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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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At least 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Cosmo Cassette: A Microfluidic Microgravity Microbial System For Synthetic Biology Unit Tests and Satellite Missions

Although methods in the design-build-test life cycle of the synthetic biology field have grown rapidly, the expansion has been non-uniform. The design and build stages in development have seen innovations in the form of biological CAD and more efficient means for building DNA, RNA, and other biological constructs. The testing phase of the cycle remains in need of innovation. Presented will be both a theoretical abstraction of biological measurement and a practical demonstration of a microfluidics-based platform for characterizing synthetic biological phenomena. Such a platform demonstrates a design of additive manufacturing (3D printing) for construction of a microbial fuel cell (MFC) to be used in experiments carried out in space. First, the biocompatibility of the polypropylene chassis will be demonstrated. The novel MFCs will be cheaper, and faster to make and iterate through designs. The novel design will contain a manifold switchingdistribution system and an integrated in-chip set of reagent reservoirs fabricated via 3D printing. The automated nature of the 3D printing yields itself to higher resolution switching valves and leads to smaller sized payloads, lower cost, reduced power and a standardized platform for synthetic biology unit tests on Earth and in space. It will be demonstrated that the application of unit testing in synthetic biology will lead to the automatic construction and validation of desired constructs. Unit testing methodologies offer benefits of preemptive problem identification, change of facility, simplicity of integration, ease of documentation, and separation of interface from implementation, and automated design.

Bioelectrochemical System↗
DOE OSTI2011

Building Technologies Program Key Activities

The Building Technologies Program (BTP) employs a balanced approach to making buildings more energy efficient. The three pillars of our program, research and development (R&D), market stimulation, and building and equipment standards, help meet our strategic vision.

key activities↗
DOE OSTI2023

System and method for characterization of air leakage in building using data from communicating thermostats and/or interval meters

Systems and methods for characterization of retrofit opportunities are described. Some embodiments are directed to methods for determining the air leakage rate of a building, and accordingly, for determining suitability of sealing of air leaks to improve the energy efficiency of a building. The methods may comprise computing, using at least one computing device disposed remote from a building and based at least in part on heating, ventilation and air conditioning (HVAC) runtime data associated with the building, one or more thermal characteristics of the building. The HVAC runtime data may be computed based on data received from a thermostat or a meter, such as an electric or a gas meter. To isolate the impact of air leakage, subsets of the HVAC runtime data at time intervals selected to have substantially the same conditions, but different wind speeds, may be computed.

Zeifman, Michael↗
DOE OSTI2014

ANSI/ASHRAE/IES Standard 90.1-2013 Determination of Energy Savings: Quantitative Analysis

This report provides the quantitative analysis to assess whether buildings constructed according to the requirements of ANSI/ASHRAE/IES Standard 90.1-2013 would result in improved energy efficiency in commercial buildings. The analysis considered each of the addenda to Standard 90.1-2010 that were included in Standard 90.1-2013.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Development, Monitoring, and Control of Fracture Thermal Energy Storage in Crystalline Rock Formations (DEMO-FTES) [Abstract]

Approximately half of global energy consumption is used for heating and cooling. Because fossil fuels are used to meet most of this demand, heating and cooling of buildings produces a large portion of global greenhouse gas (GHG) emissions. The proposed project seeks to demonstrate the feasibility of a seasonal thermal energy storage concept called fracture thermal energy storage (FTES), which has the potential to dramatically lower energy requirements for heating and cooling and improve the resilience of building energy systems. FTES is a technique for building a highly efficient heat exchanger by creating a carefully designed set of fractures in the ground below a building. This heat exchanger allows thermal energy to be stored over seasonal timeframes—for example, hot thermal energy that is easily captured in the summer or energy from waste heat sources—to meet heating needs during colder months. FTES offers a solution with a relatively small footprint and lower cost compared to currently operating aquifer thermal energy storage (ATES) systems and could be used in the many areas without aquifers suitable for ATES. If commercialized, FTES systems could exceed the 2.5 TWh of energy storage per year from the more than 2,800 ATES systems in operation worldwide, which range from 0.1 MW to 30 MW. The savings in CO2 emissions per year are also expected to match or exceed individual ATES projects, with the largest, a 30 MW system used to provide heating and cooling to the University of Technology in Eindhoven in the Netherlands, estimated to save 13,000 tons of CO2 emissions per year. FTES utilizes mature drilling and fracturing technology and therefore has the potential to be rapidly commercialized once demonstrated. The ability to construct and establish flow through an FTES heat exchanger has been demonstrated by a previous project and the potential for efficient, large-capacity energy storage has been shown using numerical models. However, no experimental validation of these numerical estimates of thermal energy storage has been made. The first crucial need to advance FTES technology is to identify the sensitivity of key metrics such as thermal energy storage and production rates, capacities, and efficiencies to design parameters such as the number of fractures, depth/temperature of fractures, size of fractures, and circulation rates. The second crucial need is experimental testing of achievable thermal performance with optimized system design parameters. The proposed scope of work seeks to systematically address these two critical needs through a highly complementary international collaboration spanning theory, laboratory, and mesoscale field evaluation. The proposed work plan calls for using dimensional analysis and existing state-of-the-art numerical simulators to design carefully scaled laboratory and 10-meter-scale field tests of the thermal efficiency of FTES. The existing advanced laboratory and intermediate-scale field testbeds that will be used for this project will allow for detailed monitoring of the system performance during the test and of how the performance changes across time and length scales. These results will determine the feasibility of full- scale FTES systems. If the thermal performance is consistent with model predictions, the results will provide a strong economic justification for rapid commercialization of FTES technology in a wide range of geographical areas.

25 ENERGY STORAGE↗
DOE OSTI2019

Ten questions on urban building energy modeling

Buildings in cities consume up to 70% of all primary energy. To achieve cities’ energy and climate goals, it is necessary to reduce energy use and associated greenhouse gas emissions in buildings through energy conservation and efficiency improvements. Computational tools empowered with rich urban datasets can model performance of buildings at the urban scale to provide quantitative insights for stakeholders and inform their decision making on urban energy planning, as well as building energy retrofits at scale, to achieve efficiency, sustainability, and resilience of urban buildings. Designing and operating urban buildings as a group (from a city block to a district to an entire city) rather than as single individuals requires simulation and optimization to account for interactions among buildings and between buildings and their surrounding urban environment, and for district energy systems serving multiple buildings with diverse thermal loads across space and time. When hundreds or more buildings are involved in typical urban building energy modeling (UBEM) to estimate annual energy demand, evaluate design or retrofit options, and quantify impacts of extreme weather events or climate change, it is crucial to integrate urban datasets and UBEM tools in a seamless automatic workflow with cloud or high-performance computing for users including urban planners, designers and researchers. This paper presents ten questions that highlight significant UBEM research and applications. The proposed answers in this work aim to stimulate discussion and provide insights into the current and future research on UBEM, and more importantly, to inspire new and important questions from young researchers in the field.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Selecting durable building envelope systems with machine learning assisted hygrothermal simulations database

Hygrothermal simulations provide insight into the energy performance and moisture durability of building envelope components under dynamic conditions. The inputs required for hygrothermal simulations are extensive, and carrying out simulations and analyses requires expert knowledge. An expert system, the Building Science Advisor (BSA), has been developed to predict the performance and select the energy-efficient and durable building envelope systems for different climates. The BSA consists of decision rules based on expert opinions and thousands of parametric simulation results for selected wall systems. The number of potential wall systems results in millions, too many to simulate all of them. We present how machine learning can help predict durability data, such as mold growth, while minimizing the number of simulations needed to run. The simulation results are used for training and validation of machine learning tools for predicting wall durability. We tested Artificial Neural Network (ANN) and Gradient Boosted Decision Trees (GBDT) for their applicability and model accuracy. Models developed with both methods showed adequate prediction performance (root mean square error of 0.195 and 0.209, respectively). Finally, we introduce how the information supports guidance for envelope design via an easy-to-use web-based tool that does not require the end-user to run hygrothermal simulations.

Salonvaara, Mikael↗
DOE OSTI2018

Residential Slab Component Calculations

Modern residential building energy codes provide a component tradeoff mechanism by which builders can trade reductions in the efficiency of some building components in trade for corresponding improvement in other components. One common tradeoff approach is based on maintaining a building "UA value," which represents the building envelope's overall thermal conductance. The building UA is the sum of individual component UA values, each of which is calculated as the product of the component's U-factor and area. Current codes, however, provide little guidance on including slab-on-grade components in the overall UA calculation. This brief provides information on calculating effective slab UA values and provides recommended text for building codes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Evaluating the Maturity of Cybersecurity Programs for Building Control Systems

The cyber-physical security threat to buildings is complex, non-linear, and rapidly evolving as operational and information technologies converge and connect buildings to cyberspace. Cyberattacks on buildings can exploit smart building controls and breach corporate networks, causing financial and reputational damage. This may result in the loss of sensitive building information or the disruption of, or damage to, the systems necessary for the safe and efficient operation of buildings. For the buildings and facility infrastructure, there is a need for a robust national cybersecurity strategy for buildings, guidance on the selection and implementation of appropriate cybersecurity controls for buildings, an approach to evaluate the maturity and adequacy of the cybersecurity programs. To provide an approach for evaluating the maturity of the cybersecurity programs for building control systems, the US Department of Energy’s widely used Cybersecurity Capability and Maturity Model (C2M2) has been adapted into a building control systems version. The revised model, the Buildings-C2M2 (B-C2M2) provides maturity level indicators for cybersecurity programmatic domains. A “B-C2M2 Lite” version allows facility managers and building control system engineers, or information technology personnel to perform rapid self-assessments of their cybersecurity program. Both tools have been pilot tested on several facilities. This paper outlines the concept of a maturity model, describes the B-C2M2 tools, presents results and observations from the pilot assessments, and lays out plans for future work.

Glantz, Clifford S.↗
DOE OSTI2017

Building America Case Study: Simple Retrofit High-Efficiency Natural Gas Water Heater Field Test, Minneapolis, Minnesota

High-performance water heaters are typically more time consuming and costly to install in retrofit applications, making high-performance water heaters difficult to justify economically. However, recent advancements in high-performance water heaters have targeted the retrofit market, simplifying installations and reducing costs. Four high-efficiency natural gas water heaters designed specifically for retrofit applications were installed in single-family homes along with detailed monitoring systems to characterize their savings potential, their installed efficiencies, and their ability to meet household demands.

Building America↗
DOE OSTI2014

Strengthening Retrofit Markets for Comprehensive Savings in Multifamily Buildings (Interim Final Report)

Energy efficiency is vitally important in Maine. Nearly 70% of Maine households rely on fuel oil as their primary energy source for home heating, a higher share than in any other state. Coupled with the state's long, cold winters, Maine's dependence on oil renders homeowners particularly vulnerable to fluctuating fuel costs. With $\$$4.5 million in seed funding from the Energy Department's Better Buildings Neighborhood Program, the Governor's Energy Office (GEO), through Efficiency Maine Trust (the Trust), is spurring Maine landlords to lower their monthly energy bills and improve comfort for their tenants during the state's cold winter months and increasingly warmer summers. Maine's aging multifamily housing stock can be expensive to heat and costly to maintain. It is not unusual to find buildings with little or no insulation, drafty windows, and significant air leaks, making them ideal candidates for energy efficiency upgrades. Maine modeled its Multifamily Efficiency Program (MEP) after the state's highly successful Home Energy Savings Program (HESP) for single-family homes. HESP provided cash incentives and financing opportunities to owners of one-to four-unit structures, which resulted in thousands of energy assessments and whole-house energy upgrades in 225 communities. Maine's new MEP multifamily energy efficiency upgrade and weatherization initiative focuses on small to medium-sized (i.e., five to 20 units) apartment buildings. The program's energy efficiency upgrades will provide at least 20% energy savings for each upgraded multifamily unit. The Trust’s MEP relies on a network of approved program partners who help move projects through the pipeline from assessment to upgrade. MEP has two components: benchmarking and development of an Energy Reduction Plan (ERP). Using the ENERGY STAR® Portfolio Manager benchmarking tool, MEP provides an assessment of current energy usage in the building, establishes a baseline for future energy efficiency improvements, and enables tracking and monitoring of future energy usage at the building— all at no cost to the building owner. The ERP is developed by a program partner using either the Trust’s approved modeling or prescriptive tools; it provides detailed information about the current energy related conditions in the building and recommends energy efficiency, health, and safety improvements. The Trust's delivery contractor provides quality assurance and controls throughout the process. Through this effort, MEP's goal is to establish a self-sustaining, market-driven program, demonstrating the value of energy efficiency to other building owners. The increasing value of properties across the state will help incentivize these owners to continue upgrades after the grant period has ended. Targeting urban areas in Maine with dense clusters of multifamily units—such as Portland, Lewiston- Auburn, Bangor, and Augusta—MEP engaged a variety of stakeholder groups early on to design its multifamily program. Through direct emails and its website, program officials invited lending institutions, building professionals, engineering firms, equipment distributors, and local property owners associations to attend open meetings around the state to learn about the goals of the multifamily program and to help define its parameters. These meetings helped program administrators understand the diversity of the customer base: some owners are individuals with a single building, while other owners are groups of people or management companies with an entire portfolio of multifamily buildings. The diversity of the customer base notwithstanding, owners see MEP as an opportunity to make gains in their respective properties. Consistently high turnouts at stakeholder meetings fueled greater customer interest as awareness of the program spread through word of mouth. The program also gained traction by utilizing the program partner networks and building on the legacy of the Trust’s successful HESP for single-family residences. MEP offers significant incentives for building owners to participate in the upgrade program. Wholebuilding benchmarking services are available to most multifamily housing buildings free of charge. The service provides the building owner with an assessment of the building's current energy efficiency as compared to other multifamily buildings on a national scale, establishes a baseline to measure future improvements, and enables owners to track monthly energy consumption using the ENERGY STAR Portfolio Manager. Once the benchmarking process is complete, the program links building owners with approved program partners (e.g., energy professionals, home performance contractors) to identify and implement specific energy-saving opportunities in the building. Program partners can also provide project quotes with estimated financing incentives and payback period calculations that enable building owners to make informed decisions. What's more, the Trust provides two financial incentives for successful completion of program milestones. The first is a per-unit incentive for completion of an approved ERP (i.e., $\$$100 per unit if a prescriptive path is followed, and $\$$200 per unit for a modeled ERP). Upon final inspection of the installed project scope of work, an incentive of $\$$1,400 per unit or 50% of installed cost—whichever is less—is paid. The Trust originally established a $\$$1 million loan-loss reserve fund (LLRF) to further enhance financing opportunities for qualified multifamily building owners. This funding mechanism was designed to connect building owners with lenders that retain the mortgages for their properties and encourages the lenders to offer financing for energy efficiency improvements. However, there has been no interest in the LLRF and therefore the LLRF has been reduced. Ultimately, MEP plans to build an online tool for building owners to assess opportunities to make upgrades in their multifamily units. The tool will include a performance rating system to provide a way for building owners to more easily understand energy use in their building, and how it could be improved with energy efficiency upgrades. Prospective tenants will also be able to use the rating system to make informed decisions about where to rent. Furthermore, the rating can be incorporated into real estate listings as a way for prospective home buyers and the real estate financial community to evaluate a home's operating costs. The Trust’s MEP has identified the state's most experienced energy professionals, vendors, suppliers, and contractors that install energy efficiency equipment in the multifamily sector to be qualified program partners. To be eligible for partnership, energy assessment professionals and contractors are required to have demonstrated experience in the multifamily sector and hold associated professional certifications, such as Building Operator Certification (BOC), Certified Energy Manager (CEM), Professional Engineer (PE), or Building Performance Institute (BPI) Multifamily Building Analyst. Widespread program interest has enabled the Trust to redirect funds that might otherwise be needed for program promotion to building capacity through contractor training. In addition to boosting professional training and certification opportunities, MEP teaches its partners how to market the multifamily program to prospective multifamily homeowners.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

OpenEIS Algorithms

The OpenEIS Algorithm package seeks to provide a low-risk path for building owners, service providers and managers to explore analytical methods for improving building control and operational efficiency. Users of this software can analyze building data, and learn how commercial implementations would provide long-term value. The code also serves as a reference implementation for developers who wish to adapt the algorithms for use in commercial tools or service offerings.

Granderon, Jessica↗
DOE OSTI2024

Equitable Energy Metrics for Integration into Building Performance Standard Tracking Platforms: Preprint

Building Performance Standards (BPS) are being adopted globally and in the United States of America, where 14 different states and jurisdictions have a policy in place and many others are under development (Department of Energy (DOE) 2023). Accurate and equitable data sources are essential to make informed decisions about focusing investment on upgrading buildings to meet jurisdictional goals. There have been multiple new tools developed related to Energy Equity and Environmental Justice (EEEJ) and the resulting datasets need to be integrated into large building port-folios for quick access and better scalability. Integrating EEEJ data in a user-friendly format can help decision makers more quickly assess impacts and analyze the multitude of potentially significant metrics for which there is not yet consensus. In the U.S. and Canada, many BPS ordinances rely primarily on ENERGY STAR Portfolio Manager (ESPM) to capture building characteristics and energy and water consumption data. These datasets can then be imported into city-specific building tracking tools like the Standard Energy Efficiency Data Platform (SEED). Crucially, BPS decision makers require an efficient means of identifying buildings in priority communities to effectively allocate resources and funding. This process must integrate seamlessly with existing jurisdictional toolsets for optimal utility. This paper will demonstrate, for the case of Washington D.C.'s (the District) data, a workflow that provides actionable data for building upgrade investment prioritization in disadvantaged communities.

BPS↗
DOE OSTI2014

Data and Analytics to Inform Energy Retrofit of High Performance Buildings

Buildings consume more than one-third of the world?s primary energy. Reducing energy use in buildings with energy efficient technologies is feasible and also driven by energy policies such as energy benchmarking, disclosure, rating, and labeling in both the developed and developing countries. Current energy retrofits focus on the existing building stocks, especially older buildings, but the growing number of new high performance buildings built around the world raises a question that how these buildings perform and whether there are retrofit opportunities to further reduce their energy use. This is a new and unique problem for the building industry. Traditional energy audit or analysis methods are inadequate to look deep into the energy use of the high performance buildings. This study aims to tackle this problem with a new holistic approach powered by building performance data and analytics. First, three types of measured data are introduced, including the time series energy use, building systems operating conditions, and indoor and outdoor environmental parameters. An energy data model based on the ISO Standard 12655 is used to represent the energy use in buildings in a three-level hierarchy. Secondly, a suite of analytics were proposed to analyze energy use and to identify retrofit measures for high performance buildings. The data-driven analytics are based on monitored data at short time intervals, and cover three levels of analysis ? energy profiling, benchmarking and diagnostics. Thirdly, the analytics were applied to a high performance building in California to analyze its energy use and identify retrofit opportunities, including: (1) analyzing patterns of major energy end-use categories at various time scales, (2) benchmarking the whole building total energy use as well as major end-uses against its peers, (3) benchmarking the power usage effectiveness for the data center, which is the largest electricity consumer in this building, and (4) diagnosing HVAC equipment using detailed time-series operating data. Finally, a few energy efficiency measures were identified for retrofit, and their energy savings were estimated to be 20percent of the whole-building electricity consumption. Based on the analyses, the building manager took a few steps to improve the operation of fans, chillers, and data centers, which will lead to actual energy savings. This study demonstrated that there are energy retrofit opportunities for high performance buildings and detailed measured building performance data and analytics can help identify and estimate energy savings and to inform the decision making during the retrofit process. Challenges of data collection and analytics were also discussed to shape best practice of retrofitting high performance buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Building America Case Study: Simple Retrofit High-Efficiency Natural Gas Water Heater Field Test, Minneapolis, Minnesota

High performance water heaters are typically more time consuming and costly to install in retrofit applications, making high performance water heaters difficult to justify economically. However, recent advancements in high performance water heaters have targeted the retrofit market, simplifying installations and reducing costs. Four high efficiency natural gas water heaters designed specifically for retrofit applications were installed in single-family homes along with detailed monitoring systems to characterize their savings potential, their installed efficiencies, and their ability to meet household demands. The water heaters tested for this project were designed to improve the cost-effectiveness and increase market penetration of high efficiency water heaters in the residential retrofit market. The retrofit high efficiency water heaters achieved their goal of reducing costs, maintaining savings potential and installed efficiency of other high efficiency water heaters, and meeting the necessary capacity in order to improve cost-effectiveness. However, the improvements were not sufficient to achieve simple paybacks of less than ten years for the incremental cost compared to a minimum efficiency heater. Significant changes would be necessary to reduce the simple payback to six years or less. Annual energy savings in the range of $200 would also reduce paybacks to less than six years. These energy savings would require either significantly higher fuel costs (greater than $1.50 per therm) or very high usage (around 120 gallons per day). For current incremental costs, the water heater efficiency would need to be similar to that of a heat pump water heater to deliver a six year payback.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Emerging Technologies: Integrating with the Power Grid of Tomorrow

Traditional interactions between the built environment and the electric utility industry are changing rapidly. Rather than a one-way flow of electricity where utilities produce and transmit the electricity that buildings then consume, buildings are becoming efficient energy consumers that can dynamically adjust loads to ensure grid-provided energy is used effectively. Buildings are transitioning to now be at the intersection of forecasting loads and demand response, forecasting and control of output from distributed generation and renewable energy systems, and the optimal dispatch of energy storage. Because residential and commercial buildings consume 74.7% of the electricity generated in the United States, grid-integrated buildings represent an important solution to addressing challenges facing the power sector. In addition to the electric power grid, buildings will be increasingly interactive with water, transportation, and telecommunications networks, and will also more strongly affect surrounding buildings and other civic infrastructure.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Cost-Benefit Analysis For Indonesia Building Sector: Whole-Building Cooling Solutions

The Net Zero World (NZW) Initiative Collaborative Work Program with the Government of Indonesia (GoI) includes technical assistance and investment mobilization facilitation to accelerate deployment of energy efficiency technologies and solutions for the building sector. A February 2023 U.S.–Indonesia Joint Workshop on Decarbonizing the Building Sector yielded a NZW Indonesia Building Decarbonization Working Group (NZW IBDWG) with four sub-working groups (SWG): SWG-A National Center, SWG-B Capacity Building, SWG-C Investment and Financing, and SWG-D Pilot Projects. Technical analysis of whole-building cooling solutions for tropical climates of Indonesia was conducted by SWG-A to quantify energy savings, carbon dioxide reductions, and comfort improvements offered by 12 passive or low-energy cooling strategies: ceiling fans with and without thermostat setbacks; cool roofs; cool walls; exterior awnings; exterior shades; interior shades; insulated roofs; insulated walls; low-e windows; solar window films; and natural ventilation. Leveraging the results from SWG-A, cost-benefit analysis (CBA) was conducted by SWG-C to assess the consumer and national costs and impacts associated with these 12 cooling solutions. The evaluation involved estimating life-cycle costs (LCC), payback period (PBP), net present values (NPV), annual electricity burden change for low-income households, and reduced national annual power-sector generation demand by 2030, 2040, 2050, and 2060. This evaluation can help guide Indonesia’s Just Energy Transition Partnership (JETP) investments in policies and programs to advance research, development, deployment, and commercial adoption (RDDCA) of efficient residential building sector cooling technologies and solutions in Indonesia. Four key energy conservation measures (ECM) have been identified to reduce air-conditioning (AC) energy demand in single-family housing in Indonesia: ceiling fan with temperature setback (to 28.1 °Celcius from 25 °C); insulated walls; insulated roof; and cool roof. This study found that low-income households with AC installations in Indonesia currently face a high energy cost burden of approximately 10%. However, by implementing a ceiling fan with temperature setback, this burden could decrease to 2.5% today and further reduce to 1.3% by the year 2060. The PBP for a ceiling fan with temperature setback is one year, indicating one of the lowest LCC and best NPV. In the planned upcoming phase of CBA, a series of building cooling improvement scenarios can be further defined, incorporating more than one ECM in combination with socio-economic factors evaluated in the initial CBA phase. Additionally, the analysis of ECM effects in multifamily housing can be expanded. This broader national analysis aims to encompass a holistic and comprehensive system-level perspective, including factors such as avoided power sector infrastructure investments, domestic job creation, domestic manufacturing job creation, and gross domestic product (GDP) growth.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Deep-Learning-Based Multi-Timescale Load Forecasting in Buildings: Opportunities and Challenges from Research to Deployment

Electricity load forecasting for buildings and campuses is becoming increasingly important as the penetration of distributed energy resources (DERs) grows. Efficient operation and dispatch of DERs require reasonably accurate predictions of future energy consumption in order to conduct near-real-time optimized dispatch of on-site generation and storage assets. Electric utilities have traditionally performed load forecasting for load pockets spanning large geographic areas, and therefore, forecasting has not been a common practice by buildings and campus operators. Given the growing trends of research and prototyping in the grid-interactive efficient buildings domain, characteristics beyond simple algorithm forecast accuracy are important in determining the algorithm's true utility for smart buildings. Other characteristics include the overall design of the deployed architecture and the operational efficiency of the forecasting system. In this work, we present a deep-learning-based load forecasting system that predicts the building load at 1-hour intervals for 18 hours in the future. We also discuss challenges associated with the real-time deployment of such systems as well as the research opportunities presented by a fully functional forecasting system that has been developed within the National Renewable Energy Laboratory's Intelligent Campus program.

building load forecasting↗