Simulation-based coefficients for adjusting climate impact on energy consumption of commercial buildings

This paper presents a new technique for and the results of normalizing building energy consumption to enable a fair comparison among various types of buildings located near different weather stations across the United States. The method was developed for the U.S. Building Energy Asset Score, a whole-building energy efficiency rating system focusing on building envelope, mechanical systems, and lighting systems. The Asset Score is based on simulated energy use under standard operating conditions. Existing weather normalization methods such as those based on heating and cooling degrees days are not robust enough to adjust all climatic factors such as humidity and solar radiation. In this work, over 1000 sets of climate coefficients were developed to separately adjust building heating, cooling, and fan energy use at each weather station in the United States. This paper also presents a robust, standardized weather station mapping based on climate similarity rather than choosing the closest weather station. This proposed simulated-based climate adjustment was validated through testing on several hundreds of thousands of modeled buildings. Results indicated the developed climate coefficients can adjust the climate variations to enable a fair comparison of building energy efficiency.     

A study of energy efficiency of private office buildings in Hong Kong

A benchmark study of the energy efficiency of private office buildings in Hong Kong was conducted in 2002 because energy efficiency was declining. In the study, private office buildings were divided into five user groups. For each group, a multiple regression model was developed to find the relationship between Energy Use Intensities (EUIs) and other factors, such as operating hours, for normalization and benchmarking purposes. In this paper we make use of the regression results to study the energy efficiency of private office buildings by different grades. In Hong Kong, office buildings are divided into three grades (A, B, and C) based on the quality of the facility, which is reflected in rental values; a Grade A office building denotes expensive luxury. We found that the EUI of Grade A office buildings is the highest, consuming over 50% of the total energy used in office buildings. Recently, the annual EUI of office buildings has improved even though Grade A floor space is increasing. This may be due to the promotion of the energy efficiency program launched in the last decade.     

A decision tree method for building energy demand modeling

This paper reports the development of a building energy demand predictive model based on the decision tree method. This method is able to classify and predict categorical variables: its competitive advantage over other widely used modeling techniques, such as regression method and ANN method, lies in the ability to generate accurate predictive models with interpretable flowchart-like tree structures that enable users to quickly extract useful information. To demonstrate its applicability, the method is applied to estimate residential building energy performance indexes by modeling building energy use intensity (EUI) levels. The results demonstrate that the use of decision tree method can classify and predict building energy demand levels accurately (93% for training data and 92% for test data), identify and rank significant factors of building EUI automatically. The method can provide the combination of significant factors as well as the threshold values that will lead to high building energy performance. Moreover, the average EUI value of data records in each classified data subsets can be used for reference when performing prediction. One crucial benefit is improving building energy performance and reducing energy consumption. Another advantage of this methodology is that it can be utilized by users without requiring much computation knowledge.     

Genetic-algorithm based approach to optimize building envelope design for residential buildings

A simulation–optimization tool is developed and applied to optimize building shape and building envelope features. The simulation–optimization tool couples a genetic algorithm to a building energy simulation engine to select optimal values of a comprehensive list of parameters associated with the envelope to minimize energy use for residential buildings. Different building shapes were investigated as part of the envelope optimization, including rectangle, L, T, cross, U, H, and trapezoid. Moreover, building envelope features were considered in the optimization analysis including wall and roof constructions, foundation types, insulation levels, and window types and areas. The results of the optimization indicate rectangular and trapezoidal shaped buildings consistently have the best performance (lowest life-cycle cost) across five different climates. It was also found that rectangle and trapezoid exhibit the least variability from best to worst within the shape.     

Decoupling of building energy use and climate

Energy use intensity (EUI) and climate have a well documented correlation, which is generally applied in building energy management. Green buildings have sought to greatly reduce energy consumption and a number of examples are documented in the literature. A sample of high performance buildings constructed in a variety of global locations is analyzed here, and provides evidence that measures to reduce energy consumption have reduced EUI to the point where its correlation with heating degree days is no longer apparent. This result suggests that end-user behaviour is the next major hurdle in lowering the energy consumption of greener buildings.     

Analysis of a simplified calibration procedure for 18 design-phase building energy models

This paper evaluates the accuracy of 18 design-phase building energy models, built according to LEED Canada protocol, and investigates the effectiveness of model calibration steps to improve simulation predictions with respect to measured energy data. These calibration steps, applied in professional practice, included inputting actual weather data, adding unregulated loads, revising plug loads (often with submetered data), and other simple updates. In sum, the design-phase energy models underpredicted the total measured energy consumption by 36%. Following the calibration steps, this error was reduced to a net 7% underprediction. For the monthly energy use intensity (EUI), the coefficient of variation of the root mean square error improved from 45% to 24%. Revising plug loads made the largest impact in these cases. This step increased the EUI by 15% median (32% mean) in the models. This impact far exceeded that of calibrating the weather data, even in a sensitivity test using extreme weather years.     

Simulation and visualization of energy-related occupant behavior in office buildings

In current building performance simulation programs, occupant presence and interactions with building systems are over-simplified and less indicative of real world scenarios, contributing to the discrepancies between simulated and actual energy use in buildings. Simulation results are normally presented using various types of charts. However, using those charts, it is difficult to visualize and communicate the importance of occupants’ behavior to building energy performance. This study introduced a new approach to simulating and visualizing energy-related occupant behavior in office buildings. First, the Occupancy Simulator was used to simulate the occupant presence and movement and generate occupant schedules for each space as well as for each occupant. Then an occupant behavior functional mockup unit (obFMU) was used to model occupant behavior and analyze their impact on building energy use through co-simulation with EnergyPlus. Finally, an agent-based model built upon AnyLogic was applied to visualize the simulation results of the occupant movement and interactions with building systems, as well as the related energy performance. A case study using a small office building in Miami, FL was presented to demonstrate the process and application of the Occupancy Simulator, the obFMU and EnergyPlus, and the AnyLogic module in simulation and visualization of energy-related occupant behaviors in office buildings. The presented approach provides a new detailed and visual way for policy makers, architects, engineers and building operators to better understand occupant energy behavior and their impact on energy use in buildings, which can improve the design and operation of low energy buildings.     

Parametric analysis of alternative energy conservation measures in an office building in hot and humid climate

The growth of demand for electrical energy in the rapidly expanding towns, cities and industries exceeds the growth of the power being made available. Therefore, energy conservation is becoming an increasingly important issue in Saudi buildings. The objective of this study was to investigate the impact of alternative energy conservation measures on energy requirements in office buildings in hot–humid climates. The study was conducted on a five-story office building located in Dammam, Saudi Arabia, which has been in use since 1998. Different types of HVAC systems were selected and different feasible and practical operational energy conservation measures (ECMs) were evaluated using the energy simulation software of Visual DOE 4.0. Previous studies conducted in this area were reviewed. Data was collected through review of design drawings, building audit and the analysis of 4 years of utility bills. All the collected data was analyzed and the utility bills data was used to calibrate the base case of the existing building using Visual DOE energy simulation software. Conclusions and recommendations were developed for conserving energy using various appropriate ECMs in office buildings in hot and humid climates.     

TEASER: an open tool for urban energy modelling of building stocks

The energy supply of buildings in urban contexts is undergoing significant changes. The increase of renewable sources for electrical and thermal energy generation will require flexible and secure supply systems. To reflect and consider these changes in energy systems and buildings, dynamic simulation is one key element. Sparse and limited access to detailed building information as well as computing time are challenges for building simulation on urban-scale. In addition, data acquisition and modelling for building performance simulation (BPS) are time-consuming and error-prone. To enable the use of BPS on urban-scale, this paper presents TEASER, an open framework for urban energy modelling of building stocks (open-source at https://github.com/RWTH-EBC/TEASER). TEASER provides an interface for multiple data sources, data enrichment and export of ready-to-run Modelica simulation models. The paper presents TEASER's methodology and package structure. Three use cases show TEASER's capabilities on the building, neighbourhood and urban scales.     

Learning by playing – teaching energy simulation as a game

Being able to read thermal simulation results and to adapt one's design accordingly has become an essential skill for graduating and practicing architects. This article proposes and evaluates an innovative way of how this skill can be taught via a 90-min in-class exercise or ‘game’ based on DesignBuilder/EnergyPlus. The game was tested in a class of 47 architecture students who competed to generate the lowest energy use intensity (EUI) for an office building in Boston. Design upgrades were associated with a cost premium and the overall upgrade budget was capped. The EUIs of the 10 final submissions were 22–31% below the base variant. While student essays revealed a clear preference for game-based learning vis-a-vis conventional teaching methods, the authors further propose that the game nourishes the emergence of an energy modelling ‘culture’ within schools of architecture that may lead to enhanced communication between architects and energy modellers.     

A multi-layer approach for estimating the energy use intensity on an urban scale

Various governments are planning their cities to be climate responsive by reducing the energy consumption and carbon emissions according to different scenarios whilst maintaining good indoor comfort conditions. A robust and reliable tool that can estimate the Energy Use Intensity (EUI) of a city is required. This paper presents a new bottom-up engineering-based multi-layer approach able to analyse the energy performance of existing settlements of every size by retaining as much information as possible about their complexities. The process involves i) creating a 3D model of the urban area, ii) building up templates representing different building characteristics such as functions, the age-band of the buildings and operating schedules, iii) running dynamic thermal simulations and iv) displaying the EUI or total energy demand in the 3D model which can be post-processed for further analysis. This approach offers a flexible simulation process according to various purposes, which is particularly useful in decision-making for urban energy retrofitting or planning for new areas. The hourly high-resolution outcomes would benefit the detailed analysis of energy efficiency strategies in order to achieve carbon reduction. The application of this approach is demonstrated for the case of Yuzhong district in Chongqing municipality, China.     

经济型酒店能源基准工具研究

我国经济型酒店能源目前常用 EUI（用能强度）单位面积能耗表示,但是将来用 EUI 代理成为发展趋势,在某些发达国家已被广泛采用。讨论了应用酒店能源基准工具应注意的问题。该能源基准利用多元线性回归分析,将 EUI 作为因变量,将若干能耗影响因素作为自变量,应用最小二乘拟合回归方程作为能源基准。该能源基准评价最终用能源利用率（能效比）表示,它是实际 EUI 与预测 EUI 二者之比的百分数。实际 EUI 根据现场能源计算获得,预测 EUI 根据回归方程计算获得。并给出两个能源基准的评价实例。     

Contrasting the capabilities of building energy performance simulation programs

For the past 50 years, a wide variety of building energy simulation programs have been developed, enhanced and are in use throughout the building energy community. This paper is an overview of a report, which provides up-to-date comparison of the features and capabilities of twenty major building energy simulation programs. The comparison is based on information provided by the program developers in the following categories: general modeling features; zone loads; building envelope and daylighting and solar; infiltration, ventilation and multizone airflow; renewable energy systems; electrical systems and equipment; HVAC systems; HVAC equipment; environmental emissions; economic evaluation; climate data availability, results reporting; validation; and user interface, links to other programs, and availability.     

An enhanced linear regression-based building energy model (LRBEM+) for early design

The design community lacks simple, data-driven energy assessment tools to explore energy-efficient alternatives during the early stages of building design. A promising option is to utilize a whole building energy simulation engine (e.g. EnergyPlus) within a Monte Carlo simulation framework to develop a linear regression-based building energy model (LRBEM) that can predict idealized heating and cooling loads based on parameters relevant to early design. Previous work was limited to medium-sized US commercial office buildings with rectangular geometries. A key limitation is addressed in this paper by considering complex geometries. A reformulated model, LRBEM+, is developed and tested with a suite of building geometries that represent limiting cases. The resultant relative error between LRBEM+ and EnergyPlus is generally less than 10%. Furthermore, LRBEM+ correctly predicts the direction and magnitude of changes in heating and cooling loads in response to changes in the most influential early design parameters.     

A rapid calibration procedure and case study for simplified simulation models of commonly used HVAC systems

A rapid procedure for calibrating simplified building energy simulation models of commonly used HVAC systems has been developed. The procedure developed will allow building professionals to project annual cooling and heating energy consumption of buildings with multiple HVAC systems from short-term field measurement data. This paper describes the general calibration procedure developed, and demonstrates the use of the calibration procedure by applying it to an office building. The calibration methodology requires as little as two weeks of measured hourly heating and cooling consumption data. In the example presented, the simulation model was calibrated using only two weeks of measured heating and cooling data. After calibrating the simulation using this procedure, the RMSE is reduced significantly. The simulation calibrated to two weeks of measured data is then used to simulate the hourly consumption of the building for the year 2004. Comparison of the results of this simulation with the measured data gave monthly CV(RMSE) values of 10.3% and 3.7% for cooling and heating, respectively, which are both well below the 15% values considered acceptable in ASHRAE Guideline 14 [1]. It also shows monthly NMBE values of 2.2% and 1.4% for cooling and heating respectively.     

探究夏热冬冷地区办公建筑面积对单位建筑面积能耗(EUI)的影响

以上海地区的气象参数作为夏热冬冷气候区的典型代表,提出"H/S——建筑形状系数"并作为建筑形状分类指标,对办公建筑分类建模,采用能耗模拟软件e QUEST进行能耗估算,并用SPSS软件做逐步线性回归分析,探究建筑总面积、建筑形态与单位建筑面积年能耗(EUI)之间的数学关系。研究表明:1单位建筑面积能耗(EUI)随建筑总面积的增加而减少。2总面积越小的单体建筑,面积变化对能耗影响越大。3越"瘦高"的建筑,建筑能耗越大。     

Energy simulation in the variable refrigerant flow air-conditioning system under cooling conditions

As a high-efficiency air-conditioning scheme, the variable refrigerant flow (VRF) air-conditioning system is finding its way in office buildings. However, there is no well-known energy simulation software available so far which can be used for the energy analysis of VRF. Based on the generic dynamic building energy simulation environment, EnergyPlus, a new VRF module is developed and the energy usage of the VRF system is investigated. This paper compares the energy consumption of the VRF system with that of two conventional air-conditioning systems, namely, variable air volume (VAV) system as well as fan-coil plus fresh air (FPFA) system. A generic office building is used to accommodate the different types of heating, ventilating, and air-conditioning (HVAC) systems. The work focuses on the energy consumption of the VRF system in the office buildings and helps the designer's evaluation and decision-making on the HVAC systems in the early stages of building design. Simulation results show that the energy-saving potentials of the VRF system are expected to achieve 22.2% and 11.7%, compared with the VAV system and the FPFA system, respectively. Energy-usage breakdown for the end-users in various systems is also presented.     

Evaluation of simplified models for predicting CO2 concentrations in small commercial buildings

Evaluation of a building for application of demand-controlled ventilation (DCV) typically involves the use of computer simulations to predict energy use/costs for both fixed ventilation and ventilation adjusted to maintain fixed CO₂ levels within the space. The simulation tools incorporate models for predicting CO₂ concentrations in response to internal sources (people), infiltration/exfiltration, and ventilation. This paper presents a detailed evaluation of different modeling approaches for predicting levels of CO₂ in occupied spaces for small, single-zone commercial buildings employing packaged air-conditioning equipment. Two-zone and three-zone transient models were compared with a quasi-static equilibrium model applied to three distinctly different building types. Baseline data were derived from computational fluid dynamic models that were developed for field sites. A complete building system simulation model was then used to compare the impact of the different modeling approaches on the predicted energy cost savings associated with application of DCV in each building type. The use of a transient CO₂ model did not have a significant impact on model prediction accuracy and energy cost savings predictions as compared with the quasi-static model. The difference in predicted annual energy costs between the various CO₂ modeling types were small and less than might result from errors introduced by factors such as CO₂ sensor uncertainty. Therefore, the use of an equilibrium model is sufficient for use in evaluating DCV for small commercial buildings.     

Nationwide buildings energy research enabled through an integrated data intensive

Modern workflow systems can enable scientists to run ensemble simulations at unprecedented scales and levels of complexity, allowing them to study system sizes previously impossible to achieve. However as a result of these new capabilities the science teams suddenly also face unprecedented data volumes that they are unable to analyze with their existing tools and methodologies in a timely fashion. In this paper we describe the ongoing development work to create an integrated data intensive scientific workflow and analysis environment that offers researchers the ability to easily create and execute complex simulation studies and provides them with different scalable methods to analyze the resulting data volumes. The capabilities of the new environment are demonstrated on a use case that focuses on building energy modeling. As part of the PNNL research initiative PRIMA (Platform for Regional Integrated Modeling and Analysis) the team performed an initial 3-year study of building energy demands for the US Eastern Interconnect domain. They are now planning to extend to predict the demand for the complete century. In the 3-year study the team simulated 2000 individual building types for 100 independent climate similar regions (600 000 individual runs) raising their data demands from a few MBs to 400 GB for the 3-year study.     

Calibration and validation of a solar thermal system model in Modelica

Recent advancements in the domain of modeling physical processes offer opportunities to use equation based modeling environments, such as Modelica, for the simulation of building heating, ventilation, and air-conditioning (HVAC) systems. The current work demonstrates Modelica capabilities in a case study of real building solar thermal system simulation. The simulated system is part of an innovative ENERGYbase building, designed according to the so called Passivhaus standard. Model calibration and validation procedure is developed to include optimization based parametric adjustments of component models using the monitoring data during a single week. The calibrated system adequately reproduces half a year of real system operation. Future work will concentrate on application of the developed calibration and validation methodology in the whole year overall building energy simulation.