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This presentation summarizes the items discussed during the End-use Load Profiles for the U.S. Building Stock: Technical Advisory Group Meeting #6 on March 5, 2020.
This presentation summarizes the items discussed during the End-use Load Profiles for the U.S. Building Stock: Technical Advisory Group Meeting #7 on May 26–27, 2020.
This presentation summarizes the items discussed during the End-use Load Profiles for the U.S. Building Stock: Technical Advisory Group Meeting #8 on September 22, 2020.
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.
Overview and Intended Use Cases: These scenarios establish a range of futures for U.S. buildings sector energy use and CO2 emissions to 2050 using Scout (scout.energy.gov), a reproducible and granular model of U.S. building energy use, emissions, and consumer costs developed by the U.S. national labs for the U.S. Department of Energy's Building Technologies Office (BTO). Scout benchmark scenario data are suitable for the following example use cases: setting high-level policy goals for the U.S. buildings sector to 2050 (e.g., X% building CO2 emissions reductions vs. 2005 levels by 2030, Y% reductions vs. 2005 levels by 2050); exploring the effects of key dynamics driving U.S. buildings sector energy and CO2 emissions to 2050 that could be affected by policy levers (e.g., raising minimum technology performance levels; accelerating electrification and/or retrofit rates; introducing breakthrough technologies to the market); determining priority segments (regions, building types, and end use/technology types) and sequencing of U.S. buildings sector energy and CO2 emissions reductions to 2050 under a given set of assumptions; and/or identifying the energy and emissions impacts or cost effectiveness of specific technologies or operational approaches of interest—in isolation or after considering competition with other measures in a scenario portfolio. Scenario Summary: A total of 8 scenarios explore the effects of changes across both the demand- and supply-side of building energy use on annual U.S. building energy use and CO2 emissions from 2022–2050. Scenarios are organized into three groups representing low, moderate, and best-case potentials for building decarbonization, respectively.
This package replaces existing gas and electric resistance rooftop units (RTUs) with standard efficiency heat pump RTUs and improves roof insulation. The purpose is to couple heat pumps retrofits with an improved envelope to investigate the combined effect.
In the ResStock 2024.2 dataset, ResStock runs are used to create "what-if" scenarios including energy efficiency measures such as heat pumps, envelope improvements, and electrification of appliances. This dataset release includes 15 measure packages across two weather years and incorporates ResStock improvements in variable speed heat pump modeling, geothermal heat pump modeling, and housing characteristic data updates from RECS 2020.
The commercial building sector stock model, or ComStock™, is a highly granular, bottom-up model that uses multiple data sources, statistical sampling methods, and advanced building energy simulations to estimate the annual sub-hourly energy consumption of the commercial building stock across the United States. ComStock asks and answers two questions: how is energy used in the U.S. building stock and what are the impact of energy saving technologies. Specifically, ComStock identifies where energy is being consumed geographically, in what building types and end uses, and at what times of day. Simultaneously, it identifies the impact of efficiency measures: how much energy do efficiency measures save; where, or in what use cases do measures save energy; when, or at what time of day do savings occur; and which building stock segments have the biggest savings potential. This document contains the methodology and assumptions behind ComStock and serves as a guide to its use.
The residential building sector accounts for a substantial portion of total energy consumption in the United States and offers a significant opportunity for energy reduction and decarbonization through improvements in energy efficiency. Heating and air conditioning are the primary contributors to residential energy usage and electricity system peak demand. However, due to the diversity of the housing stock and the complexity of factors affecting heating and cooling demand, identifying the relative contributions to heating and cooling loads poses challenges. To address this, we applied the ResStock analysis tool to simulate 550,000 building energy models, providing statistical representation of residential buildings in the contiguous United States. We introduced outputs that quantified the heating and cooling influence of different components of a home, such as air leakage, envelope components (ceilings, walls, windows, foundations), internal heat gains from people, lighting, plug loads, and duct losses and gains. Leveraging the granularity of ResStock, we present a dataset to enable deeper understanding of the contributors to heating and cooling loads as a function of housing characteristics such as location, envelope efficiency, and building type. This work aims to support prioritization of research and development and informed decision-making for residential building decarbonization.
20% of the U.S. commercial building sector's energy usage is from on-site combustion of fossil fuels for heating. Decarbonization will require electrification of these systems to meet climate goals, often by transitioning to heat pumps. Rooftop units (RTU) are the most prominent commercial building HVAC system type and should therefore be prioritized for decarbonization solutions. However, there is limited understanding of the impact on emissions that considers regional electricity generation methods, as well as the impact of other heat pump intricacies such as the effects of temperature on capacity/efficiency, defrost operation, realistic sizing methodologies, and supplementary heating. This study explores the effects of transitioning all conventional RTUs to high-performance heat pump RTUs for the U.S. commercial building stock. The analysis is performed using ComStock, DOE's calibrated model of the U.S. commercial building stock developed by NREL. Results show 9% and 17% reductions in stock aggregate energy consumption and GHG emissions, respectively. Furthermore, average heat pump operational details are presented by state. This analysis will help inform the transition to heat pump RTUs for the U.S. commercial building stock.
Recent advancements in data science and high-performance computing are making it easier to run millions of building simulations, but meaningful visualization of such large datasets remains a challenge. This paper presents a new tool developed to view the results of large-scale OpenStudio simulations of national, regional, or local building stocks. The tool processes millions of simulations to calculate measure savings, utility bills, carbon emissions, primary energy, and cost-effectiveness metrics at a high geographic resolution. Interactive visualizations of the building characteristics, consumption, and measure savings data include proportional symbol maps and histogram plots and can be filtered by any building characteristic.
ComStock™ is an NREL model of the U.S. commercial building stock. The model takes some building characteristics from the U.S. Department of Energy's (DOE's) Commercial Prototype Building Models and Commercial Reference Building. However, unlike many other building stock models, ComStock also combines these with a variety of additional public- and private-sector data sets. Collectively, this information provides high-fidelity building stock representation with a realistic diversity of building characteristics. This repository contains the source code used to build and execute ComStock models, including upgrade scenarios. In addition, the sampling of buildings characteristics used for the initial ComStock (V1.0) release is provided. The ComStock model is under active calibration and development, which is publicly visible on this repository. Execution of the ComStock workflow is managed through the buildstockbatch repository, a shared asset of ResStock™ and ComStock™ , specifically developed to scale to execution of tens of millions of simulations through multiple infrastructure providers. The dataset output from the initial ComStock (V1.0) release can be found at the accompanying ComStock data viewer website and additional information about ComStock found on the NREL Buildings Website. For more details about ongoing model development please consult the End Use Load Profiles website. ComStock is a direct result of the NREL residential stock modeling tool ResStock™ (recipient of a R&D100 award) and was inspired by the high-fidelity solar & storage adoption model dGen™. Additionally, this tool would not be possible without the decades of work undertaken by the OpenStudio® and EnergyPlus® visionaries and contributors, significant funding, feedback and support from the Los Angeles Department of Water and Power, and the Department of Energy's Building Technology Office ongoing support of and investment in building energy modeling software. is an analytic methodology for modeling the energy usage of the commercial building stock within the United States of America. The commercial building stock is represented through a sampling of complex probabilistic distributions of various features of interest for modeling energy usage within commercial buildings. Each sample from these distributions is converted into a building energy model based on the features of that specific sample. Each building energy model can be simulated as is, but additional changes can be made to the model through addition of energy conservation measures, component faults, or other desired alterations. The results of the simulations are then processed to provide insights for various stakeholders, including but not limited to policy makers, engineers, and marketers.
This study provides hypothetical thermal heating and cooling loads for ComStock models representing the U.S. commercial building stock. This measure scenario removes all HVAC models from the baseline ComStock building model and instead uses "ideal air" to meet loads. "Ideal air" can be thought of as an HVAC unit that mixes air at the zone exhaust condition with the specified amount of outdoor air, and then adds or removes heat and moisture at 100% efficiency to produce a supply air stream at the specified conditions. The resulting ideal thermal loads are represented under the "district" fuel type for both heating and cooling and can be found in both annual and timeseries results in the ComStock public dataset. This measure scenario does not represent any real technology or improvement, but rather, serves as a resource for thermal heating and cooling loads for buildings.
This report is part of a series describing different ResStock (TM) measures. "Measures" refers to energy efficiency retrofits that can be applied to buildings during modeling. This documentation covers the "Electric Vehicle Adoption With Level 1 Charging" measure upgrade methodology and briefly discusses key results.
This report is part of a series describing different ResStock (TM) measures. "Measures" refers to energy efficiency retrofits that can be applied to buildings during modeling. This documentation covers the "Electric Vehicle Adoption With Level 2 Charging" measure upgrade methodology and briefly discusses key results.
This report is part of a series describing different ResStock measures. "Measures" refers to energy efficiency retrofits that can be applied to buildings during modeling. This documentation covers the "Electric Vehicle Adoption With Level 2 Charging and Demand Flexibility" measure upgrade methodology and briefly discusses key results.
This report is part of a series describing different ResStock measures. "Measures" refers to energy efficiency retrofits that can be applied to buildings during modeling. This documentation covers the "Efficient Electric Vehicle Adoption With Level 2 Charging and Demand Flexibility" measure upgrade methodology and briefly discusses key results.
This report is part of a series describing different ResStock (TM) measures. "Measures" refers to energy efficiency retrofits that can be applied to buildings during modeling. This documentation covers the "Efficient Electric Vehicle Adoption With Level 2 Charging" measure upgrade methodology and briefly discusses key results.