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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

A SIMPLIFIED ENERGY MODELING APPROACH FOR BUILDINGS

This paper introduces simplified energy modeling (SEM) approaches using DOE2 and EnergyPlus and proposes a validation method for simplified energy modeling. Simplified energy modeling can allow more design teams and owners to leverage the power of energy modeling to inform their designs and lead to greater energy savings and a lower first cost because the technologies and design strategies can be thoroughly tested against models before the decisions are made. By starting a discussion on how to develop simplified energy modeling approaches and methods to validate results, we hope to increase innovation in energy modeling software while decreasing variation between modelers. Simplified modeling is not yet widely accepted because it is unclear if the simplifications reduce the accuracy of the results. By starting an industry dialogue on a testing method for these modeling approaches, we hope to aid adoption of more streamlined tools when they can be shown to provide similar accuracy to more detailed tools. This paper proposes a method to test simplified energy modeling programs against the DOE prototype buildings. It builds on the testing procedure established for simulation engines by ASHRAE Standard 140. By comparing whole building and end use results from the accepted prototype buildings to any simplified modeling approach across multiple building types and climate zones we can determine if the simplifications create unwarranted error. We will present the SEM approach and results for a case study validation for a sample building types in 16 US climate zones from two such simplified energy modeling tools.

Energy Modeling, 90.1 Appendix G, Asset Score Tool↗
DOE OSTI2026

OpenStudio®-MCP [SWR-26-035]

OpenStudio®-MCP is a Model Context Protocol (MCP) server that lets AI assistants perform building energy modeling through natural language. Rather than requiring users to learn the OpenStudio® SDK, EnergyPlus® scripting, or Ruby/Python automation, the server translates conversational requests into sequences of tool calls that create models, design HVAC systems, run simulations, and extract results — all within a single chat session. The server's 124 tools are organized into a skills architecture where each skill encapsulates a domain of building energy modeling (envelope, HVAC, loads, weather, simulation, results) behind typed, LLM-friendly interfaces. High-leverage operations like applying ASHRAE 90.1 baseline systems or generating standards-compliant typical buildings are exposed as single tool calls that internally wire dozens of OpenStudio® objects. Bundled measures from ComStock™ and Openstudio® -common-measures-gem are wrapped with dedicated tools and typed arguments rather than exposed through a generic measure interface, so AI models get consistent, error-resistant recipes without needing to discover measure arguments at runtime. A key design decision is structured results extraction: six SQL-based tools return surgical ~300–1,000 token responses (end-use breakdowns, envelope summaries, HVAC sizing, timeseries data) instead of requiring the AI to parse ~100K-token raw HTML reports, making iterative design exploration practical within context window limits. The codebase is designed as a reference implementation — explicit, well-commented, and modular — so that other simulation engines (EnergyPlus® standalone, TRNSYS, DOE-2) can use it as a template for building their own MCP servers.

Ball, Brian [National Laboratory of the Rockies (N↗
DOE OSTI2017

Evaluation of energy savings potential of variable refrigerant flow (VRF) from variable air volume (VAV) in the U.S. climate locations

Variable refrigerant flow (VRF) systems are known for their high energy performance and thus can improve energy efficiency both in residential and commercial buildings. The energy savings potential of this system has been demonstrated in several studies by comparing the system performance with conventional HVAC systems such as rooftop variable air volume systems (RTU-VAV) and central chiller and boiler systems. This paper evaluates the performance of VRF and RTU-VAV systems in a simulation environment using widely-accepted whole building energy modeling software, EnergyPlus. A medium office prototype building model, developed by the U.S. Department of Energy (DOE), is used to assess the performance of VRF and RTU-VAV systems. Each system is placed in 16 different locations, representing all U.S. climate zones, to evaluate the performance variations. Both models are compliant with the minimum energy code requirements prescribed in ASHRAE standard 90.1-2010 — energy standard for buildings except low-rise residential buildings. Finally, a comparison study between the simulation results of VRF and RTU-VAV models is made to demonstrate energy savings potential of VRF systems. The simulation results show that the VRF systems would save around 15–42% and 18–33% for HVAC site and source energy uses compared to the RTU-VAV systems. In addition, calculated results for annual HVAC cost savings point out that hot and mild climates show higher percentage cost savings for the VRF systems than cold climates mainly due to the differences in electricity and gas use for heating sources.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Urban-Scale Energy Modeling, Part 8

Development of urban-scale building energy models is becoming increasingly tractable for many applications including city-wide energy supply/demand strategies, urban development planning,electrical grid stability, and urban resilience. This seminar has assembled researchers from MIT and Lawrence Berkeley National Laboratory with capabilities in the field of urban-scale energy models to discuss an overview of the field as well as the data, algorithms, workflow, and practical challenges addressed in their applications involving creation of useful models of individual and tall buildings at the scale of a city, urban, or metropolitan area.

Nagpal, Shreshth↗
DOE OSTI2024

Assessing the Impact of Variable Air Volume Box Damper Stuck Faults Using a Building Automation System and Building Energy Simulation Model

The study examines the impact of variable air volume (VAV) damper stuck faults on the system operation, building indoor conditions, and reheating energy consumption. This study includes both experimental and simulation studies for five test scenarios, including a fault-free scenario. We implemented VAV damper stuck fault through the building automation system (BAS). Results show that a damper stuck in a high opening position (60% damper opening) results in supplying an excessive amount of cold air from the rooftop unit (RTU) to the conditioned zone, increasing reheating energy consumption. The results of this research can serve as a foundational resource for developing fault detection algorithms.

Jung, Sungkyun↗
DOE OSTI2021

Characterizing patterns and variability of building electric load profiles in time and frequency domains

The rapid development of advanced metering infrastructure provides a new data source—building electrical load profiles with high temporal resolution. Electric load profile characterization can generate useful information to enhance building energy modeling and provide metrics to represent patterns and variability of load profiles. Such characterizations can be used to identify changes to building electricity demand due to operations or faulty equipment and controls. In this study, we proposed a two-path approach to analyze high temporal resolution building electrical load profiles: (1) time-domain analysis and (2) frequency-domain analysis. Furthermore, the commonly adopted time-domain analysis can extract and quantify the distribution of key parameters characterizing load shape such as peak-base load ratio and morning rise time, while a frequency-domain analysis can identify major periodic fluctuations and quantify load variability. We implemented and evaluated both paths using whole-year 15-minute interval smart meter data of 188 commercial office building in Northern California. The results from these two paths are consistent with each other and complementary to represent full dynamics of load profiles. The time- and frequency-domain analyses can be used to enhance building energy modeling by: (1) providing more realistic assumptions about building operation schedules, and (2) validating the simulated electric load profiles using the developed variability metrics against the real building load data.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

ComStock/COVID-19: U.S. Commercial Building Stock Analysis of COVID-19 Mitigation Strategies

ComStock is a DOE platform, with NREL as the lead developer, that models the U.S. commercial building stock using OpenStudio/EnergyPlus to perform physics-based building energy modeling simulations. The ASHRAE Epidemic Taskforce (ASHRAE-ETF) has released several COVID-19 mitigation strategies for commercial buildings. ComStock was used to analyze the impact of four strategies on the existing commercial building stock. These strategies are upgrading to MERV-13 filters, disabling demand control ventilation (DCV), increasing minimum outdoor air to 100%, and HVAC flushing mode operation. Results show the impact of each measure on energy consumption, electric consumption, gas consumption and peak electric.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2018

Final Energy Savings Analysis of the Proposed NYStretch-Energy Code 2018

This study was conducted by the Pacific Northwest National Laboratory (PNNL) in support of the stretch energy code development led by the New York State Energy Research and Development Authority (NYSERDA). In 2017 NYSERDA developed its 2016 Stretch Code Supplement to the 2016 New York State Energy Conservation Construction Code (hereinafter referred to as “NYStretch-Energy”). NYStretch-Energy is intended as a model energy code for statewide voluntary adoption that anticipates other code advancements culminating in the goal of a statewide Net Zero Energy Code by 2028. Since then, NYSERDA continues to develop the NYStretch-Energy Code 2018 edition (NYSERDA 2018). To support the effort, PNNL conducted energy simulation analysis to quantify the energy savings of proposed commercial provisions of the NYStretch-Energy Code 2018 in New York. The focus of this project is to significantly improve the energy efficiency over existing commercial model energy codes. A key requirement of the proposed stretch code is that it be ‘adoptable’ as an energy code, meaning that it must align with current code scope and limitations, and primarily impact building components that are currently regulated by local building departments. It is largely limited to prescriptive measures, which are what most building departments and design projects are most familiar with. This report describes a set of energy-efficiency measures (EEMs) that demonstrate significant energy savings over ANSI/ASHRAE/IES Standard 90.1-2013 (ASHRAE 2013) across a broad range of commercial building types and all three climate zones in New York. In collaboration with New Building Institute, the EEMs were developed from national model codes and standards, high-performance building codes and standards, regional energy codes, and measures being proposed as part of the on-going code development process. PNNL analyzed these measures using whole building energy models for selected prototype commercial buildings and multifamily buildings representing buildings in New York.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Energy Savings Analysis of the Proposed NYStretch-Energy Code 2018

This study was conducted by the Pacific Northwest National Laboratory (PNNL) in support of the stretch energy code development led by the New York State Energy Research and Development Authority (NYSERDA). In 2017 NYSERDA developed its 2016 Stretch Code Supplement to the 2016 New York State Energy Conservation Construction Code (hereinafter referred to as “NYStretch-Energy”). NYStretch-Energy is intended as a model energy code for statewide voluntary adoption that anticipates other code advancements culminating in the goal of a statewide Net Zero Energy Code by 2028. Since then, NYSERDA continues to develop the NYStretch-Energy Code 2018 edition. To support the effort, PNNL conducted energy simulation analysis to quantify the energy savings of proposed commercial provisions of the NYStretch-Energy Code (2018) in New York. The focus of this project is the 20% improvement over existing commercial model energy codes. A key requirement of the proposed stretch code is that it be ‘adoptable’ as an energy code, meaning that it must align with current code scope and limitations, and primarily impact building components that are currently regulated by local building departments. It is largely limited to prescriptive measures, which are what most building departments and design projects are most familiar with. This report describes a set of energy-efficiency measures (EEMs) that demonstrate 20% energy savings over ANSI/ASHRAE/IES Standard 90.1-2013 (ASHRAE 2013) across a broad range of commercial building types and all three climate zones in New York. In collaboration with New Building Institute, the EEMs were developed from national model codes and standards, high-performance building codes and standards, regional energy codes, and measures being proposed as part of the on-going code development process. PNNL analyzed these measures using whole building energy models for selected prototype commercial buildings and multifamily buildings representing buildings in New York. Section 2 of this report describes the analysis methodology, including the building types and construction area weights update for this analysis, the baseline, and the method to conduct the energy saving analysis. Section 3 provides detailed specifications of the EEMs and bundles. Section 4 summarizes the results of individual EEMs and EEM bundles by building type, energy end-use and climate zone. Appendix A documents detailed descriptions of the selected prototype buildings. Appendix B provides energy end-use breakdown results by building type for both the baseline code and stretch code in all climate zones.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

AirflowNetwork [SWR 19-45]

The AirflowNetwork software provides the ability to simulate air movement and the resulting transport of contaminants and other materials within a building. The performance of air distribution systems, including supply and return leaks, and multizone airflows driven by outdoor wind and forced air during HVAC system operation are simulated using a nodal network representation of the building. The pressure network model implemented here is based on George Walton's AIRNET and was modified for inclusion in the EnergyPlus building energy modeling software. The algorithm were then extracted from EnergyPlus into a stand-alone package to facility use without the building energy model and more extensive testing and validation of the underlying operations.

DeGraw, Jason↗
DOE OSTI2022

Individualized empirical baselines for evaluating the energy performance of existing buildings

The evaluation of building energy performance requires a baseline for comparison. Common empirical baselines are usually used for existing buildings since they are fast and convenient. However, the same type of building at the same location will receive the same baseline despite their difference in usage. Individualized baselines by creating building energy models are possible solutions, but it is labor intensive and time-consuming. To fill the gap, this study is to develop individualized empirical baselines for existing buildings in a fast way. First, common empirical baselines are created based on survey data. Then, to get training samples, building energy models for large-scale existing buildings are created and simulated. So finally, based on simulation results, mathematical models to get individualized empirical baselines in a fast way are created. U.S. medium office buildings were used as an example to demonstrate the method. We developed 30 mathematical models for medium office buildings in two vintages (constructed before 1980 and after 1980) and 15 climate zones. The mean absolute percentage errors (MAPE) between the individualized empirical baselines and the modeled baselines for those 30 mathematical models are all lower than 5.5%. An engineer can obtain the individualized empirical baseline for an existing building in a few seconds by using the open-source tool we developed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Methodology to assess “no-touch” building audit software using simulated utility data

Building audits are conducted in many commercial buildings to identify opportunities to reduce energy costs and improve building operation. Because audits require significant effort by building engineers, they are usually only affordable for larger commercial buildings. “No-touch” building audit tools have thus been developed to identify potential savings based on a simplified analysis of building energy consumption patterns via high-level energy data such as monthly utility bills. This paper presents a comprehensive and standardized methodology to evaluate the accuracy of no-touch audit tools in detecting and diagnosing building energy problems and quantifying potential energy savings. The test suite is based on output data from a well-characterized set of building energy models, and the methodology is illustrated by applying it to a representative no-touch building audit tool. Results show that the tool estimates building energy end uses with reasonable accuracy but is less accurate in identifying probably causes of high energy.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

Energy savings modelling of re-tuning energy conservation measures in large office buildings

Today, many large commercial buildings use sophisticated building automation systems (BASs) to manage a wide range of building equipment. While the capabilities of BASs have increased over time, many buildings still do not fully use the BAS’s capabilities and are not properly commissioned, operated or maintained, which leads to inefficient operation, increased energy use, and reduced lifetimes of the equipment. This paper investigates the energy savings potential of several common HVAC system re-tuning measures on a typical large office building, using the Department of Energy’s building energy modeling software, EnergyPlus. The baseline prototype model uses roughly as much energy as an average large office building in existing building stock, but does not utilize any re-tuning measures. Individual re-tuning measures simulated against this baseline include automatic schedule adjustments, damper minimum flow adjustments, thermostat adjustments, as well as dynamic resets (set points that change continuously with building and/or outdoor conditions) to static pressure, supply-air temperature, condenser water temperature, chilled and hot water temperature, and chilled and hot water differential pressure set points. Six combinations of these individual measures have been formulated – each designed to conform to limitations to implementation of certain individual measures that might exist in typical buildings. All the individual measures and combinations were simulated in 16 climate locations representative of specific U.S. climate zones. The modeling results suggest that the most effective energy savings measures are those that affect the demand-side of the building (air-systems and schedules). Many of the demand-side individual measures were capable of reducing annual total HVAC system energy consumption by over 20% in most cities that were modeled. Supply side measures affecting HVAC plant conditions were only modestly successful (less than 5% annual HVAC energy savings for most cities for all measures). Combining many of the re-tuning measures revealed deep savings potential. Some of the more aggressive combinations revealed 35-75% reductions in annual HVAC energy consumption, depending on climate and building vintage.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

A Method to Test Model Calibration Techniques: Preprint

This paper describes a method for testing model calibration techniques. Calibration is commonly used in conjunction with energy retrofit audit models. An audit is conducted to gather information about the building needed to assemble an input file for a building energy modeling tool. A calibration technique is used to reconcile model predictions with utility data, and then the 'calibrated model' is used to predict energy savings from a variety of retrofit measures and combinations thereof. Current standards and guidelines such as BPI-2400 and ASHRAE-14 set criteria for 'goodness of fit' and assume that if the criteria are met, then the calibration technique is acceptable. While it is logical to use the actual performance data of the building to tune the model, it is not certain that a good fit will result in a model that better predicts post-retrofit energy savings. Therefore, the basic idea here is that the simulation program (intended for use with the calibration technique) is used to generate surrogate utility bill data and retrofit energy savings data against which the calibration technique can be tested. This provides three figures of merit for testing a calibration technique, 1) accuracy of the post-retrofit energy savings prediction, 2) closure on the 'true' input parameter values, and 3) goodness of fit to the utility bill data. The paper will also discuss the pros and cons of using this synthetic surrogate data approach versus trying to use real data sets of actual buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

A Method to Test Model Calibration Techniques

This paper describes a method for testing model calibration techniques. Calibration is commonly used in conjunction with energy retrofit audit models. An audit is conducted to gather information about the building needed to assemble an input file for a building energy modeling tool. A calibration technique is used to reconcile model predictions with utility data, and then the 'calibrated model' is used to predict energy savings from a variety of retrofit measures and combinations thereof. Current standards and guidelines such as BPI-2400 and ASHRAE-14 set criteria for 'goodness of fit' and assume that if the criteria are met, then the calibration technique is acceptable. While it is logical to use the actual performance data of the building to tune the model, it is not certain that a good fit will result in a model that better predicts post-retrofit energy savings. Therefore, the basic idea here is that the simulation program (intended for use with the calibration technique) is used to generate surrogate utility bill data and retrofit energy savings data against which the calibration technique can be tested. This provides three figures of merit for testing a calibration technique, 1) accuracy of the post-retrofit energy savings prediction, 2) closure on the 'true' input parameter values, and 3) goodness of fit to the utility bill data. The paper will also discuss the pros and cons of using this synthetic surrogate data approach versus trying to use real data sets of actual buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Building Energy Analysis of Manufactured and Multifamily Housing Types in Juneau, Alaska

This report details the results of building energy modeling analysis evaluating the potential energy savings, economic outcomes, and grid-level electricity reduction associated with cold climate air source heat pump (ccASHP) adoption across multifamily and manufactured housing (MMFH) building typologies in the City and Borough of Juneau (CBJ). Three building archetypes were evaluated: multifamily 4-plex apartments, multifamily 8-plex apartments, and manufactured housing units. Building energy models were developed using OpenStudio-HPXML and calibrated to actual utility consumption data and local meteorological data from the Juneau International Airport weather station using an automated calibration tool following the BPI-2400-S-2015 v.2 standard for model calibration. Occupant behaviors present the greatest variability in successful calibrations. Calibrated models were benchmarked against a baseline electric resistance heating condition, with the selected ccASHP modeled as the retrofit condition and typical meteorological year weather data for all results generation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Urbanization-induced land and aerosol impacts on sea-breeze circulation and convective precipitation

Abstract. Changes in land cover and aerosols resulting from urbanization may impact convective clouds and precipitation. Here we investigate how Houston urbanization can modify sea-breeze-induced convective cloud and precipitation through the urban land effect and anthropogenic aerosol effect. The simulations are carried out with the Chemistry version of the Weather Research and Forecasting model (WRF-Chem), which is coupled with spectral-bin microphysics (SBM) and the multilayer urban model with a building energy model (BEM-BEP). We find that Houston urbanization (the joint effect of both urban land and anthropogenic aerosols) notably enhances storm intensity (by ∼ 75 % in maximum vertical velocity) and precipitation intensity (up to 45 %), with the anthropogenic aerosol effect more significant than the urban land effect. Urban land effect modifies convective evolution: speed up the transition from the warm cloud to mixed-phase cloud, thus initiating surface rain earlier but slowing down the convective cell dissipation, all of which result from urban heating-induced stronger sea-breeze circulation. The anthropogenic aerosol effect becomes evident after the cloud evolves into the mixed-phase cloud, accelerating the development of storm from the mixed-phase cloud to deep cloud by ∼ 40 min. Through aerosol–cloud interaction (ACI), aerosols boost convective intensity and precipitation mainly by activating numerous ultrafine particles at the mixed-phase and deep cloud stages. This work shows the importance of considering both the urban land and anthropogenic aerosol effects for understanding urbanization effects on convective clouds and precipitation.

54 ENVIRONMENTAL SCIENCES↗