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At least 19 records

Simulating energy performance of buildings: a study using eQUEST and Energy Star ® portfolio manager

Commercial buildings consume significant energy in the United States and exhibit high potential for energy use reduction through retrofits. Benchmarking and energy simulation are well established tools in the industry to identify potential improvements and measure performance. Analysis to identify most sensitive retrofit parameters to energy performance can optimize investment and available energy savings. Presented study demonstrates methodology using a static model to determine sensitivity of building design and retrofit parameters with respect to energy performance. Calibrated simulation energy models (eQUEST) of two distribution centers (A, B) are presented. A fractional factorial analysis is conducted on retrofit parameters of efficiency measures targeting the highest energy consumers, and the results are benchmarked using Energy Star® Portfolio Manager. A custom Microsoft Excel® based simulation model is created to simulate occupancy levels, lighting, plug loads, and other equipment used in various spaces throughout the day. For Building A, efficient lighting was the most influential parameter for energy savings, carbon savings and benchmarking score; whereas, for Building B, HVAC efficiency was most influential for energy and demand controlled ventilation and economizers was most influential for benchmarking score. While retrofit projects can save energy and carbon emissions, variation in source-site ratios and state grid emissions, benchmarking scores may not always reflect equivalent improvement. State grid emissions factors, natural gas composition are difficult to model and hence not considered in this study. In conclusion, the synergistic analysis presented, emphasizes the importance of benchmarking and efficiency retrofits in promoting sustainable building practices to reduce energy consumption.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Latent heat thermal energy storage performance maps enabling fast & accurate building energy simulations

Thermal energy storage (TES) using phase change materials (PCMs) has gained attention as an effective approach to manage energy demand fluctuations and shift peak building loads. PCM embedded heat exchangers (PCM-HXs) offer high energy storage density and low temperature variation during phase change, being suitable for load-shifting applications. However, this component is typically evaluated using computationally expensive methods, which present significant challenges when the ultimate goal is to assess the performance of PCM-HX integrated thermal energy storage systems in the full building context. In this paper, we present a methodology to generate highly accurate and computationally efficient PCM-HX performance maps which can be easily integrated into building energy simulation tools to analyze the feasibility of space conditioning systems with latent heat PCM-based TES. The performance maps are generated using a computationally efficient PCM-HX simulation tool based on a Generalized Resistance-Capacitance Model (GRCM) which can simulate arbitrary PCM-HXs with high accuracy and significantly less computational effort compared to full CFD simulations. The methodology was verified for a case study considering a 5-ton (~17.5 kW) air-to-water heat pump-thermal energy storage system (HP-TES), which was co-simulated in Modelica for a DOE prototype small-office building in Vienna, Austria, using Spawn of EnergyPlus™. The TES performance maps provided accurate predictions of PCM-HX behavior when used as Modelica component, with deviations within 2-4% while also achieving at least 103 computational time reduction. Leveraging this faster prediction capability, four PCMs with different melting temperatures for cooling (12°C, 16°C) and heating (31°C, 36°C) were assessed to investigate their impact on system performance. This work highlights the importance of robust PCM-HX models for efficient and high-fidelity building-level simulations, presenting new opportunities for advanced control strategy development and parametric analysis of TES configurations in a computationally efficient manner

Modelica Building Simulations↗

Tensorized Interior Radiative Heat Transfer for a Scalable and Calibrated Building Energy Simulator

Building energy simulation is a critical tool for developing and testing advanced control strategies, such as Reinforcement Learning (RL), to provide demand flexibility and affordable energy costs. The recently introduced Smart Buildings Control Suite (sbsim) provides a lightweight, scalable, and data-calibrated simulation environment based on a 2D finite-difference model. However, the initial model primarily focused on conductive and convective heat transfer, neglecting the significant impact of long-wave radiative heat exchange between interior surfaces. This paper presents a significant extension to the sbsim framework by incorporating a physically-grounded model for interior radiative heat transfer. Our primary contribution is the development and integration of a fully tensorized radiative heat transfer module, which preserves the computational efficiency and scalability of the original simulator. This was achieved by developing a pipeline for view factor calculation, including an algorithm to identify directly seeing surfaces within complex floor plans, and formulating the net radiation equations for efficient execution on modern hardware accelerators. We validate the numerical accuracy of our tensorized implementation by comparing its results against a traditional iterative approach, demonstrating identical outcomes. This enhancement increases the physical fidelity of sbsim, enabling more accurate training of RL agents for building energy optimization.

Ham, Sang woo↗

Preparing an Incompressible-Flow Fluid Dynamics Code for Exascale-Class Wind Energy Simulations

The U.S. Department of Energy has identified exascale-class wind farm simulation as critical to wind energy scientific discovery. A primary objective of the ExaWind project is to build high-performance, predictive computational fluid dynamics (CFD) tools that satisfy these modeling needs. GPU accelerators will serve as the computational thoroughbreds of next-generation, exascale-class supercomputers. Here, we report on our efforts in preparing the ExaWind unstructured mesh solver, Nalu-Wind, for exascale-class machines. For computing at this scale, a simple port of the incompressible-flow algorithms to GPUs is insufficient. To achieve high performance, one needs novel algorithms that are application aware, memory efficient, and optimized for the latest-generation GPU devices. The result of our efforts are unstructured-mesh simulations of wind turbines that can effectively leverage thousands of GPUs. In particular, we demonstrate a first-of-its-kind, incompressible-flow simulation using Algebraic Multigrid solvers that strong scales to more than 4000 GPUs on the Summit supercomputer.

algebraic multigrid↗

Molecular Dynamics Free Energy Simulations Reveal the Mechanism for the Antiviral Resistance of the M66I HIV-1 Capsid Mutation

While drug resistance mutations can often be attributed to the loss of direct or solvent-mediated protein−ligand interactions in the drug-mutant complex, in this study we show that a resistance mutation for the picomolar HIV-1 capsid (CA)-targeting antiviral (GS-6207) is mainly due to the free energy cost of the drug-induced protein side chain reorganization in the mutant protein. Among several mutations, M66I causes the most suppression of the GS-6207 antiviral activity (up to ~84,000-fold), and only 83- and 68-fold reductions for PF74 and ZW-1261, respectively. To understand the molecular basis of this drug resistance, we conducted molecular dynamics free energy simulations to study the structures, energetics, and conformational free energy landscapes involved in the inhibitors binding at the interface of two CA monomers. To minimize the protein−ligand steric clash, the I66 side chain in the M66I−GS-6207 complex switches to a higher free energy conformation from the one adopted in the apo M66I. In contrast, the binding of GS-6207 to the wild-type CA does not lead to any significant M66 conformational change. Based on an analysis that decomposes the absolute binding free energy into contributions from two receptor conformational states, it appears that it is the free energy cost of side chain reorganization rather than the reduced protein−ligand interaction that is largely responsible for the drug resistance against GS-6207.

Sun, Qinfang (ORCID:0000000173621543)↗

Grey-box modeling and application for building energy simulations - A critical review

Grey-box modeling, as one of the three fundamental modeling techniques for building energy models, has many advantages compared with black-box modeling and white-box modeling. Additionally, it has been widely applied to solve problems of building technologies, such as building load estimation, control and optimization, and building-grid integration. However, a thorough review of grey-box modeling is not available. This review study systematically investigated various aspects of grey-box modeling for buildings. First, the fundamental aspects of grey-box modeling are presented, including the theoretical background, modeling of building elements, modeling order, modeling diagram, and order reduction. Second, the detailed modeling approaches are discussed. Third, multiple applications of grey-box modeling are investigated for building energy domain, which are categorized into the following groups: heat dynamics analysis, thermal load estimation, building control and optimization, district/urban scale energy modeling, and building-grid integration. Finally, the available software packages for grey-box modeling are compared. Overall, the challenges of using grey-box modeling can be summarized as follows: (1) the theoretical limitations and assumptions of grey-box modeling are unclear; (2) grey-box model naming convention and structure are confusing; (3) grey-box model creation is vague; (4) suitable applications of grey-box models are unknown; and (5) grey-box models lack unified software solutions for wider adoption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

CHARMM-GUI Free Energy Calculator for Absolute and Relative Ligand Solvation and Binding Free Energy Simulations

Alchemical free energy simulations have long been utilized to predict free energy changes for binding affinity and solubility of small molecules. However, while the theoretical foundation of these methods is well established, seamlessly handling many of the practical aspects regarding the preparation of the different thermodynamic end states of complex molecular systems and the numerous processing scripts often remains a burden for successful applications. Here, we present CHARMM-GUI Free Energy Calculator (http://www.charmm-gui.org/input/fec) that provides various alchemical free energy perturbation molecular dynamics (FEP/MD) systems with input and post-processing scripts for NAMD and GENESIS. Four submodules are available: Absolute Ligand Binder (for absolute ligand binding FEP/MD), Relative Ligand Binder (for relative ligand binding FEP/MD), Absolute Ligand Solvator (for absolute ligand solvation FEP/MD), and Relative Ligand Solvator (for relative ligand solvation FEP/MD). Each module is designed to build multiple systems of a set of selected ligands at once for high-throughput FEP/MD simulations. The capability of Free Energy Calculator is illustrated by absolute and relative solvation FEP/MD of a set of ligands and absolute and relative binding FEP/MD of a set of ligands for T4-lysozyme in solution and the adenosine A 2A receptor in a membrane. The calculated free energy values are overall consistent with the experimental and published free energy results (within ~1 kcal/mol). We hope that Free Energy Calculator is useful to carry out high-throughput FEP/MD simulations in the field of biomolecular sciences and drug discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Prototype Courthouse Building Energy Model: Building Characteristics and Energy Simulation Results

To coordinate commercial building energy research activities, the US Department of Energy uses a suite of commercial prototype building models, which includes 16 building types and covers 80% of US commercial floorspace. Efforts are underway to expand this suite by developing prototype models for additional building types, including a courthouse. Informed by building design guides, databases, documented projects, and personal communication with courthouse design experts, a 3-story, 4-courtroom, 69,324 ft 2 building was considered as the prototype courthouse to represent an average-sized courthouse in the United States. This report documents the building and system characteristics of the prototype courthouse model combined with climate-specific and construction vintage–specific requirements for the building envelope and systems from ASHRAE Standard 90.1. The energy simulation results are presented for 4 construction vintages (2004, 2007, 2010, and 2013) and 15 ASHRAE climate zones. To verify the energy simulation results, energy use statistics of existing courthouses from different building database are also presented. Based on the simulated energy use, the site energy use intensity of the prototype courthouse ranged from 45 to 159 kBtu/ft 2 compared with the average energy use intensity of 94.7 kBtu/ft 2 for the courthouse building type in the 2012 Commercial Building Energy Consumption Survey (CBECS) Data.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Rooftop unit comparison calculator: a framework for comparing performance of rooftop units with building energy simulation

The applications of building energy simulation (BES) in designing heating, ventilation, and air conditioning (HVAC) systems are limited by the high costs of developing simulation models and the lack of references for determining the model parameters. This paper presents a software framework for selecting designs for rooftop unit HVAC (RTU) systems with BES. Specifically, this framework reduces the cost of using BES by automating the generation of EnergyPlus models. It also employs a systematic method for determining model parameters based on well-accepted datasets. We applied this framework in a comprehensive assessment of an advanced design of RTU systems in which 478 EnergyPlus models were developed without human involvement. The assessment reveals that replacing a constant-speed fan/coil with a multiple-speed fan/coil may not guarantee better overall performance. In conclusion, it also suggests the benefits of replacing furnace coils with heat pumps are subject to utility cost, weather conditions, and heating load profiles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Model America - 2022 Arizona Building Energy Simulation Results from ORNL's AutoBEM

This dataset contains energy simulation outputs using ORNL's AutoBEM, covering the summer months (June 1st to August 31st) (named by "county_name.csv") and full-year periods (in output_all_year.zip) for each county in Arizona, USA. The data package includes simulation results such as basic energy metrics and anthropogenic emissions estimates. Files are provided in .csv. These data were generated to analyze the impact of weather conditions on energy use and emissions across urban and rural environments in Arizona, aiming to support research on urban heat islands, energy efficiency, and building retrofitting strategies. The source data for this work include NASA POWER weather datasets and computational models run using AutoBEM (i.e., an automated, large-scale energy simulation tool leveraging OpenStudio/EnergyPlus). This dataset can assist researchers, urban planners, and policymakers in developing climate-resilient energy systems and understanding anthropogenic contributions to local environments.

54 ENVIRONMENTAL SCIENCES↗

Prototype College Building Energy Model: Building Characteristics and Energy Simulation Results

The US Department of Energy supports the development of commercial building energy codes and standards. To support commercial building energy research activities and the development of commercial building energy codes and standards, continuous efforts have been made to convert 16 prototype building models, which cover 80% of US commercial building floor space, to OpenStudio prototype buildings. Additionally, the suite of prototype building models was expanded to include the addition of new building prototype models (e.g., courthouse, college building). Multiple sources, including databases, documented projects, and personal communications, were used to define the prototype college building, and a 4-story with 69,063 ft 2 building was considered as the prototype college building to represent an average-sized college building in the United States. To represent realistic occupancy schedules and increase the granularity of information, actual class reservation schedules were collected and used. This report documents the building and system characteristics of the prototype college building model combined with climate-specific and construction vintage–specific requirements for the building envelope and systems from ASHRAE Standard 90.1. The energy simulation results are presented for 4 construction vintages (2004, 2007, 2010, and 2013) and 15 ASHRAE climate zones. The site energy use intensity of the college building was compared with 2012 Commercial Building Energy Consumption Survey (CBECS) and ENERGY STAR data to verify the simulation results. The site energy use intensity of the college building ranged from 60 to 202.4 kBtu/ft 2 , and compared with the energy use intensities of Commercial Building Energy Consumption Survey (122.9 kBtu/ft 2 ) and ENERGY STAR (84.3 kBtu/ft 2 ) data, the prototype college building results are in a reasonable range.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Development of window scheduler algorithm exploiting natural ventilation and thermal mass for building energy simulation and smart home controls

Building energy simulations often rely on abstract assumptions when it comes to natural ventilation, such as ‘windows always open [or closed]’ or ‘windows open when outdoor temperature is below a certain threshold.’ However, simulations based on these assumptions fail to fully exploit the cooling potential of natural ventilation, as its effectiveness can be enhanced or diminished by various factors, including the presence of thermal mass. This issue also extends to smart home controls, where determining the window schedule becomes challenging without information about the building's response to outdoor conditions. To address these issues, this study has developed an analytical model for window operation schedules that leverages the passive cooling from natural ventilation. The analytical model was validated against a Modelica simulation. A case study utilizing the BESTEST model of ANSI/ASHRAE Standard 140 underwent validation with EnergyPlus simulations, showing strong concordance. The algorithm provides window schedule recommendations adapted to various airflow rates, thermal masses, and climate variations. Notably, the case study demonstrated that proper window scheduling could reduce indoor temperature by up to 8 °C under the given simulation settings, thereby improving resilience and indicating potential energy savings. Furthermore, the paper explores the potential opportunities and challenges this approach presents, especially for building simulation and smart home applications.

42 ENGINEERING↗

Prototype-Wise Sensitivity Analysis of Urban Building Energy Simulation Surrogate Modeling Accuracy

Urban Building Energy Modeling (UBEM) is an important reference for urban energy-related policymaking. Because of the significant impact of urban microclimates on the energy simulation, UBEM requires simulations of many microclimate-prototype pairs. Surrogate modeling is commonly used to reduce the cost of simulation computations. In UBEM surrogate modeling, it is important to determine the percentage of microclimates related to a prototype used for generating surrogate model training data. This study analyzes the prototype-wise variations and sensitivities of surrogate model estimation accuracy to the microclimate sampling ratios. The results of the study can help determine the number of simulations used for generating surrogate modeling data, avoid redundant simulations, and reduce the computational cost for UBEM surrogate modeling and its time.

Pan, Xiyu↗

Studying the Collective Functional Response of a Receptor in Alchemical Ligand Binding Free Energy Simulations with Accelerated Solvation Layer Dynamics

Ligand binding free energy simulations (LB-FES) that involve sampling of protein functional conformations have been longstanding challenges in research on molecular recognition. Particularly, modeling of the conformational transition pathway and design of the heuristic biasing mechanism are severe bottlenecks for the existing enhanced configurational sampling (ECS) methods. Inspired by the key role of hydration in regulating conformational dynamics of macromolecules, this report proposes a novel ECS approach that facilitates binding-associated structural dynamics by accelerated hydration transitions in combination with the lambda-exchange of free energy perturbation (FEP). Further, two challenging protein-ligand binding processes involving large configurational transitions of the receptor are studied, with hydration transitions at binding sites accelerated by Hamiltonian-simulated annealing of the hydration layer. Without the need for pathway analysis or ad hoc barrier flattening potential, LB-FES were performed with FEP/lambda-exchange molecular dynamics simulation at a minor overhead for annealing of the hydration layer. The LB-FES studies showed that the accelerated rehydration significantly enhances the collective conformational transitions of the receptor, and convergence of binding affinity calculations is obtained at a sweet-spot simulation time scale. Alchemical LB-FES with the proposed ECS strategy is free from the effort of trial and error for the setup and realizes efficient on-the-fly sampling for the collective functional response of the receptor and bound water and therefore presents a practical approach to high-throughput screening in drug discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

BESTEST-GSR (Building Energy Simulation Test - Generation Simulation and Reporting) 2023 [SWR 18-23]

Building Energy Simulation Test (BESTEST) is an NREL-developed method to validate the qualitative performance of different whole building simulations engines relative to each other. https://www.nrel.gov/docs/legosti/old/6231.pdf The purpose of this repository is to generate BESTEST test case models, run simulations, and populate data for ASHRAE Standard 140 reporting spreadsheets for EnergyPlus® based whole building simulation tools. It was originally setup for 2014 version of Standard 140. In May of 2022 it was updated to the 2020 version of Standard 140. This update included updates and additions to existing test suites, the bulk of which was in Section 5.2 (Building Thermal Envelope and Fabric Load Tests). We did not add Section 5.5 Airside HVAC Equipment Performance, but we hope to add that later in 2022. At some point we also hope to add Section 5.2.4 ground modeling, which is currently excluded. Supported Tools The default IDF generation is based on the OpenStudio® CLI, but the workflow supports a 'Bring your own IDF' use case. Additionally, for non-EnergyPlus® based tools the post processing scripts can be used if simulation results are provided as a CSV file.The scripts on this repository should work on Mac, Windows, and Linux. Dependencies Install OpenStudio® 3.4.0 make sure command line can recognize the 'openstudio' command This includes EnergyPlus® 22.1 Install Ruby on your system if it isn't already setup. 2.7 is used for development but other versions may work Since OpenStudio has its own embedded Ruby, which is used for running measures, you don't necessarily have to use a version of Ruby supported by OpenStudio. Install RubyXL Ruby gem This is used to modify Microsoft Excel spreadsheets Install Parallel Ruby gem This allows the CLI to run simulations in parallel

Goldwasser, David↗

Offshore Wind ENergy Simulation Toolkit (OWENS)

SAND2021-2751 O The Offshore Wind ENergy Simulation Toolkit (OWENS) is a collection of aerodynamic, structural, hydrodynamic, drivetrain, controls, composite structure and mesh preprocessing, and data postprocessing. OWENS is primarily an ontology, or glue code, pulling together many open-source and Sandia-developed libraries to model the aero-servo-hydro-elastic physics of wind and marine energy turbines. The toolkit’s intended use is for arbitrary aeroelastic rotor configurations analysis including vertical-axis wind turbines, horizontal-axis wind turbines, and analogous marine energy applications for fixed-bottom and floating configurations. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525

Owens, Brian↗

An Enhanced Vertical Ground Heat Exchanger Model for Whole-Building Energy Simulation

This paper presents an enhanced vertical ground heat exchanger (GHE) model for whole-building energy simulation (WBES). WBES programs generally have computational constraints that affect the development and implementation of component simulation sub-models. WBES programs require models that execute quickly and efficiently due to how the programs are utilized by design engineers. WBES programs also require models to be formulated so their performance can be determined from boundary conditions set by upstream components and environmental conditions. The GHE model developed during this work utilizes an existing response factor model and extends its capabilities to accurately and robustly simulate at timesteps that are shorter than the GHE transit time. This was accomplished by developing a simplified dynamic borehole model and then exercising that model to generate exiting fluid temperature response factors. This approach blends numerical and analytical modeling methods. The existing response factor models are then extended to incorporate the exiting fluid temperature response factor to provide a better estimate of the GHE exiting fluid temperature at short simulation timesteps.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗