An efficient quantum algorithm for building effective Hamiltonians on fault-tolerant hardware
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Pathak, Shivesh↗
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Results for “Building Efficiency”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Development of a Control Platform for a Building-Scale Hybrid Solar PV-Natural Gas Microgrid
Building-scale microgrids are a type of behind-the-meter microgrids where the building operator has control of the distributed energy resources, including, in this case, a natural gas-fired microturbine in addition to solar PV and battery energy storage systems. There is a growing trend in deploying behind-the-meter microgrids due to their benefits including the resiliency of serving critical loads, especially in regions with abundant natural gas. In order to ensure distributed energy resources are dispatched optimally for the desired mode of operation, a hierarchical control platform including a centralized controller was developed and installed. The platform includes communication and control infrastructure that interface with controllers for distributed energy resources and the building automation system of a recently built energy efficient commercial building. Based on desirable outcomes under different grid and building conditions, operational modes were defined for the microgrid controller. The controller is programmed to map each mode to respective operational modes for distributed energy resources controllers. Experimental data for test runs corresponding to two operational modes confirm the communication and control infrastructure can execute hierarchical control commands. Finally, dispatch optimization for a year-long simulation of system operation is presented and the benefits of the hybrid solar PV-natural gas setup are evaluated.
Energy & Fuels↗
Financing Turnkey Efficiency Solutions for Small Buildings and Small Portfolios
Building Technologies Office's commercial building integration project 2013
2013 BTO Program Peer Review↗
What a New Energy Efficiency Measure for Commercial Buildings Means to You
This article describes a new path for compliance with ASHRAE Standard 90.1-2016. The new approach will lead to increased flexibility for designers, multiple uses for the same building energy models, increased recognition of energy saving design strategies, and lower energy modeling costs.
Appendix G↗
Embodied Carbon Reduction in New Construction: Reference Guide
The U.S. Department of Energy launched the Advanced Building Construction (ABC) Initiative in 2019 to modernize and streamline building renovation and construction processes that facilitate the integration of high-performance and low-carbon solutions in the U.S. building stock. There are four attributes of ABC that are the focus of the Initiative: affordable, fast, appealing, and low carbon. Substantial improvements have been made to reduce operational carbon emissions of buildings through efficiency and electrification. However, to achieve low-carbon new construction buildings, increased efforts to reduce the embodied carbon of buildings are needed. Embodied carbon emissions in buildings come primarily from the manufacturing of building envelope materials such as concrete, steel, lumber, and glass, among others. Recent studies show that construction and renovation of buildings account for 5% of energy use and 10% of carbon emissions globally.
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Potential of artificial intelligence in reducing energy and carbon emissions of commercial buildings at scale
Artificial intelligence has emerged as a technology to enhance productivity and improve life quality. However, its role in building energy efficiency and carbon emission reduction has not been systematically studied. This study evaluated artificial intelligence’s potential in the building sector, focusing on medium office buildings in the United States. A methodology was developed to assess and quantify potential emissions reductions. Key areas identified were equipment, occupancy influence, control and operation, and design and construction. Six scenarios were used to estimate energy and emissions savings across representative climate zones. Here we show that artificial intelligence could reduce cost premiums, enhancing high energy efficiency and net zero building penetration. Adopting artificial intelligence could reduce energy consumption and carbon emissions by approximately 8% to 19% in 2050. Combining with energy policy and low-carbon power generation could approximately reduce energy consumption by 40% and carbon emissions by 90% compared to business-as-usual scenarios in 2050.
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Impact analysis of heating electrification in US buildings with geothermal heat pumps
Few studies have investigated the impacts of large-scale deployment of geothermal heat pumps (GHPs, also called ground source heat pumps) on the electric grid. GHPs utilize the ground as a heat source to warm buildings more efficiently than other space-heating systems. The coupling with the ground offers seasonal thermal storage so that GHPs can also cool buildings in summer more efficiently than other space-cooling systems. This study simulated the performance of GHP systems for various commercial and residential buildings in 15 climate zones in the United States. Combined with the latest End-Use Load Profiles of the US building stock and grid modeling, this study aims to assess the impacts of a national deployment of GHP systems on the US electric grid in terms of energy consumption, emissions, and operational resilience. The preliminary results show that the GHP deployment can save 429 billion kWh of electricity (a 19% reduction from baseline) and reduce carbon emissions by 496 million tons per year (a 31 % reduction from baseline). A geographical view of the results indicates that retrofitting existing HVAC systems with new GHP systems can lead to further reductions in annual electricity consumption and peak electricity demand in the southern regions of the United States than in other parts of the country. On the other hand, GHP retrofits result in higher percentages of site energy savings and carbon emission reduction in the north (cold climates) than in the south (warm climates).
Liu, Xiaobing↗
California: California's Clean Energy Resources and Economy [Brochure]
California is remarkably well positioned to compete in the global race for clean energy. It is second in the nation among states with renewable power capacity, contains multiple renewable energy resources from all types of renewable energy, and is the nation’s leader in solar, biomass, and geothermal power generation. For example, California has the most solar photovoltaic installations in the country and is a leader in wind energy. It added more new wind power than any other state in 2011, and wind now makes up 4% of the state’s electricity generation. The state also takes advantage of abundant hydroelectric resources from California rivers. California is also a perennial leader in energy efficiency investment, leading the country with $\$$1.1 billion in utility investment for energy efficiency programs in 2010. Investment from 2010–2012 is expected to yield savings of nearly 7,000 gigawatt hours of electricity. The state has set unprecedented energy efficiency standards for appliances, equipment, and residential and commercial buildings. For example, the recently approved 2013 Building Energy Efficiency Standards will result in 25% and 30% more efficient residential and commercial construction standards respectively than those that they will be replacing, providing more savings for California energy users.
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Air quality and comfort constrained energy efficient operation of multi-zone buildings
Maintaining indoor air quality (IAQ) through effective ventilation is essential for the well-being and productivity of building occupants. Control strategies aimed at improving the efficiency of heating, ventilation and air conditioning (HVAC) systems must jointly determine ventilation and heating and cooling processes. Here, in this paper, we study the problem of minimizing the energy consumption of the HVAC system in a multi-zone building, while meeting thermal comfort and IAQ requirements. We first perform a steady state analysis of the zonal carbon dioxide (CO 2 ) concentration and the temperature dynamics. The resulting expressions are convex in the zonal mass flow rates and zonal temperatures. Guided by the steady state solutions for meeting the thermal comfort constraints, we develop two control policies for improving the energy efficiency of building HVAC systems while jointly satisfying indoor temperature and IAQ constraints. We compare the performance of our proposed approaches with those of multiple baseline approaches which implement separate regimes for controlling zonal temperature and IAQ for a typical work-day in a multi-zone campus building. We have evaluated the performance of our proposed approaches under varying levels of flexibility in zonal temperatures. We have shown that zonal temperature flexibility can result in energy savings up to 32% (for the same control strategies) as compared to the case where no such flexibility is permitted. Our proposed approaches were seen to offer potential savings of nearly 29% compared to the baseline.
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Survey and Analysis of Weather Data for Building Energy Simulations
In recent years, calibrated energy modeling of residential and commercial buildings has gained importance in a retrofit-dominated market. Accurate weather data plays an important role in this calibration process and projected energy savings. It would be ideal to measure weather data at the building location to capture relevant microclimate variation but this is generally considered cost-prohibitive. There are data sources publicly available with high temporal sampling rates but at relatively poor geospatial sampling locations. To overcome this limitation, there are a growing number of service providers that claim to provide real time and historical weather data for 20-35 km2 grid across the globe. Unfortunately, there is limited documentation from 3rd-party sources attesting to the accuracy of this data. This paper compares provided weather characteristics with data collected from a weather station inaccessible to the service providers. Monthly average dry bulb temperature; relative humidity; direct, diffuse and horizontal solar radiation; and wind speed are statistically compared. Moreover, we ascertain the relative contributions of each weather variable and its impact on building loads. Annual simulations are calculated for three different building types, including a closely monitored and automated energy efficient research building. The comparison shows that the difference for an individual variable can be as high as 90%. In addition, annual building energy consumption can vary by 7% while monthly building loads can vary by 40% as a function of the provided location s weather data.
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Deep Point Cloud Building Envelope Segmentation (DeeP-CuBES) using Deep Learning
Building Information Modeling (BIM) plays an important role in building design and construction, particularly for achieving energy-efficient retrofits. Building envelope retrofits using panelized prefabricated system, such as those popularized by the Energiesprong program, need accurate as-built dimensions of facade features (windows, doors, etc.) to achieve the desired thermal and air tightness. Traditionally, building surveying is done manually, resulting in a time-consuming and labor-intensive process. Recently, 3D point clouds from terrestrial LiDAR have been used to automate the generation of as-built dimensions of existing buildings. However, automated BIM using LiDAR relies on solving the point cloud semantic segmentation (PCSS) problem. In this work, we propose a robust pipeline for solving the PCSS problem using deep neural networks, focusing on overcoming challenges posed by imbalanced datasets and complex architectural features. We introduce the first high-density, labeled, and validated building envelope point cloud dataset derived from multiple building scans, specifically curated to tackle challenges in facade-level segmentation. Results from the trained neural networks show that advanced attention-based architectures and incorporating radiometry (light intensity and RGB) features significantly boost segmentation accuracy for windows and doors.
Selvakumar, Balaji [ORNL]↗
Sustainable Campus with PEV and Microgrid
Market penetration of electric vehicles (EVs) is gaining momentum, as is the move towards increasingly distributed, clean and renewable electricity sources. EV charging shifts a significant portion of transportation energy use onto building electricity meters. Hence, integration strategies for energy-efficiency in buildings and transport sectors are of increasing importance. This paper focuses on a portion of that integration: the analysis of an optimal interaction of EVs with a building-serving transformer, and coupling it to a microgrid that includes PV, a fuel cell and a natural gas micro-turbine. The test-case is the Nanyang Technological University (NTU), Singapore campus. The system under study is the Laboratory of Clean Energy Research (LaCER) Lab that houses the award winning Microgrid Energy Management System (MG-EMS) project. The paper analyses three different case scenarios to estimate the number of EVs that can be supported by the building transformer serving LaCER. An approximation of the actual load data collected for the building into different time intervals is performed for a transformer loss of life (LOL) calculation. The additional EV loads that can be supported by the transformer with and without the microgrid are analyzed. The numbers of possible EVs that can be charged at any given time under the three scenarios are also determined. The possibility of using EV fleet at NTU campus to achieve demand response capability and intermittent PV output leveling through vehicle to grid (V2G) technology and building energy management systems is also explored.
Singh, Reshma↗
A long-term, integrated impact assessment of alternative building energy code scenarios in China
China is the second largest building energy user in the world, ranking first and third in residential and commercial energy consumption. Beginning in the early 1980s, the Chinese government has developed a variety of building energy codes to improve building energy efficiency and reduce total energy demand. This paper studies the impact of building energy codes on energy use and CO2 emissions by using a detailed building energy model that represents four distinct climate zones each with three building types, nested in a long-term integrated assessment framework GCAM. An advanced building stock module, coupled with the building energy model, is developed to reflect the characteristics of future building stock and its interaction with the development of building energy codes in China. This paper also evaluates the impacts of building codes on building energy demand in the presence of economy-wide carbon policy. We find that building energy codes would reduce Chinese building energy use by 13% - 22% depending on building code scenarios, with a similar effect preserved even under the carbon policy. The impact of building energy codes shows regional and sectoral variation due to regionally differentiated responses of heating and cooling services to shell efficiency improvement.
Building energy codes↗
Brick : Metadata schema for portable smart building applications
Buildings account for 32% of worldwide energy usage. A new regime of exciting new “applications” that span a distributed fabric of sensors, actuators and humans has emerged to improve building energy efficiency and operations management. These applications leverage the technological advances in embedded sensing, processing, networking and methods by which they can be coupled with supervisory control and data acquisition systems deployed in modern buildings and with users on mobile wireless platforms. There are, however, several technical challenges to confront before such a vision of smart building applications and cyber-physical systems can be realized. The sensory data produced by these systems need significant curation before it can be used meaningfully. This is largely a manual, cost-prohibitive task and hence such solutions rarely experience widespread adoption due to the lack of a common descriptive schema. Recent attempts have sought to address this through data standards and metadata schemata but fall short in capturing the richness of relationships required by applications. Here, this paper describes Brick, a uniform metadata schema for representing buildings that builds upon recent advances in the area. Our schema defines a concrete ontology for sensors, subsystems and the relationships between them, which enables portable applications. We demonstrate the completeness and effectiveness of Brick by using it to represent the entire vendor-specific sensor metadata of six diverse buildings across different campuses, comprising 17,700 data points, and running eight unmodified energy efficiency applications on these buildings.
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Retail Building Guide for Entrance Energy Efficiency Measures
This booklet is based on the findings of an infiltration analysis for supermarkets and large retail buildings without refrigerated cases. It enables retail building managers and engineers to calculate the energy savings potential for vestibule additions for supermarkets; and bay door operation changes in large retail stores without refrigerated cases. Retail managers can use initial estimates todecide whether to engage vendors or contractors of vestibules for pricing or site-specific analyses, or to decide whether to test bay door operation changes in pilot stores, respectively.
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North Birmingham Housing Energy Baseline and Upgrade Strategies [Slides]
The community of North Birmingham, Alabama, participated in the Communities LEAP pilot program. As part of this technical assistance pilot, residential buildings, energy efficiency, and electrification were analyzed. This slide deck details the baseline analysis of residential buildings in the community and potential upgrade strategies.
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Low-cost phase change material as an energy storage medium in building envelopes: Experimental and numerical analyses
A promising approach to increasing the energy efficiency of buildings is the implementation of a phase change material (PCM) in the building envelope. Numerous studies over the last two decades have reported the energy saving potential of PCMs in building envelopes, but their wide application has been inhibited, in part, by their high cost. This article describes a novel PCM made of naturally occurring fatty acids/glycerides trapped into high density polyethylene (HDPE) pellets and its performance in a building envelope application. The PCM-HDPE pellets were mixed with cellulose insulation and then added to an exterior wall of a test building in a hot and humid climate, and tested over a period of several months, To demonstrate the efficacy of the PCM-enhanced cellulose insulation in reducing the building envelope heat gains and losses, side-by-side comparison was performed with another wall section filled with cellulose-only insulation. Further, numerical modeling of the test wall was performed to determine the actual impact of the PCM-HDPE pellets on wall-generated heating and cooling loads and the associated electricity consumption. The model was first validated using experimental data and then used for annual simulations using typical meteorological year (TMY3) weather data. Furthermore, this article presents the experimental data and numerical analyses showing the energy-saving potential of the new PCM.
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Energy and Energy Cost Savings Analysis of the 2015 IECC for Commercial Buildings
As required by statute (42 USC 6833), DOE recently issued a determination that ANSI/ASHRAE/IES Standard 90.1-2013 would achieve greater energy efficiency in buildings subject to the code compared to the 2010 edition of the standard. Pacific Northwest National Laboratory (PNNL) conducted an energy savings analysis for Standard 90.1-2013 in support of its determination . While Standard 90.1 is the model energy standard for commercial and multi-family residential buildings over three floors (42 USC 6833), many states have historically adopted the International Energy Conservation Code (IECC) for both residential and commercial buildings. This report provides an assessment as to whether buildings constructed to the commercial energy efficiency provisions of the 2015 IECC would save energy and energy costs as compared to the 2012 IECC. PNNL also compared the energy performance of the 2015 IECC with the corresponding Standard 90.1-2013. The goal of this analysis is to help states and local jurisdictions make informed decisions regarding model code adoption.
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