and 8.3 % for the air relative humidity. The validation process involved assessing the applicability of the calibrated model using two additional datasets. For all the cases, comparing the simulation results with indoor environment measurements resulted in an RMSE of less than 2 °C for air temperature and less than 10 % for air relative humidity; these values compare favorably to the literature. The model achieved a 3.7 % mean relative error (MRE) in estimating monthly energy consumption for a minimally heated greenhouse. Given these results, the model is deemed sufficiently accurate and applicable for future investigations.

Parametric simulation tool for the enviro-economic evaluation of energy renovation strategies in residential buildings with life cycle thinking: PARARENOVATE-LCT

The EU regulations require long-term renovation strategies (LTRS) for the energy transition of the existing building stock, emphasising the importance of the whole-life carbon evaluation and the cost-effectiveness of the processes. The building performance simulation (BPS) tools combined with the integration of the life cycle thinking (LCT) are considered a promising approach for evaluating the renovation of buildings. Besides, the performance gap due to occupant behaviour (OB) and the uncertainty of the economic scenario is an essential barrier to the accurate assessment of renovation strategies in residential buildings. The objective of this study is to develop a simulation tool to evaluate the environmental and economic sustainability of energy renovations in residential buildings based on LCT, considering the OB diversity and economic uncertainty. For this, the study develops the PARARENOVATE-LCT tool. This script-based tool combines the dynamic BPS and the integration of the environmental life cycle assessment (LCA) and the economic life cycle cost (LCC), evaluating different renovation strategies in multiple scenarios based on the combination of multiple variables of archetype, climatic zone, OB patterns, economic scenario and orientation. The methodological tool is applied in a case study of the most common archetypes of single-family and multi-family residential buildings of the Basque Country, in northern Spain. The results show how the tool can prioritise strategies, analyse the significance of baseline scenario parameters, and measure the influence of the LCT application. This way, the study provides a methodological tool as a new approach towards developing policies and plans to answer the EU requirements.

Usability and fitness testing for building performance simulation tools

Architects and engineers who seek design decision aid for sustainable building and city design frequently experience decisional conflict and require support across the design process. Building performance simulations have become central to supporting the design process, but little is known about the fit and usability of simulation tools and the factors influencing the implementation of simulation-based design in practice. This paper presents a novel framework for simulation tool usability called USER-FIT. The framework defines usability based on ISO definitions, a review of evidence in the literature, and our experience supporting the development of the framework. USER-FIT provides six measures for modelers and software developers to test how a simulation tool is useful, usable, and satisfactory for the intended users to inform sustainable design decision-making. Further research and testing are needed to support better the acquisition and implantation of usability testing for building performance simulation tools and applications.

Multi-objective Optimization Design of Low-carbon Modular Building

In recently architectural research, there is a well-documented emphasis on energy-saving design optimization. However, there is a conspicuous deficiency in studies that address multi-objective optimization related to the long-term carbon emissions associated with building lifecycles. In this study, modular buildings in construction sites are taken as the research object, and box-type rooms are taken as the prototypical model. A set of multi-objective optimization methods for architectural design is established by series modeling tools, building performance simulation tools and NSGA-II non-dominated sorting genetic algorithm tools, combined with Python programming tools. This method is to optimize the reduction of carbon emissions, energy consumption and costs throughout the life cycle. The purpose of this investigation is to establish a methodology for assessing and optimizing architectural designs with a primary focus on carbon emissions during the design phase. The goal is to provide architects with practical insights to enhance their designs while simultaneously achieving intelligent, eco-friendly buildings.

Development of a crop growth model for the energy analysis of controlled agriculture environment spaces

In controlled environment agriculture spaces, the conditions fluctuate between photoperiod and dark period, with crops growing continuously. As crops grow, their impact on the energy demand and energy use, often estimated using a building performance simulation tool, becomes more prominent. In this paper, a dynamic crop model integrated into a building performance simulation tool is proposed to estimate the yield and heat gain/loss from crops by combining a growth model and an energy balance model of the crops. The developed growth model is an adjusted version of a greenhouse lettuce growth model modified for high-density controlled environment agriculture applications by calibrating the sensitive parameters for several indoor environment conditions (temperature, lighting, etc.) using an experimental growth dataset. The yield, the energy demand and the energy use were assessed for a case study modelled in TRNSYS. The results obtained using the greenhouse and developed growth models were compared to those generated with the experimental growth dataset. Depending on the indoor environment conditions, the difference in specific energy use estimated using the experimental growth dataset and the developed model varied between 0.1% and 3.5%, indicating that the model led to an acceptable level of accuracy. The dynamic crop model estimates yield and heat gain/loss from crops for various indoor environment conditions, which are essential for carrying out energy, financial, and environmental analyses.

Towards Sustainable Indoor Thermal Comfort in the Tropical Building Design: Comparative Performance Analysis of Fixed External Shading Elements and Differential Window Glass Thermal Properties

Tropical region is characterised by high outdoor solar radiation and temperature. These radiations penetrate into the interior particularly through the window glazing, thereby raising the indoor temperature with a resultant effect on high cooling energy demand (for comfortable indoor living condition). Of the identified three sustainable approaches towards inhibiting direct incoming indoor solar penetration in the tropical city of Ogbomoso, Nigeria, this study, through computer-based simulation technique, compared performance effectiveness of varying design interventions on the window composition/material adopted. Through multiple/iterative building performance simulation tool, DesignBuilder, the methodology involves virtual model of a three-bedroom residential building, typical of the prevailing building typology in the study area. This particular model served as the experimental control model. Three (3) variants of the control model, each with either externally mounted shading devices on the building envelope, or improved thermally resistant multilayer window glazing (i.e., double glazing) or low-emissivity coated window glazing material, were generated for individual performance effectiveness evaluation. All the four models were subjected to a twelve-month simulation cycle, to experience a year-round thermal conditions and evaluations individually. The results show that double-glazing window installation proved to be the most effective approach, with about 13.1 % improvement (i.e., solar radiation inhibition) on the indoor thermal gains. This is followed by the externally mounted shading devices (i.e., 11.1 % improvement) and the least inhibition (i.e., 5.0 %) was observed in the case of low-emissivity coated window glazing material. Adoption of double or more layers of glass panes in window fabrication for controlling indoor solar radiation penetration is therefore advised. Alternatively, integration of external window shading elements could be adopted. This study is directed towards reduction of cooling energy consumption in tropical buildings through efficient and sustainable indoor cooling mechanism capable of inhibiting solar gains into the building, with a focus on the performance roles and composition of windows in particular.

Between Fancy and Functionality: Comparative Thermal Performance Analyses of Selected External Building Shading Elements in Tropical Building Design

Tropical region is characterized by high temperature, arising from high solar radiation. Incoming near-infrared energy emanating from excessive direct sunlight leads to increase in the indoor temperature with its attendant indoor thermal discomfort. Thus, there is the need for protection of the interior from this excessive direct heating. One of such protective approaches is the introduction of exterior shading elements to block the incoming solar energy. To achieve this in a typical tropical city of Ogbomoso, Nigeria, several forms of exterior window shading elements are adopted predominantly based on individual preferences, fancies, etc., without scientific consideration for their effectiveness. This study therefore investigated performance effectiveness of each type, with a view to identifying the most effective shading element in the study area. The study adopted the use of multiple/iterative building performance simulation tool, DesignBuilder for evaluating indoor thermal performance of a typical three-bedroom residential building, with regard to four predominantly adopted fixed external shading elements in the study area. Virtual models of five variants of the building were subjected to energy performance simulation analysis, using weather data for Ogbomoso. While the first building tagged Building I was modelled without any shading element, to serve as the control building, the remaining four tagged Building II, Building III, Building IV and Building V were modelled with overhangs, side-fins, hybrids and louvres shading system respectively. Building V recorded highest reduction (56.55%) in the indoor solar gains. This was followed in the order of Building IV (23.90%), Building II (16.00%), and Building III (7.63%). Thus, effectiveness of external louvres system as an external shading device over side-fins and overhangs in the study area could be established. This research is necessary to minimize additional active energy required to reduce the indoor thermal discomfort arising from solar gains (through reduced annual space cooling loads). This will increase building energy efficiency and reduce carbon emissions for overall clean and safe global environment

Advances in the Co-Simulation of Detailed Electrical and Whole-Building Energy Performance

This article describes recent co-simulation advances for the simultaneous modeling of detailed building electrical distribution systems and whole-building energy performance. The co-simulation architecture combines the EnergyPlus® engine for whole-building energy modeling with a new Modelica library for building an electrical distribution system model that is based on harmonic power flow. This new library allows for a higher-fidelity modeling of electrical power flows and losses within buildings than is available with current building electrical modeling software. We demonstrate the feasibility of the architecture by modeling a simple, two-zone thermal chamber with internal power electronics converters and resistive loads, and we validate the model using experimental data. The proposed co-simulation capability significantly expands the capabilities of building electrical distribution system models in the context of whole-building energy modeling, thus enabling more complex analyses than would have been possible with individual building performance simulation tools that are used to date.

Development of a BLOCK zonal model in a BPS software to predict thermal stratification and air flows

An excellent way to obtain a detailed description of the air flows and temperature field in a zone is to perform accurate Computational Fluid Dynamics (CFD) simulations. Unfortunately, this is often prohibitive due to the powerful resources that are required, and the large computational times. As a consequence, several intermediate models between CFD and the standard well-mixed models have been proposed over the years. These are known as zonal models, and they aim at delivering sufficiently accurate predictions of the thermal comfort in a room, for long periods (months or even years), and with substantially shorter computational times. However, none of these models has yet been implemented in a building performance simulation (BPS) tool. In this work, we have developed and implemented a BLOCK zonal model [1,2] within the IDA ICE (BPS) software. A multi-node 1D model for the prediction of vertical temperature gradients is used, together with flow element theory and an appropriate algorithm for the estimation of view-factors in non-convex geometries with obstacles. The paper presents the theoretical background of the model along with advice on its range of applicability. Finally, the model is validated against several test cases, showing its suitability in predicting the thermal stratification.

Optimization Bundle Paths of the Building Envelope for Zero-Carbon Strategies

Improving building energy performance with minimum emission and cost is important for zero-carbon strategies. In this regard, this study mainly focuses on the envelope of an apartment block. The aim is to investigate the tripartite relationship between energy performance, CO2 emission, and cost by using different wall and roof insulation materials, and various glazing types in a typical reinforced concrete five-floor apartment block in Istanbul, Turkey. In a building performance simulation tool - Cove. Tool, material alternatives’ impacts on energy use, cost, and CO2 emission are calculated. Consequently, 32 different design bundles are generated. Finally, the most advantageous material combination is explored from the design combinations to make cost-conscious, performance-driven, and environmentally-friendly decisions.

Reverse passive strategy exploration for building massing design-An optimization-aided approach

In building massing design, using passive design strategies is a critical approach to reducing energy consumption while offering comfortable indoor environments. However, it is often impractical for architects to systematically explore passive design strategies at the outset of the building massing design and architectural form-finding processes, which may result in inefficient or ineffective utilization of the strategies. To address this issue, this study presents a reverse passive design strategy exploration approach that leverages the capability of computational optimization and parametric modeling to help architects identify feasible passive design strategies for building massing design. The approach is achieved using a building massing design generation and optimization tool, called EvoMass, and various building performance simulation tools in Rhino-Grasshopper. The optimization can produce site-specific design references that reflect rich performance implications associated with passive design strategies, such as atriums and self-shading. As such, architects can screen out promising passive design strategies corresponding to different performance factors from the optimization result. Two case studies related to daylighting, sky exposure, and solar heat utility are presented to demonstrate the approach, and the relevant utility and limitations are discussed.

Optimizing heating operation via GA- and ANN-based model predictive control: Concept for a real nearly-zero energy building

Using a simulation- and optimization-based framework that leverages artificial neural networks for the model predictive control of space heating operation, machine learning techniques are explored to predict the energy performance of a real nearly zero energy building located in Benevento (Southern Italy, Mediterranean climate). The framework's goal is to minimize heating energy costs and thermal discomfort by providing optimal values of setpoint temperatures on a day-ahead planning horizon based on weather forecasts. To achieve this, a Pareto multi-objective approach is applied, which considers thermal comfort via the adaptive theory of ASHRAE 55, assessing a comfort penalty function. The optimization problem is solved using a genetic algorithm in the MATLAB® environment. Objective functions are evaluated using the coupling between MATLAB® and EnergyPlus, which is used as building performance simulation tool. Multi-criteria decision-making is performed to select an optimal solution from the Pareto front while setting a limit to the comfort penalty. To test the framework, EnergyPlus weather data is used to simulate weather forecasts for typical days of the winter season. Two different economic scenarios are simulated in order to be able to analyze both conditions and given the variability of the electricity price. For the different days tested, the best results in terms of savings achieved through the proposed solution are on Feb. 28, corresponding to the coldest day and the highest energy cost, with daily savings of 26% compared to a reference control with a fixed setpoint of 21 °C, while maintaining similar comfort performance. The results suggest that optimized control is a crucial aspect of sustainable building design, and the proposed framework can be virtually implemented or integrated into automation systems for real-time model predictive control.

Windows of Opportunities: Orientation, Sizing and PV-Shading of the Glazed Area to Reduce Cooling Energy Demand in Sub-Sahara Africa

In hot climates, such as sub-Sahara Africa, window sizing and orientation pose challenges as they add, through solar insolation, to the building cooling energy demand and thus the cause of indoor overheating risk. This risk can be reduced through passive building-design-integrated measures, e.g., optimizing the window size, orientation and solar shading strategies. Through an IDA-ICE building performance simulation tool, the current study explores the impact of window size, optimization and building-integrated PV panels as shading strategies on cooling energy demands in three cities (Niamey, Nairobi and Harare) in sub-Sahara Africa. Results show that thermal comfort and cooling energy demand are sensitive to a window-to-wall ratio (WWR) > 70%, while the need for artificial lighting is negligible for a WWR > 50%, particularly in the north for cities in the Southern hemisphere and the south in the Northern hemisphere. A WWR > 70% in the east and west should be avoided unless shading devices are incorporated. Internal blinds perform better in improving occupant thermal comfort but increase artificial lighting while integrating PV panels, as external shading overhangs reduce cooling energy but also produce energy that can be utilized for building services, such as air conditioning. In this study, the results and implications of the optimization of window size, orientation and building-integrated shading and operation are discussed.

Empirical validation of co-simulation models for adaptive building envelopes

The thermal performance of adaptive building envelopes can be evaluated using building performance simulation tools. Simulation capabilities and accuracy in predicting the dynamic behaviour of adaptive building envelopes can be enhanced through co-simulation. However, it is unclear how accurately co-simulation can predict the performance of adaptive building envelopes and how the accuracy of adaptive building envelope models created in co-simulation setups can be assessed and validated. Therefore, this study presents new evidence on the empirical validation of co-simulation setups for adaptive building envelopes by establishing an assessment framework to determine the extent to which they can accurately represent the real world. The framework was applied to a case study to validate a co-simulation setup for a blind automation system using monitored data from MATELab, a full-scale outdoor test facility with realistic indoor and outdoor conditions. The validation of the co-simulation model of MATELab resulted in a median CV-RMSE index, a measure of model accuracy, of 5.9%. This indicates that the simulated data points have a small variance relative to the measured data points, showing a good model fit. In the future, modellers from the façade community can use the assessment framework for their co-simulation setups.

Parametric Design and Spatial Optimization of East–West-Oriented Teaching Spaces in Shanghai

The goal of the current study was to determine the appropriate spatial shapes for classroom occupants while saving energy. The research used parametric design and Genetic Algorithm (GA) to achieve this. Four recognized performance indicators, Energy Use Intensity (EUI), Useful Daylight Illuminance (UDI), Daylight Factor (DF), and Daylight Autonomy (DA), were used as the evaluation indexes for the research. The tests took place in six east–west-oriented classrooms at Shanghai University, China. The methodology was based on four steps: (1) parametric 3D modeling by Rhino and Grasshopper; (2) using building performance simulation tools; (3) running algorithm optimization; (4) outputting the useful results. The results proved that the methodology worked successfully in reducing energy consumption: optimized classrooms could be reduced by 7.5~14.5%, and classrooms with east directions were generally 4.8~8.3% more efficient than west-facing ones. The indoor lighting environment was also significantly improved, being slightly better than north–south-oriented classrooms in terms of the UDI index (60~75%) and inferior (but still high) in terms of the DF (4.0~7.0%) and DA (60~80%) indexes. The conclusion can help save design time in the early design process of teaching spaces.

A framework for obtaining a BIM-compatible design solution based on quantitative decisions on building performance

The direction towards high-performance buildings soars the complexity of the design process. Therefore, Building Performance Simulation (BPS) tools are used to aid designers to realize the implications of early design decisions. Coupling BPS tools and geometrical tools featured with Building Information Modeling (BIM) has recently received much attention. Yet, Computer-Aided Drafting (CAD-based) geometrical tools are still the preferred choice for a large portion of designers. Therefore, this paper aims to develop a Performance-based Design Framework (PbDF) to aid designers in obtaining an optimal design solution compatible with BIM software based on a quantitative decision that satisfies both daylighting, energy, and cost of buildings at the early stage of design. The PbDF included 3 D modeling, daylight and energy simulations, cost calculations, decision-making using Technique for Order by Similarity to Ideal Solution (TOPSIS), and BIM generation. The framework was tested through two stages and validated by face validity approach. The test results demonstrated that the proposed framework can assist designers to efficiently propose high-performance designs and send them to BIM software to complete the rest of the tasks required for design and construction. The PbDF was accepted as reasonable for its intended purpose by people who are knowledgeable about the performance-based design.

Occupant centric energy renovation strategy for hospital and restaurant building envelop using distinct modellingtools: A case study from low-income cultural context

A building envelope has a significant influence on the overall energy consumption of a building. Presently, Building Information Modelling (BIM) and Building Performance Simulation (BPS) tools are advanced and cost-efficient options for analyzing and improving the energy-efficient building envelop. However, existing BIM-BPS-based studies incorporate several buildings envelop parameters that account for static occupancy profiles. This contributes to higher discrepancies between the actual and simulated energy consumption. Also there is a dearth of studies about the hospital and restaurant building envelop by considering the local construction materials. Thus,the key aim of this study is to perform a stochastic occupant-centric building energy assessment for hospital and restaurant building envelop using agent based modelling (ABM) and BIM-BPS tools. Initially, stochastic occupancy, HVAC and lighting ON/OFF profiles were generated using a robust ABM-BIM approach followed by the real-time data gathering for verifications and energy model construction. Afterwards, the building energy performance was evaluated using the BPS tools, while initial energy consumption data was calibrated using the pre-installed smart meter data in Chittagong, Bangladesh. The study also empowers the assessments of CO2 reduction, carbon credits, life cycle, and payback time analysis from the sustainable built environment perspective. The findings show the highest amount of monthly energy-saving for the hospital (Case 3) and restaurant (Case 3) buildings around 37.42 % (July) and 32.52 % (October), respectively, while considering the local envelop materials. Moreover, the maximum amount of CO2 reduction was 17.71 tons/year and 12.31 tons/year, and the equivalent earned carbon credits were 88,539.5 BDT/year and 61,524.1 BDT/year for hospital and restaurant buildings respectively. Additionally, the study calculates the payback period for both buildings by considering different local envelop materials. The findings of this study have presented a new framework between ABM, BIM and BPS based building envelop simulation, and contribute to proper building envelop material selection in low-income cultural contexts. Lastly, the study has provided areas for further studies such as the need for a comprehensive model construction process, seasonal occupancy patterns, climatic factors, and composite materials study for different envelop systems which serves as limitations of this current study.

Characterization of the density-driven counter-flow through a doorway using Large Eddy Simulation

The density-driven bidirectional flow through an open doorway is of prime importance for ventilation and heat distribution between rooms in buildings. Although this flow has been extensively studied in the past, some important flow characteristics, such as unsteady flow phenomena, have not been documented in detail. Therefore, a high-resolution Large Eddy Simulation (LES) of the bulk flow through a doorway is performed. This LES can also serve as a reference solution to compare the accuracy of simpler evaluation methods, from the standard theoretical model calibrated using a discharge coefficient (Cd) to CFD solving the Reynolds-Averaged Navier-Stokes (RANS) equations. Based on LES results, the bidirectional flow can generate turbulent mixing in the middle of the doorway. However, the effects remain limited to the close vicinity of the neutral plane. The bidirectional airstream in the doorway further develops into two non-isothermal jets that entrain a fraction of the airflow. Furthermore, the two jets create large unsteady flow structures when they expand in the adjoining rooms. The results show that unsteady RANS is a good alternative to the resource-intensive LES if the analysis of turbulent jets is not of interest. The standard theoretical model demonstrates that two-dimensional contraction is the dominant effect driving the Cd value, while the viscous effects have a minor influence. Unlike previous studies, LES results show that viscous effects tend to increase the Cd as they moderate the contraction effect. This paper also provides guidelines for the laboratory measurement of Cd and its use in building performance simulation tools.