Empirical validation of building energy simulation programs

The largest-ever exercise to validate dynamic thermal simulation programs (DSPs) of buildings has recently been completed. It involved 25 program/user combinations from Europe, the USA and Australia, and included both commercial and public domain programs. Predictions were produced for three single-zone test rooms in the UK. These had either a single-glazed or double-glazed south-facing window, or no window at all. In one 10-day period the rooms were intermittently heated and in another 10-day period they were unheated. The predictions of heating energy demands and air temperatures were compared. The observed interprogram variability was highly likely to be due to inherent differences between the DSPs, rather than the way they were used. Predictions of the difference in performance of two rooms were no more consistent than predictions of the absolute performance of a single room. By comparing the predictions with the measurements and taking due account of experimental uncertainty, the DSPs that are likely to contain significant internal errors are distinguished from those which, in these tests, performed much better. The likely sources of internal error are discussed. It is recommended that empirical validation exercises should consist of an initial blind phase in which program users are unaware of the actual measured performance of the building, and then an open phase in which the measurements are made available. The work has produced five empirical validation benchmarks, which have significant practical benefits for program users, vendors and potential purchasers. There is considerable scope for improving the predictive ability of DSPs and so suggestions for further work are made.     

Simplified daylighting energy savings for non-daylighting building energy simulation programs

The California Legislature mandated the California Energy Commission (CEC) to establish and periodically update energy efficiency standards for new buildings. To this end, a sensitivity analysis was conducted by the Standards Development Office of the California Energy Commission for nonresidential buildings. The purpose of this parametric analysis was to determine which variations in building parameters actually have significant energy impacts.A “generic” building model was developed and implemented in conducting this sensitivity analysis. The generic model was used as an analytical tool in modeling the energy impact of building parameter variations, as well as architectural and mechanical energy-saving measures on the energy use of each module. It is recognized that the level of significant energy impact is equivalent to, or bounded by the accuracy of the energy analysis tools in predicting energy usage in actual buildings. For the computer program used, DOE 2.1A this accuracy is within ±5%.Since DOE 2.1A and most of the other building energy simulation programs do not have daylighting algorithms, another calculation tool was used to determine daylight availability and lighting power reduction on an hour-by-hour basis for each orientation. This is accomplished with a daylight reduction factor (DRF).Quicklite, a simplified daylighting program, calculated footcandle (lux) levels based on outdoor ambient light levels, physical room dimensions and properties. To assess the impact of the Quicklite calculated footcandle (lux) levels on artificial lighting use, a control scheme was assumed, and a DRF was calculated based on annual sky conditions by climate zone.Once the DRF values are known for each orientation, the electric lighting schedule can be modified. A new profile number, representing the proportion of installed lighting switched on at that hour, replaced the daily lighting schedules when daylighting was utilized (09:00 – 17:00). To test this methodology, a sensitivity analysis was conducted between DOE 2.1A with Quicklite modifications and DOE 2.1B which has a daylighting preprocessor. The results displayed a 3.6% variation in total energy use.We conclude that daylighting calculations for design days using simplified programs can be used to approximate daylighting energy savings in building energy simulation programs that allow zoned lighting schedules but do not calculate daylight contributions.     

A green roof model for building energy simulation programs

A physically based model of the energy balance of a vegetated rooftop has been developed and integrated into the EnergyPlus building energy simulation program. This green roof module allows the energy modeler to explore green roof design options including growing media thermal properties and depth, and vegetation characteristics such as plant type, height and leaf area index. The model has been tested successfully using observations from a monitored green roof in Florida. A preliminary set of parametric tests has been conducted on prototypical 4000 m² office buildings in Chicago IL and Houston TX. These tests focus on evaluating the role of growing media depth, irrigation, and vegetation density (leaf area index) on both natural gas and electricity consumption. Building energy consumption was found to vary significantly in response to variations in these parameters. Further, this response depended significantly on building location (climate). Hence, it is evident that the green roof simulation tool presented here can serve a valuable role in informing green roof design decisions.     

Overview of pressure coefficient data in building energy simulation and airflow network programs

Wind pressure coefficients (C_p) are influenced by a wide range of parameters, including building geometry, facade detailing, position on the facade, the degree of exposure/sheltering, wind speed and wind direction. As it is practically impossible to take into account the full complexity of pressure coefficient variation, building energy simulation (BES) and Airflow network (AFN) programs generally incorporate it in a simplified way. This paper provides an overview of pressure coefficient data and the extent to which they are currently implemented in BES–AFN programs. A distinction is made between primary sources of C_p data, such as full-scale measurements, reduced-scale measurements in wind tunnels and computational fluid dynamics (CFD) simulations, and secondary sources, such as databases and analytical models. The comparison between data from secondary sources implemented in BES–AFN programs shows that the C_p values are quite different depending on the source adopted. The two influencing parameters for which these differences are most pronounced are the position on the facade and the degree of exposure/sheltering. The comparison of C_p data from different sources for sheltered buildings shows the largest differences, and data from different sources even present different trends. The paper concludes that quantification of the uncertainty related to such data sources is required to guide future improvements in C_p implementation in BES–AFN programs.     

Improved model for the thermal performance calculation of non-planar window frames for building simulation programs

Windows are a key factor for designing energy-efficient buildings, particularly the frame area that can produce high thermal bridging. This paper deals with accurately estimating heat transfer through window frames under fluctuating film coefficients. The one-dimensional frame conductance model traditionally used by building simulation programs is analysed and an alternative model is proposed, which takes into account the non-planar morphology of studied frames. This model shows a positive agreement with the results obtained from a two-dimensional heat-transfer simulation program, demonstrating that the thermal performance of high-conductance non-planar frames strongly depends on the ratio between the boundary surface area and the projected frame area. According to the results, the traditional conductance model seems to be suitable for all frames with a thermal transmittance lower than 5?W/m²K; however, frames with a U-factor higher than 6.2?W/m²K need an alternative conductance model that better reflects the 2D nature of frame sections.     

An automated IFC-based workflow for building energy performance simulation with Modelica

Steadily increasing use of Building Information Modeling (BIM) in all phases of building's lifecycle, together with more attention for openBIM and growing software support for the most recent version of the Industry Foundation Classes (IFC 4) have created a very promising context for an even broader application of Building Energy Performance Simulation (BEPS). At the same time, an urgent need for modeling guidelines and standardization becomes evident. A well-defined BIM-based workflow and a set of tools that fully exploit and extend the possibilities of the openBIM-technology can make the difference when it comes to reliability and cost of BEPS to design, build and operate high-performance buildings. This paper describes the essential elements of this integrated workflow, explains why openBIM comprises much more than just a standardized file-format and what is achieved with the already available technology, namely the Information Delivery Manual (IDM) and a newly developed Model View Definition. This MVD is tailored to the needs of Building Energy Performance Simulation (BEPS) that uses the Modelica language together with a specific library (IDEAS) and can easily be adapted to other libraries. In this project, several tools have been developed to closely integrate BEPS and IFC4. The simulation engine now gets the vast majority of the required input directly from the IFC4-file. For the implementation of the tools, the PYTHON language and the open source library IfcOpenShell are used. A case study is presented, that was used for extensive tests of the proposed approach and the implemented tools. The essential benefits of this new workflow are illustrated, and the feasibility is demonstrated. Opportunities and remaining bottlenecks are identified to encourage further development of BIM software to fully support IFC4 as an information source for BEPS. Besides some improvements of the proprietary class structure and functionality, enabling the export of IFC4 files based on custom MVDs is one required key feature.     

Applying the building energy simulation test (BESTEST) diagnostic method to verification of space conditioning equipment models used in whole-building energy simulation programs

Validation of building energy simulation programs consists of a combination of empirical validation, analytical verification, and comparative analysis techniques. An analytical verification and comparative diagnostic procedure was developed to test the ability of whole-building simulation programs to model the performance of unitary space-cooling equipment that is typically modeled using manufacturer design data presented as empirically derived performance maps. This procedure is based on the International Energy Agency (IEA) building energy simulation test (BESTEST) diagnostic method and systematically tests whole-building energy simulation software by comparing results from such software to analytical solutions that were developed for the test cases. Field trials of the new procedure were conducted by researchers from nations participating in the IEA Solar Heating and Cooling (SHC) Programme Task 22, using a number of detailed hourly simulation programs from Europe and the US, including: CA-SIS, CLIM2000, ENERGYPLUS, PROMETHEUS, TRNSYS-TUD, and two versions of DOE-2.1E. This article also includes discussion about simulation validation methodologies.     

建筑能耗模拟在能源审计中的应用

以某大厦为例,阐述了建筑能耗模拟时的模型校验方法,并利用经过校验的模型进行了能耗预测和节能量计算.指出在进行能源审计时,必须用实际的建筑资料和历史能耗数据对所建模型进行校验,只有经过实测能耗数据校验的模型才能对建筑能耗进行准确预测;通过能耗模拟进行能耗预测和节能量计算,可以节省大量的时间,且更加准确、直观,具有很好的应用前景.     

Comparing computer run time of building simulation programs

This paper presents an approach for comparing the computer run time of building simulation programs. The computing run time of a simulation program depends on several key factors, including the calculation algorithm and modeling capabilities of the program, the run period, the simulation time step, the complexity of the energy models, the run control settings, and the software and hardware configurations of the computer used to run the simulation. To demonstrate this approach, we ran simulations for several representative DOE-2.1E and EnergyPlus energy models. We then compared and analyzed the computer run times of these energy models.     

Assessing building performance by simulation

This paper characterizes the state-of-the-art in the assessment of a building's performance by computer simulation. Theoretical and application aspects are outlined and current developments are described which will help to ensure that simulation can be effectively applied in practice by designers with limited knowledge of the technology. Remaining problems are identified.     

Ground reflectivity in the context of building energy simulation

This paper stresses the importance of a proper estimate of ground reflectivity in building energy simulation, particularly in the presence of snow. Several factors influencing ground reflectivity are reviewed. Two models for estimating ground reflectivity in the presence of snow are developed. The first one is based on the number of days with snow depth greater than 5 cm, and is appropriate for use with ‘typical’ meteorological years. The second makes use of actual records of snow depth, and takes into account snow accumulation, ageing and melting to calculate reflectivity values. The algorithms were implemented in ESP-r and tested by simulating a passive solar house for six Canadian locations. The sensible heating load calculated by the simulations is reduced by up to 10.9% on a yearly basis, and 23.3% on a monthly basis, when the ground reflectivity takes into account the presence of snow.     

Partnership in building energy performance contracting

Building energy performance contracting is a business strategy to assist building owners overcome the financial barriers for improving the energy performance of their buildings. In return for the investments made into the energy-saving measures, the energy service contractors would share with the building owners the energy cost saving. Although the contractual arrangement is meant to create a win–win situation, disappointments could arise due to mismatches between the expected and actual outcomes. From a micro-economics viewpoint, the key factors contributing to the failure of a building energy performance contract are reviewed. To solve the commonly encountered problems in building energy performance contracting, it is proposed the conventional performance contract is replaced with a partnership formed jointly by the building owner and the energy service contractor, with the latter assuming the role of the performance contractor. This would unite the goals of the two parties and cultivate genuine cooperation between them. The key features for this new contractual arrangement are described along with how this arrangement could resolve typical energy performance contracting problems.     

Whole building energy simulation and energy saving potential analysis of a large public building

This article explores how to use EnergyPlus to construct models to accurately simulate complex building systems as well as the inter-relationships among sub-systems such as heating, ventilation and air conditioning (HVAC), lighting and service hot water systems. The energy consumption and cost of a large public building are simulated and calculated for Leadership in Energy and Environmental Design (LEED) certification using EnergyPlus. American Society of Heating, Refrigerating and Air Conditioning Engineers (ASHRAE) baseline model is constructed according to ASHRAE 90.1 standard and the comparison of annual energy consumption between ASHRAE baseline model and proposed model is carried out. Moreover, an energy efficiency (EE) model is built based on the design model. Meanwhile, other energy conservation measures (ECMs) such as daylighting dimming and occupant sensors are considered. The simulation results show 4.7% electricity consumption decrease but 6.9% gas consumption increase of the EE model compared to ASHRAE baseline model. In summary, the annual energy cost of the EE model is reduced by 7.75%.     

Partnership in building energy performance contracting

Building energy performance contracting is a business strategy to assist building owners overcome the financial barriers for improving the energy performance of their buildings. In return for the investments made into the energy-saving measures, the energy service contractors would share with the building owners the energy cost saving. Although the contractual arrangement is meant to create a win-win situation, disappointments could arise due to mismatches between the expected and actual outcomes. From a micro-economics viewpoint, the key factors contributing to the failure of a building energy performance contract are reviewed. To solve the commonly encountered problems in building energy performance contracting, it is proposed the conventional performance contract is replaced with a partnership formed jointly by the building owner and the energy service contractor, with the latter assuming the role of the performance contractor. This would unite the goals of the two parties and cultivate genuine cooperation between them. The key features for this new contractual arrangement are described along with how this arrangement could resolve typical energy performance contracting problems.     

Achieving informed decision-making for net zero energy buildings design using building performance simulation tools

Building performance simulation (BPS) is the basis for informed decision-making of Net Zero Energy Buildings (NZEBs) design. This paper aims to investigate the use of building performance simulation tools as a method of informing the design decision of NZEBs. The aim of this study is to evaluate the effect of a simulation-based decision aid, ZEBO, on informed decision-making using sensitivity analysis. The objective is to assess the effect of ZEBO and other building performance simulation tools on three specific outcomes: (i) knowledge and satisfaction when using simulation for NZEB design; (ii) users’ decision-making attitudes and patterns, and (iii) performance robustness based on an energy analysis. The paper utilizes three design case studies comprising a framework to test the use of BPS tools. The paper provides results that shed light on the effectiveness of sensitivity analysis as an approach for informing the design decisions of NZEBs.     

Diagnostic test cases for verifying surface heat transfer algorithms and boundary conditions in building energy simulation programs

Verification and validation are crucial in developing and implementing models. Although there are standards to test energy simulation software, this article describes an additional set of eight test cases that are a combination of analytical cases and numerical cases for solid conduction heat transfer. These tests focus on diagnosing and verifying conductive heat transfer algorithms and boundary conditions in building envelopes or fabrics. As an example, EnergyPlus versions 5, 6 and 7 are tested using these eight test cases. The test cases were useful for detecting several bugs in the code. The authors recommend these test cases as useful complements to existing verification test cases for building envelopes.     

Occupant behavior models: A critical review of implementation and representation approaches in building performance simulation programs

Occupant behavior (OB) in buildings is a leading factor influencing energy use in buildings. Quantifying this influence requires the integration of OB models with building performance simulation (BPS). This study reviews approaches to representing and implementing OB models in today’s popular BPS programs, and discusses weaknesses and strengths of these approaches and key issues in integrating of OB models with BPS programs. Two key findings are: (1) a common data model is needed to standardize the representation of OB models, enabling their flexibility and exchange among BPS programs and user applications; the data model can be implemented using a standard syntax (e.g., in the form of XML schema), and (2) a modular software implementation of OB models, such as functional mock-up units for co-simulation, adopting the common data model, has advantages in providing a robust and interoperable integration with multiple BPS programs. Such common OB model representation and implementation approaches help standardize the input structures of OB models, enable collaborative development of a shared library of OB models, and allow for rapid and widespread integration of OB models with BPS programs to improve the simulation of occupant behavior and quantification of their impact on building performance.