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At least 973 records · Page 54

Coupling thermal energy storage with a thermally anisotropic building envelope for building demand-side management across various US climate conditions

Here, the thermally anisotropic building envelope (TABE) is a novel active building envelope that enhances energy efficiency and thermal comfort in buildings by transferring heat and cold between building envelopes and hydronic loops. When coupled with thermal energy storage (TES) units, the TABE + TES enables the storage of both heat and cold energy captured by the TABE roof or exterior walls. This stored energy can be later released by the TABE floor for indoor heating and cooling, benefiting both the grid and the end user. This paper evaluates the merits of TABE + TES for building demand-side management across various US climate conditions, focusing on peak load shaving, annual energy savings, and cost savings under time-of-use (TOU) electric rate schedules. Simulations were conducted by integrating time-of-day–informed, rule-based control strategies in MATLAB, TABE components and TES units in COMSOL Multiphysics, and whole-building energy analysis in EnergyPlus. A case study using the US Department of Energy’s prototype single-family detached house model in Birmingham, Alabama; Los Angeles, California; Oak Ridge, Tennessee; and Denver, Colorado, showed that the TABE + TES system achieved (1) 70 % peak load shaving in Los Angeles and Denver and 20 % in Birmingham and Oak Ridge; (2) significant peak electricity savings of 351–497 kWh, reducing peak energy consumption by 38 %–78 %; and (3) annual heating cost savings of 0.79 $\$$/m2–1.17 $\$$/m 2 and cooling cost savings of 0.60 $\$$/m 2 –1.17 $\$$/m 2 using a normal utility rate or low-TOU rate. The benefits of employing the TABE + TES system are even more significant under high TOU rates.

25 ENERGY STORAGE↗

Using Dashboards to Improve Energy and Comfort in Federal Buildings

Federal agencies are taking many steps to improve the sustainability of their operations, including improving the energy efficiency of their buildings, promoting recycling and reuse of materials, encouraging carpooling and alternative transit schemes, and installing low flow water fixture units are just a few of the common examples. However, an often overlooked means of energy savings is to provide feedback to building users about their energy use through information dashboards connected to a building?s energy information system. An Energy Information System (EIS), broadly defined, is a package of performance monitoring software, data acquisition hardware, and communication systems that is used to collect, store, analyze, and display energy information. At a minimum, the EIS provides the whole-building energy-use information (Granderson 2009a). We define a ?dashboard? as a display and visualization tool that utilizes the EIS data and technology to provide critical information to users. This information can lead to actions resulting in energy savings, comfort improvements, efficient operations, and more. The tools to report analyzed information have existed in the information technology as business intelligence (Few 2006). The dashboard is distinguished from the EIS as a whole, which includes additional hardware and software components to collect and storage data, and analysis for resources and energy management (Granderson 2009b). EIS can be used for a variety of uses, including benchmarking, base-lining, anomaly detection, off-hours energy use evaluation, load shape optimization, energy rate analysis, retrofit and retro-commissioning savings (Granderson 2009a). The use of these EIS features depends on the specific users. For example, federal and other building managers may use anomaly detection to identify energy waste in a specific building, or to benchmark energy use in similar buildings to identify energy saving potential and reduce operational cost. There are several vendors of EIS technology that provide information on energy and other environmental variables in buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Machine Learning for Advanced Building Construction

High-efficiency retrofits can play a key role in reducing carbon emissions associated with buildings if processes can be scaled-up to reduce cost, time, and disruption. Here we demonstrate an artificial intelligence/computer vision (AI/CV)-enabled framework for converting exterior build scans and dimensional data directly into manufacturing and installation specifications for overclad panels. In our workflow point clouds associated with LiDAR-scanned buildings are segmented into a facade feature space, vectorized features are extracted using an iterative random-sampling consensus algorithm, and from this representation an optimal panel design plan satisfying manufacturing constraints is generated. This system and the corresponding construction process is demonstrated on a test facade structure constructed at the National Renewable Energy Laboratory (NREL). We also include a brief summary of a techno-economic study designed to estimate the potential energy and cost impact of this new system.

build scans↗

Consumer Benefits of Clean Energy: Energy Efficiency

Meeting national and state decarbonization goals requires a transition to clean energy technologies. Energy efficiency, demand flexibility, renewable energy and storage can reduce consumers’ electricity bills, lower total electricity system costs, and provide health and resilience benefits. Berkeley Lab developed a series of briefs that explore these consumer benefits of a clean energy transition. This brief focuses on energy efficiency benefits, and builds on prior analysis from Berkeley Lab’s Cost of Saved Energy database. We show that energy efficiency remains a low-cost energy and capacity resource; the levelized cost of saving energy for the programs included in the analysis is $\$0.02$/kilowatt-hour and the cost of saving peak demand is less $\$120$/kilowatt. Understanding the impact of the program mix, portfolio size, and duration of implementation for customer-funded energy efficiency portfolios can guide regulatory oversight of these programs, help utilities better utilize energy efficiency as a resource, and inform building energy decarbonization policies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A comparison of thermal zone aggregation methods

The impact of increasing energy prices on building operation budgets has fueled demand for more energy-efficient structures. Existing building energy simulation tools generate an immense amount of data yet comparatively little knowledge. This paper introduces a framework that allows aggregation-based model reduction to operate on geometric building information models. The resulting aggregation sequence provides designers with faster simulations and affords insight into complex multi-scale thermal interactions. A comparison of the trade-off between simulation speed and accuracy for three hierarchical cluster partitioning methods concludes the discussion.

97 MATHEMATICS AND COMPUTING↗

Technology Solutions Case Study: Cold Climate Foundation Wall Hygrothermal Research Facility, Cloquet, Minnesota

This case study describes the University of Minnesota’s Cloquet Residential Research Facility (CRRF) in northern Minnesota, which features more than 2,500 ft2 of below-grade space for building systems foundation hygrothermal research. Here, the NorthernSTAR Building America Partnership team researches ways to improve the energy efficiency of the building envelope, including wall assemblies, basements, roofs, insulation, and air leakage.

basement foundation insulation↗

At the Core: Fundamental Building Science Education Matters More Than Building Type

As building technologies become more advanced, the need for highly skilled and qualified workers has increased. Both residential and commercial building industries struggle to capture the full benefit of these new technologies because of the limited building science knowledge base of the professionals researching, designing, building, and selling these structures. To help address this need, the U.S. Department of Energy’s (DOE’s) Residential Building Integration (RBI) program initiated the Guidelines for Building Science Education (GBSEs). These guidelines provide guidance on the fundamental building science knowledge base that is helpful for a wide range of building industry jobs. This effort provides a mechanism for training organizations to align core curriculum that can be applied to any building type. At the same time, DOE’s Commercial Building Integration (CBI) program has been spearheading a full suite of impactful initiatives including the Better Buildings Workforce Guidelines (BBWGs), which provide voluntary national guidelines from which select stakeholders can develop high-quality and nationally recognized training and certification programs. The BBWG framework helps to improve quality and scalability issues for five energy efficiency-related jobs: Building Energy Auditor, Building Commissioning Professional, Building Operations Professional, Building Operations Journey-Worker and Energy Manager. The residential and commercial building programs are both interested in helping to create better buildings through an improved workforce. The two program initiatives complement each other in many ways. The GBSEs pave the way for more specialized training and education offered by industry and academia, which lead to credentials that signify competency. The BBWGs cover credentialing for energy efficiency jobs—a critical area that DOE believed could benefit from incentives for credentialing bodies and building operators that would improve the energy efficiency of commercial buildings. This paper summarizes the steps DOE programs have taken to work together and the outcome of this symbiotic relationship.

Metzger, Cheryn E.↗

An approach for fast and accurate simulation of phase change material based thermal energy storage in buildings

Latent heat thermal energy storage (LHTES) has significant potential for mitigating peak electricity demand and enabling load shifting in buildings. Phase Change Material embedded heat exchangers (PCM-HX) can significantly improve energy demand management due to high storage capacity. However, PCM-HX evaluation typically depends on computationally expensive fully transient simulations, posing significant challenges for scalable system- and building-level energy assessments across different climates and system architectures. This paper presents a generalized, accurate, and computationally efficient methodology for simulating building energy systems integrated with LHTES. The PCM-HX transient performance is represented by performance maps generated using a Generalized Resistance-Capacitance Model (GRCM) that enables accurate predictions of arbitrary PCM-HXs at low computational cost. The feasibility of the proposed approach was verified using a case study considering a dual-mode heat pump-thermal energy storage (HP-TES) system simulated in Modelica with Spawn of EnergyPlus™ for a DOE prototype small office building in two locations: Tampa, FL, and International Falls, MN. The PCM-HX performance maps provided accurate predictions of PCM-HX transient behavior, with mean absolute percentage deviations within 2–4% compared to GRCM while also achieving at least 1800× reduction in computational time. Moreover, the HP-TES system achieved energy savings of up to 17.4% in Tampa, FL, and 62.2% in International Falls, MN, demonstrating the broader applicability of the proposed methodology across different climate zones. This work highlights the importance of robust PCM-HX models in enabling accurate and computationally efficient building-level simulations and enabling future research opportunities for investigating optimized HP-TES designs and advanced control strategies for grid-interactive buildings.

Modelica↗

DEEP: A Database of Energy Efficiency Performance to Accelerate Energy Retrofitting of Commercial Buildings

The paper presents a method and process to establish a database of energy efficiency performance (DEEP) to enable quick and accurate assessment of energy retrofit of commercial buildings. DEEP was compiled from results of about 35 million EnergyPlus simulations. DEEP provides energy savings for screening and evaluation of retrofit measures targeting the small and medium-sized office and retail buildings in California. The prototype building models are developed for a comprehensive assessment of building energy performance based on DOE commercial reference buildings and the California DEER prototype buildings. The prototype buildings represent seven building types across six vintages of constructions and 16 California climate zones. DEEP uses these prototypes to evaluate energy performance of about 100 energy conservation measures covering envelope, lighting, heating, ventilation, air-conditioning, plug-loads, and domestic hot water. DEEP consists the energy simulation results for individual retrofit measures as well as packages of measures to consider interactive effects between multiple measures. The large scale EnergyPlus simulations are being conducted on the super computers at the National Energy Research Scientific Computing Center of Lawrence Berkeley National Laboratory. The pre-simulation database is a part of an on-going project to develop a web-based retrofit toolkit for small and medium-sized commercial buildings in California, which provides real-time energy retrofit feedback by querying DEEP with recommended measures, estimated energy savings and financial payback period based on users’ decision criteria of maximizing energy savings, energy cost savings, carbon reduction, or payback of investment. The pre-simulated database and associated comprehensive measure analysis enhances the ability to performance assessments of retrofits to reduce energy use for small and medium buildings and business owners who typically do not have resources to conduct costly building energy audit. DEEP will be migrated into the DEnCity - DOE’s Energy City, which integrates large-scale energy data for multi-purpose, open, and dynamic database leveraging diverse source of existing simulation data.

Hoon Lee, Sang↗

Retrofit-ability: A supplementary metric to inform energy efficiency policies and programs

Building Energy Use Intensity (EUI) has been commonly used to facilitate policy makers and utilities to design energy efficacy programs and help building managers prioritize investment in building upgrades. Buildings with higher EUIs are usually chosen as better candidates for retrofit. Our study of nearly one hundred buildings in Seattle’s Building Tune Up Accelerator program and thousands of buildings in the Asset Score database reveals that EUI (after weather/location/use type normalization) alone is not the best indicator of a building’s potential to save energy, especially for those buildings in the mid-range (30-70 percentile EUI). In this paper, we introduce the concept of “retrofit-ability” — a building’s real potential to reduce its energy use cost-effectively — as a supplementary metric to inform energy efficiency policy and investment. Currently, such potential analyses are predicted for a building stock using prototypical building models or statistical data. However, typical buildings or general historical data may not sufficiently represent building configurations in a portfolio and predict their saving potentials. We utilized machine learning to investigate how key building characteristics (such as envelope attributes, HVAC type, location, use type, etc.) affect a building’s improvement potentials and developed a low-cost method to quantify such potentials for a portfolio of buildings. The supplementary perspective provided by “retrofit-ability” highlights which building assets correlate most with a building’s energy savings potential across region, building use type and more.

Wang, Na↗

AlphaBuilding - Synthetic Buildings Operation Dataset

This is a synthetic building operation dataset which includes HVAC, lighting, miscellaneous electric loads (MELs) system operating conditions, occupant counts, environmental parameters, end-use and whole-building energy consumptions at 10-minute intervals. The data is created with 1395 annual simulations using the U.S. DOE detailed medium-sized reference office building, and 30 years' historical weather data in three typical climates including Miami, San Francisco, and Chicago. Three energy efficiency levels of the building and systems are considered. Assumptions regarding occupant movements, occupants' diverse temperature preferences, lighting, and MELs are adopted to reflect realistic building operations. A semantic building metadata schema - BRICK, is used to store the building metadata. The dataset is saved in a 1.2 TB of compressed HDF5 file. This dataset can be used in various applications, including building energy and load shape benchmarking, energy model calibration, evaluation of occupant and weather variability and their influences on building performance, algorithm development and testing for thermal and energy load prediction, model predictive control, policy development for reinforcement learning based building controls.

AlphaBuilding↗

Long term occupancy estimation in a commercial space: an empirical study: poster abstract

Understanding occupancy patterns in a building is very useful to control HVAC systems for improving energy efficiency of the building and occupant comfort. There has been a very little attempt to understand long term occupancy patterns in a commercial space. In this work, we leverage depth sensors (Kinect for XBOX One) to collect occupancy count from an 11,000 square foot commercial space (Bosch office) for nine months. We analyze the collected data and describe key findings that provide deep insights about how a commercial space is used and serve as a guideline to formulate novel and efficient control strategies.

Liu, Kin Sum↗

Energy Efficiency and Conservation Block Grant (EECBG) - Better Buildings Neighborhood Program (Final Technical Report)

Austin Energy, a municipally-owned electric utility for the City of Austin, is a nationally recognized leader in energy conservation. With long-running, successful energy efficiency programs already in place in the single family and multifamily sectors, the Better Buildings grant program faced a unique operating environment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Verifying a Simplified Fuel Oil Flow Field Measurement Protocol

The Better Buildings program is a U.S. Department of Energy program funding energy efficiency retrofits in buildings nationwide. The program is in need of an inexpensive method for measuring fuel oil consumption that can be used in evaluating the impact that retrofits have in existing properties with oil heat. This project developed and verified a fuel oil flow field measurement protocol that is cost effective and can be performed with little training for use by the Better Buildings program as well as other programs and researchers.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Energy and Energy Cost Savings Analysis of the IECC for Commercial Buildings

The purpose of this analysis is to assess the relative energy and energy cost performance of commercial buildings designed to meet the requirements found in the commercial energy efficiency provisions of the International Energy Conservation Code (IECC). Section 304(b) of the Energy Conservation and Production Act (ECPA), as amended, requires the Secretary of Energy to make a determination each time a revised version of ASHRAE Standard 90.1 is published with respect to whether the revised standard would improve energy efficiency in commercial buildings. As many states have historically adopted the IECC for both residential and commercial buildings, PNNL has evaluated the impacts of the commercial provisions of the 2006, 2009, and 2012 editions of the IECC. PNNL also compared energy performance with corresponding editions of ANSI/ASHRAE/IES Standard 90.1 to help states and local jurisdictions make informed decisions regarding model code adoption.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Verifying a Simplified Fuel Oil Field Measurement Protocol

The Better Buildings program is a U.S. Department of Energy program funding energy efficiency retrofits in buildings nationwide. The program is in need of an inexpensive method for measuring fuel oil consumption that can be used in evaluating the impact that retrofits have in existing properties with oil heat. This project developed and verified a fuel oil flow field measurement protocol that is cost effective and can be performed with little training for use by the Better Buildings program as well as other programs and researchers.

02 PETROLEUM↗

CAD-based Energy & Cost Models Prove Affordable Net Zero Energy Performance for WonderWindows + 24" On-center Framing

Windows are thermally the “weakest link” in the building envelope. Increasing the thermal resistance of windows can make buildings more energy efficient and reduce the cost of electricity needed for conditioning the building. The proper design and placement of framing can also help to reduce the thermal bridging that occurs near the window frame area. This study investigates the energy performance of multi-pane acrylic windows fitting 24" on-center framing. Initial parametric analysis is done for a single zone accessory dwelling unit (ADU). Then, an energy model was developed for three types of wood-framed buildings: townhomes, stacked flats and hotels. A whole building energy simulation is performed for each of these building types in hot-humid Houston, mixed-humid New York, and cold-humid Minneapolis climates. The results show up to a 39% reduction in heating, ventilation, and air-conditioning (HVAC) related electricity consumption for the cold climate compared to the Base case which has window and wall properties based on ASHRAE standard 90.1 2019. In the hot climate, a modest increase in electricity consumption was seen due to an increase in cooling electricity demand. The ADU achieved Net Zero Energy performance in all 3 Climate Zones despite having the highest exterior surface area-to-floor area ratio: the ADU also had the highest PV kW to floor area ratio compared to the other multi-story building types. The townhomes, hotel and stacked flats respectively met 73, 52 and 57 % of electrical use in Houston, 71, 48 and 56 % in New York, and 63, 40 and 53 % in Minneapolis from energy produced by rooftop solar. If 400 W solar panels are used instead of 320 W panel used for energy simulation, it is estimated that in the townhomes, hotel and stacked flats rooftop solar can meet 91, 65 and 71 % of electrical use in Houston; 89, 60 and 70% in New York, and 79, 50 and 66 % in Minneapolis. A preliminary evaluation of cost shows that such superior performance can potentially be achieved at less first cost with this 24"on-center solution than conventional construction. All the building types at the three locations used for simulation had net energy use intensity under 20 kBtu/sf/year with 320 W solar panel and under 17 kBtu/sf/year with 400 W solar panel. Further tailoring of building envelope R-values and window solar heat gain to particular Climate Zone locations for each building type shows promise in reducing the HVAC electricity use that comprises almost half of building energy use.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗