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This report summarizes technical analysis conducted by Pacific Northwest National Laboratory (PNNL), assessing expected end-use energy consumption in commercial buildings, based on recent editions of the model energy code for the commercial sector, ANSI/ASHRAE/IES Standard 90.1, Energy Standard for Buildings Except Low-Rise Residential Buildings.
The Infrastructure Investment and Jobs Act (H.R. 3684, 2021) directed the Secretary of Energy to prepare a report identifying the existing codes and standards for energy storage technologies. The stated goals for the report are to enhance the safe development of energy storage systems by identifying codes that require updating and facilitation of greater conformity in codes across different types and usages of energy storage technologies. This paper will focus on the specific codes and standards for stationary energy storage systems (ESS).
This slide deck report identifies objectives and key indicators for state activities that advance demand flexibility in buildings — legislation, utility regulatory proceedings, executive orders and programs. It also illustrates progress to date and identifies trends, gaps, and opportunities. Part I of the report focuses on (1) demand response and (2) energy efficiency targeted to reduce peak demand or integrate with demand response. This section covers building energy codes, appliance and equipment standards, resource standards, utility planning, utility programs, advanced metering infrastructure and meter data, rate design, state programs, state energy planning, and related state policies and regulations. Part II of the report addresses traditional energy efficiency indicators, including utility and state programs, codes, and standards that support annual energy savings. See the additional links for an infographic, library of cited state documents on demand flexibility, and presentation to the NASEO-NARUC Grid-Interactive Efficient Buildings Working Group.
This report assesses energy savings and peak power reduction of three heat pumps in multiple US cold climate cities and building types. The three heat pumps comprise a baseline heat pump and two high efficiency cold climate heat pumps (CCHP). The DOE/ORNL Heat Pump Design Model was used to simulate the heat pumps and generate performance curves for EnergyPlus building energy simulations. The annual energy simulations were performed over seven cold climates: 1) Minneapolis, MN; 2) Duluth, MN; 3) Fairbanks, AK; 4) Helena, MT; 5) Indianapolis, IN; 6) Peoria, IL and 7) Eagle County, CO. In order to assess impact of residential building types matching different energy codes, we simulated six single-family houses in Indianapolis, IN, including : 1) single-family house having a crawlspace; 2) having a slab foundation; 3) having a heated basement; 4) having an unheated basement; 5) one single-family house having a heated basement matching IECC code of 2009, 6) and one single-family house having a heated basement matching IECC code of 2012. The former 4 houses match the IECC 2006 code.
The HFBTHO code implements a nuclear energy density functional solver to model the structure of atomic nuclei. HFBTHO has previously been used to calibrate energy functionals and perform sensitivity analysis by using derivative-free methods. To enable derivative-based optimization and uncertainty quantification approaches, we must compute the derivatives of HFBTHO outputs with respect to the parameters of the energy functional, which are a subset of all input parameters of the code. Here, we use the algorithmic/automatic differentiation (AD) tool Tapenade to differentiate HFBTHO. We compare the derivatives obtained using AD against finite-difference approximation and examine the performance of the derivative computation.
Municipal governments in the United States are well positioned to influence clean energy (energy efficiency and alternative energy) and transportation technology and strategy implementation within their jurisdictions through planning, programs, and codification. Municipal governments are leveraging planning processes and programs to shape their energy futures. There is limited understanding in the literature related to codification, the primary way that municipal governments enact enforceable policies. The authors fill the gap in the literature by documenting the status of municipal codification of clean energy and transportation across the United States. More directly, we leverage online databases of municipal codes to develop national and state-specific representative samples of municipal governments by population size. Our analysis finds that municipal governments with the authority to set residential building energy codes within their jurisdictions frequently do so. In some cases, communities set codes higher than their respective state governments. Examination of codes across the nation indicates that municipal governments are employing their code as a policy mechanism to address clean energy and transportation.
The aim of the project reported here was to better understand the level of accuracy of three building energy simulation (BES) engines (‘engines’) — EnergyPlus™, DOE-2.1e, and DOE-2.2 — by identifying and investigating significant deviations between the performance predicted by these engines and actual performance as measured in the FLEXLAB® test facility at Lawrence Berkeley National Laboratory (LBNL). The specific test conditions included some of those prescribed in ANSI/ASHRAE Standard 140 - Standard Method of Test for the Evaluation of Building Energy Analysis Computer Programs. Detailed measurements of FLEXLAB performance, including indoor temperatures and heat fluxes and air-flow and water flow rates and temperatures in the Heating, Ventilating and Air Conditioning (HVAC) system, together with hourly weather data, were recorded and used in analyzing the simulation results from EnergyPlus v8.8, DOE-2.2 v3.65 and DOE-2.1e v127. These engines are commonly used in the United States for building energy code compliance, federal, state, and utility incentives programs, as well as energy efficient design of new buildings and energy retrofit of existing buildings. Seven conventional overhead mixing ventilation scenarios were tested and each engine was found to have a similar level of agreement with the measurements of space-level heating and sensible cooling loads. These results provide useful information regarding the accuracy of these engines in predicting the cooling and heating load elements of whole building energy performance. This information is intended for practitioners who are concerned about transitioning between simulation tools with different engines and for managers of utility programs leveraging these tools for evaluating and/or projecting measure savings to be incentivized under their programs. The results of the comparisons of simulated and measured performance indicate that the predictions from all three engines are not significantly different. The 24-hour average value of the absolute mean bias indicates the likely magnitude of the error in any particular case. The average mean bias is reduced by cancelation of overprediction in one case by underprediction in another. The daytime absolute mean biases, which may be more important for both energy performance and occupant comfort, are ~6%, presumably because of the greater complexity involved in simulating in the presence of solar radiation. EnergyPlus typically overpredicts the cooling load and/or underpredicts the heating load by ~1.5% and the DOE-2 engines typically underpredict the cooling load by approximately the same amount. The Root Mean Square Error is relatively more sensitive to shorter term variations in the difference between predicted and measured loads; the three engines have similar values, ~10%, suggesting that the uncertainties in their predictions of peak loads may also be similar in magnitude. The implication of these results is that users, both designers and program analysts, can use EnergyPlus, DOE-2.1e, or DOE-2.2 to model conventional commercial buildings equipped with overhead mixing ventilation with a similar level of confidence. Further work is required to better understand the variability in the level of agreement between the engine predictions and FLEXLAB measurements, where a particular engine will agree well with FLEXLAB in some cases and not so well in others and another engine will agree or disagree in different cases. As the sources of this variability are identified and eliminated or reduced significantly, it is recommended that the experimental capabilities and methods developed in the study reported here should be applied to validating heating and cooling load calculations for spaces with different types of furniture and miscellaneous loads. These methods should then be applied to low energy space conditioning systems in EnergyPlus including, in particular, radiant slab and radiant ceiling panel cooling and heating systems and ‘mixed mode’ systems that combine mechanical cooling and natural ventilation systems, focusing on controls, including control of thermal mass. The work reported here addresses the conventional method of heating and cooling occupied spaces; other methods, such as the use of radiant heating and cooling systems have the potential to provide equivalent occupant comfort, or better, with lower energy consumption. These systems are addressed more explicitly in EnergyPlus but there is a need for empirical validation to give users the same level of confidence in modeling these systems that they have, or should have, in modeling conventional systems, based on the results presented here.
Malaysia has recently set an ambitious target of achieving carbon neutrality as early as 2050. To accomplish this, the country will need to strategically reduce its emissions across all sectors. In 2020, Malaysia emitted approximately 368 MtCO2e, with the largest sources of emissions including electricity (36% of total emissions), transportation (17%), and industry (15%)1. We find that the greatest reductions in emissions can therefore come from decarbonizing power generation and electrifying end-use sectors. Digitalization, smart technologies, and improved energy efficiency will significantly reduce economy-wide energy consumption. By leveraging efficient technologies, both Malaysia and Kuala Lumpur can address the challenges posed by rapid urbanization and climate change. Digitalization is a broad category that includes a variety of measures; for example, the wide adoption of high-efficiency appliances and lighting or improved building energy codes in the buildings sector. Similarly, technological improvements can advance industrial energy efficiency, and for transportation, smart technologies cover a shift from private to public transportation and the greater use of electric vehicles. While renewable energy (RE) will play a crucial role in decarbonization, achieving carbon neutrality in certain sectors will be difficult without emerging technologies like carbon capture and storage (CCS) and innovative fuel sources such as hydrogen. In order for Malaysia to rely on CCS as a mitigation option, early investment and incentives to the private sector will be critical. This holds for the use of hydrogen as well: investing in the necessary technology, infrastructure, and human capital will allow Malaysia to position itself as an innovator in the region and leverage these advanced technologies as a key part of its climate strategy. Another possible carbon removal option other than CCS would be a land-use sink; however, given that Malaysia is still developing and may deforest in the near-term, this report does not focus on the mitigation potential of land-use change. With its innovative and bold climate plans, Kuala Lumpur is primed to be a leader in regional climate change efforts. Kuala Lumpur is also engaged in several international collaborations to ensure sustainable city development such as the C40 network and the ASEAN Smart Cities Partnership. As such, the city will play a critical role in contributing to Malaysia’s overall climate goals and as a policy trendsetter through ambitious, scalable plans. One key factor in these emissions reductions is that Kuala Lumpur has full control over its building guidelines, allowing for ambitious policies resulting in significant emissions reductions. However, in other sectors, Kuala Lumpur has less direct control over regulations; for example, power generation and integration of RE are largely in the hands of the Malaysian government. With limited and primarily light industry, Kuala Lumpur’s contributions to emissions reductions here are curbed. And, while Kuala Lumpur has control over local transportation policies like increasing access to and quality of public transportation, broad shifts in transportation will stem from national-level policies. As such, multi-level governance is an integral component of Malaysia’s climate strategy and coordination between local and national governments will be essential in reducing emissions and achieving other climate goals. This report addresses these and other key challenges and opportunities Malaysia faces on the road to carbon neutrality.
Building energy modeling (BEM) is commonly used to estimate the energy usage of residential buildings. Uses for BEM include calculating home energy ratings, demonstrating compliance with performance-based energy codes, and establishing whether designs meet voluntary program requirements, such as ENERGY STAR® qualified homes. BEM requires simulating subsystems within the building, including storage-type water heaters. To properly simulate the in-situ performance of residential storage water heaters, it is necessary to determine key water heater parameters, including the overall heat loss coefficient (UA) and conversion efficiency (?c) of the water heater, based on the rated efficiency of the water heater. The testing procedure and rating standard for residential water heaters have recently changed: the new rating standard provides a Uniform Energy Factor (UEF) rather than the Energy Factor (EF) used previously. This paper discusses how to derive the necessary model parameters from the ratings data produced from the latest test procedure.
The Nationally Determined Contributions (NDCs) are allowing countries to examine options for reducing emissions through a range of domestic policies. Here we use the Global Change Assessment Model to demonstrate the potential impacts of energy policies and discuss strategies to implement India’s NDC with a focus on the buildings sector. Buildings are the largest end-use sector globally, and building energy consumption is expected to increase as income grows in developing countries. We find that implementing a range of energy efficiency policies robustly can reduce total Indian building energy use by 22% and lower total Indian carbon dioxide emissions by 9% in 2050 compared to the business as usual scenario. Among various policies, energy codes for new buildings can result in the most significant savings. For all energy efficiency policies, well-coordinated, consistent implementation is critical, which requires coordination across different departments and agencies, improving capacity of stakeholders, and developing appropriate institutions to facilitate policy implementation. Renewable energy deployment can also reduce carbon emissions from buildings, and incentives in the short term are important to ensuring strong market uptake. Effective development and implementation of building energy policies could help avoid lock-in of carbon-intensive infrastructure, while improving living standards and generating health benefits.
With building electric demand becoming increasingly dynamic, and a growing percentage of intermittent renewable power generation from solar photovoltaics and wind turbines, the power grid is facing increasing challenge to manage the real time balance between the supply and demand. With advancements in smart sensing and metering, smart appliances, electric vehicles, and energy storage technologies, demand side management of residential buildings can help the grid to improve stability by optimizing flexible loads. This paper reviews recent studies on residential building demand side management, with a focus on characterization and quantification of energy flexibility covering various types of flexible loads, metrics, methods, and applications. The reviewed studies showed four levels of applications: building level (45%), district or community level (29%), system level (19%), and building sector level (7%). Shifting loads is the dominant flexibility type in 60% of applications, followed by shedding (19%), generation (16%), and modulating (6%). Depending on the technology and application scope, flexible operations have a wide range of performance, with peak power reductions of 1%~65%, energy savings up to 60%, operational cost reduction of 1%~48%, and greenhouse gas emission reductions of up to29%. More than half (51%) of the studies employed control strategies to achieve flexibility; among those 72% used optimal controls, while 28% used rule-based controls. About 58% of the studies used mathematical formulation to quantify energy flexibility. Most studies were based on simulation, while less than 15% of the studies had measurements from experiments or field tests. The review reveals research opportunities to address significant gaps in the existing literature: (1) establishing a common definition and performance metrics for energy flexibility of buildings that are technology and application agnostic, (2) developing an ontology to standardize representation of flexibility resources for interoperability, (3) integrating occupant impacts into the quantification and optimization of energy flexibility, and (4) developing requirements and credits of energy flexibility in building energy codes and standards. Findings from the review can inform future research and development of energy flexible buildings which are essential to a reliable and resilient power grid.
This document updates commercial building construction weights for the purpose of estimating national and state-by-state energy savings impacts of changes made to various commercial energy codes and standards using disaggregate construction volume data for the years 2003-2007.
The OpenStudio Building Energy Standards Measure Repository is a comprehensive collection of innovative OpenStudio measures designed to facilitate energy code analysis. OpenStudio is a cutting-edge platform brings together physics-based building energy modeling (BEM), BEM process automation, and large-scale computing capabilities. Contains OpenStudio Standards Performance Rating Method Measure (IPID 32936) and OpenStudio Measure to Generate IPLV-specific Chiller Performance Curves for Chillers (IPID 32940)
Home Innovation Research Labs studied the extended plate and beam wall (EP&B) system during a two-year period from mid-2015 to mid-2017 to determine the wall’s structural performance, moisture durability, constructability, and cost effectiveness for use as a high-R enclosure system for energy code minimum and above-code performance in climate zones 4–8.
The BRICR project applied large-scale building energy modeling concepts with the aim of reducing the cost of energy efficiency targeting, design, and project development, and measurement of energy savings for energy efficiency programs implemented by local governments that serve small and medium commercial buildings (SMB). The project leveraged the services and resources of existing local government energy programs serving disadvantaged and hard-to-reach SMB customers. In contrast to programs run by utilities, local government programs generally do not have direct access to energy billing records for an entire class of customers in a geographic area, which prior research demonstrated useful for large-scale building energy model baseline development and calibration. , However, local governments are rich in public records that offer important clues about physical attributes and uses that, along with behavior, determine energy use. Relying only on public records, BRICR demonstrated development of credible baseline energy models for 3,792 office, retail, and hotel buildings. Publicly disclosed annual energy use data from a local energy benchmarking program and anonymized data from the Building Performance Database, the nation’s largest dataset about energy-related characteristics of buildings, were utilized to validate and calibrate energy models via an innovative method comparing distributions of energy intensity by fuel type for portfolios of buildings of similar size, vintage, and use. Portfolio calibration does not provide certainty that an energy model fits an individual building; the method is useful when billing data is not accessible – a common situation for researchers, energy service providers and ESCOs, local governments, and any party other than a utility. A software component was developed, the BRICR gem, which automates simulation when relevant data is added or edited by the user to a file saved in the standardized BuildingSync XML schema for energy audit data. The component was demonstrated as a simplified means to generate a mass of energy models corresponding to public records containing basic attributes such as building scale, location, use, year built, and aspect ratio in combination with building energy code prototype data corresponding to use and vintage. The component was also demonstrated as a simplified means to automate energy simulation when attributes are revised; the intention was to enable iterative improvement of the baseline model and energy savings estimates for common energy conservation measures as users revise relevant attributes based on their observations. In the context of institutional change and uncertainty for the participating local government energy programs, 13 whole building retrofits were completed. Impacts were measured by applying the CalTRACK2.0 methods to standardize measurement of normalized metered energy consumption. The GRIDMeter methods of stratified sampling and individual load shape analysis were applied to adjust for impacts of the effect of COVID-19 on retrofitted buildings in the context of all local buildings of similar size and use. Excluding impacts of the pandemic, retrofitted buildings demonstrated between 1.6% and 25.1% reduction in energy use. The project contributed use cases and feedback that helped inform evolution of the software tools and data formats that were combined for the first time in the BRICR project.
On June 1, 2022, the White House launched the National Initiative to Advance Building Codes (NIABC): a whole-government initiative to assure alignment of, and minimum standards for, all building activity funded through federal agency programs. This includes ensuring the use of current consensus-based model building and energy codes and standards, with a focus on underserved and vulnerable communities. The initiative will accelerate the adoption of modern building codes to improve resiliency, create good-paying jobs, and lower energy bills.
Appendix G, the Performance Rating Method in ASHRAE Standard 90.1 has been updated to make two significant changes for the 2016 edition, to be published in October of 2016. First, it allows Appendix G to be used as a third path for compliance with the standard in addition to rating beyond code building performance. This prevents modelers from having to develop separate building models for code compliance and beyond code programs. Using this new version of Appendix G to show compliance with the 2016 edition of the standard, the proposed building design needs to have a performance cost index (PCI) less than targets shown in a new table based on building type and climate zone. The second change is that the baseline design is now fixed at a stable level of performance set approximately equal to the 2004 code. Rather than changing the stringency of the baseline with each subsequent edition of the standard, compliance with new editions will simply require a reduced PCI (a PCI of zero is a net-zero building). Using this approach, buildings of any era can be rated using the same method. The intent is that any building energy code or beyond code program can use this methodology and merely set the appropriate PCI target for their needs. This report discusses the process used to set performance criteria for compliance with ASHRAE Standard 90.1-2016 and suggests a method for demonstrating compliance with other codes and beyond code programs.
According to the EIA, simple commercial buildings account for 97% of total commercial building stock. However, most simple commercial buildings for example small- to mid-sized offices, retail, schools and warehouses do not benefit from the data-driven decision-making capabilities of whole-building energy modeling. The high cost of custom modeling limits the use of energy modeling of simple buildings for new construction or retrofit measures. Lack of tools providing helpful information on interactive savings estimates creates difficulties in meeting aggressive decarbonization and energy efficiency goals for simple building designers and utility program managers. This paper reviews a beta phase Simple Building Calculator with the ability to generate relatively accurate and interactive modeling results based on a limited but robust set of inputs. It can evaluate whole-building or single measure savings in new or existing buildings, compare measure package choices, or provide simplified performance modeling for energy codes and utility incentives. The tool combines physical (annual whole building prototype simulation) and statistical modeling techniques to predict annual energy performance. It supports a variety of building characteristics for envelope, HVAC, and lighting with parameters ranging from vintage to max tech configurations, as well as support for single-zone and simple multi-zone HVAC systems. The Simple Building Calculator was designed to provide immediate feedback for otherwise computationally intensive tasks like measure comparison, development of multiple measure package combinations, or verification that measures meet efficiency targets—all with the goal of providing a tool for quick annual energy simulation of simple commercial buildings.