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At least 1,027 records · Page 57

All sources NASA NTRS DOE OSTI

DOE OSTI2019

Curated Modeled Fault Data Set

The curated fault model simulation data set consists of tagged and fully-described time series representing simulated faults for the AFDD test building (ORNLs Flexible Research Platform (FRP)), including baseline performance, faulty performance, and corresponding energy impact. A total of 26 fault models are considered for 99 simulation scenarios with various fault intensity levels. Additional Contacts: Principal investigator: Matt Leach Matt.Leach@nrel.gov Simulation performer: Janghyun Kim Janghyun.Kim@nrel.gov

AFDD↗

DOE OSTI2024

Empowering Rural Electrification in Honduras: An Integrated Assessment of PV/BESS and Productive Uses of Electricity in Gracias a Dios

Honduras faces significant challenges in its energy sector, particularly in rural areas where access to reliable and affordable electricity remains limited. The flagship rural electrification initiative for Honduras Secretary of Energy (SEN) is the Politica de Acceso Universal a la Electricidad (PAUEH - Universal Electricity Access Policy), a key solution for addressing this energy poverty is the deployment of more than 1700 distributed solar and hybrid mini-grid solutions. In late 2023 as a first step towards supporting SEN's electrification efforts, the National Renewable Energy Laboratory (NREL) developed a literature review of SEN electrification policy documents and conducted a series of technical capacity-building workshops with SEN and other energy sector stakeholders in Honduras focused on using NREL's open-source REopt tool to conduct techno-economic assessments and develop least-cost optimizations for potential solar + storage mini-grid systems. Building on some initial capacity building on mini-grid modeling, the National Renewable Energy Laboratory (NREL) worked with SEN to develop a detailed techno-economic assessment for electrifying two schools, a healthcare clinic, and a hospital in a hypothetical community within the department of Gracias a Dios. The analysis also evaluates the business case for cold storage productive use of energy (PUE) applications for the fisheries value chain and how the incorporation of these PUE loads potentially impacts both the viability of the PV+BESS solutions as well as local economic development. By assessing the potential for deployment of integrated PV/BESS systems to both support critical community services like education and healthcare, as well as potential for downstream enterprise and economic development, this analysis represents a first step that can help to inform specific strategies for development of pilot PV+BESS projects aligned with national priorities and sector level planning under PAUEH.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Fortalecimiento de la Electrificación Rural en Honduras: Una Evaluación Integrada de PV+BESS y Usos Productivos de la Electricidad en Gracias a Dios, Honduras [Empowering Rural Electrification in Honduras: An Integrated Assessment of PV/BESS and Productive Uses of Electricity in Gracias a Dios] (Spanish Translation)

14 SOLAR ENERGY↗

DOE OSTI2020

Modeling the Interaction Between Energy Efficiency and Demand Response on Regional Grid Scales: Preprint

With increasing penetration of intermittent renewable generation at grid and distributed scales, flexible building loads can provide significant system value and support the evolving needs of the grid. The growing value of load flexibility may complicate the traditional separation between energy efficiency (EE) and demand response (DR). EE measures may compete in some cases with a building’s DR capabilities but complement one another in other cases. EE can also increase or decrease the need for DR at the system level and change the availability of DR to meet system needs. In this study we present a bottom-up approach to modeling interactive effects between EE and DR in buildings within two regions of the US electricity grid. From a library of building simulation models for different buildings and climates, we synthesize system-level demand profiles and the impacts of potential future EE portfolios. Coupling the underlying building models with a database of DR-enabling technologies, we then compute the quantity of DR that can be delivered in each scenario. The results show that EE and DR interactions are largely driven by the timing of EE savings that are measure-specific and the coincidence with system peak demand that is region-specific. We also find that perspective of the impacts matters – for instance that some EE measures reduce the system need for DR but also reduce the DR potential. Our results imply that utility EE and DR programs developed without considering interactive effects may lead to increased grid-management challenges over the long term.

buildings↗

DOE OSTI2019

Net-zero energy building design and life-cycle cost analysis with air-source variable refrigerant flow and distributed photovoltaic systems

Net-zero energy building (NZEB) design has been gaining widespread acceptance as a major driver to reach feasible long-term goals of energy reductions in a building sector for the coming decades. Accordingly, net-zero energy targets for commercial buildings have been specified by federal and/or local government agencies in U.S. Although moving toward NZEB goals has technically feasible long-term advantages, economic issues are one of primarily concerns by building owners and designers for the application of advanced building technologies in NZEB design of their retrofit or new building construction. However, the lack of life cycle cost (LCC) data has still hindered reliable understanding of adopting NZEB design by building owners in a cost-effective manner. In response to this gap, this study conducts life-cycle cost analysis (LCCA) of NZEB design with an energy-efficient heating, ventilation, and air conditioning (HVAC) system and a solar power generation system. Here, to enable NZEB design, an air-source VRF heat pump (HP) type system is considered for energy-efficient HVAC equipment in an office building model with a grid-tied photovoltaic (PV) system. Results reveal that the LCC of NZEBs varies primarily due to a combined effect of annual site EUIs, on-site power generation, and cost-items of each location in U.S. climates. Some hot and mild climate zones in the U.S. represent that LCC values of NZEBs are considerably lower. In contrast, some other cold zones result in unattractive LCC values for NZEBs, caused by a combined effect of relatively lower potential of on-site PV electricity generation and city cost indices. Yet, with subsidized financing by the federal government for PV installation costs, LCC values of NZEBs become significantly attractive in most climate locations.

42 ENGINEERING↗

DOE OSTI2016

Airside HVAC BESTEST. Adaptation of ASHRAE RP 865 Airside HVAC Equipment Modeling Test Cases for ASHRAE Standard 140. Volume 1, Cases AE101-AE445

This report documents a set of diagnostic analytical verification cases for testing the ability of whole building simulation software to model the air distribution side of typical heating, ventilating and air conditioning (HVAC) equipment. These cases complement the unitary equipment cases included in American National Standards Institute (ANSI)/American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE) Standard 140, Standard Method of Test for the Evaluation of Building Energy Analysis Computer Programs, which test the ability to model the heat-transfer fluid side of HVAC equipment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Data-driven search for promising intercalating ions and layered materials for metal-ion batteries

The rise in demand for lithium-ion batteries has led to a large-scale search for electrode materials and intercalating ion species to meet the demands of next-generation energy technologies. Recent efforts largely focus on searching for cathodes that can accommodate large amounts of intercalating ions, but similar work on anodes is relatively limited. This study utilizes machine learning methods to find alternative two-dimensional (2D) materials and intercalating ions beyond Li for metal-ion batteries with high-power efficiencies. The approach first uses density functional theory (DFT) calculations to estimate the theoretical capacities and voltages of various metal ions on 2D materials. The DFT-generated data also provide insights into the local structural accommodation upon ion intercalation on various 2D materials. Significant changes to the lattice can result in irreversible changes to the bonding environments in the anode material, resulting in poor cycling stability. Next, this study develops a binding energy and structural accommodation-based classification model to screen anode materials for next-generation batteries. The classification model selects intercalating ions and 2D material pairs suitable for batteries based on the calculated voltage and volumetric changes in the 2D material upon intercalation. Finally, this study builds a regression model to accurately predict the binding energies of the various intercalating ions on 2D materials. The approach highlights the importance of different elemental and structural features for classification and regression tasks. In conclusion, the insights gained from this study on the role of involved features, such as electronegativities of the constituent ions and the presence of unfilled electronic levels, will help to streamline further studies towards the search for future layered battery materials.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Modeling electric load and water consumption impacts from an integrated thermal energy and rainwater storage system for residential buildings in Texas

Not Available

Upshaw, Charles R. (ORCID:0000000154735000)↗

DOE OSTI2019

A Method for Integrating an UBEM with GIS for Spatiotemporal Visualization and Analysis

Leveraging Geographic Information Systems (GIS) for spatiotemporal visualization and analysis of simulated UBEM datasets and real-world data simultaneously can assist in identifying opportunities, as well as potential barriers, to energy efficient and climate adaptation strategies. However, current GIS-based models that support interactive exploration of adaptation strategies and future scenarios are scarce and do not easily incorporate building energy use data for visual analysis over time. This paper describes a workflow to integrate simulated building energy consumption data associated with variable energy efficiency scenarios within a GIS platform for interactive spatiotemporal visualization to support climate adaptation decision-making. The contribution of the work presented is in the ability to selectively view and analyze simulated building energy performance data layered with other real-world geospatial data through an automated feedback loop between an UBEM and ArcGIS. An interactive interface is designed in ArcGIS to enable users to explore building performance scenarios spatially and over time. Using a downtown neighborhood in Syracuse, New York, USA, as a case study, preliminary results demonstrate how the workflow provides insight into existing energy use issues and potential for implementing strategies such as energy load shifting or building retrofits. A discussion includes opportunities as well as challenges to the workflow in facilitating understanding of urban energy model outputs by multiple stakeholders in evaluating potential energy efficient strategies.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗

DOE OSTI2023

BuildingsBench: A Benchmark for Universal Building Load Forecasting [SWR-23-51]

The residential and commercial building stock in the United States is responsible for a significant percentage of energy consumption and greenhouse gas emissions. Electrification of end-uses, as well as decarbonizing the electrical grid through renewable energy sources such as solar and wind, constitutes the pathway to zero-emission buildings. Forecasting day-ahead building energy consumption is an integral part of this solution. Currently, specialized forecasting models are hand-made for each individual building, which is time-consuming, expensive, and leads to duplicated efforts. BuildingsBench is a Python software framework for training and comparing generalized machine learning models for universal building load forecasting. This challenge tasks a single foundational model to generalize its forecasts for a wide variety of buildings, across geographic regions, building types, weather patterns, and more. This software provide code for pre-training such models and subsequently evaluating their performance on a suite of hundreds of diverse real and synthetic buildings. BuildingsBench is a platform for: - Large-scale pretraining with the synthetic Buildings-900K dataset for short-term load forecasting (STLF). Buildings-900K is statistically representative of the entire U.S. building stock and is extracted from the NREL End-Use Load Profiles database. - Benchmarking on two tasks evaluating generalization: zero-shot STLF and transfer learning for STLF. We provide an index-based PyTorch Dataset for large-scale pretraining, easy data loading for multiple real building energy consumption datasets as PyTorch Tensors or Pandas DataFrames, simple (persistence) to advanced (transformer) baselines, metrics management, and more.

Emami, Patrick↗

DOE OSTI2015

Development of high-fidelity models for liquid fuel spray atomization and mixing processes in transportation and energy systems

Significant inadequacies of current models for multiphase flows present a major barrier to rapid development of advanced high-efficiency low-emissions combustion devices. Liquid spray atomization processes largely determine fuel-air mixture formation, which subsequently govern combustion and controls performance, emissions, and durability of a device. The current study presents a fundamentally-consistent framework to model the effects of breakup processes, liquid drop deformations, and internal flow dynamics on mass, momentum, and energy exchange functions. This framework builds on the Taylor Analogy Breakup (TAB) model which naturally quantifies local drop deformation dynamics. Real-fluid multicomponent thermodynamic property modeling and Gradient Theory simulations facilitate accurate calculations of molecular two-phase interface exchange functions, surface tensions forces, drop oscillations, and breakup processes. The analysis establishes that these drop dynamics, along with finite liquid viscosity effects, significantly alter gas-liquid exchange functions. The study quantifies these effects for the resulting drag coefficients of liquid drops and demonstrates significant deviations from the classic dynamic drag model, which is widely applied in modern simulations performed in academia and industry. This work also quantifies effects, which originate from gas-liquid coupling dynamics, on evaporation and heating rates. The analysis establishes that the consideration of these coupling dynamics modify mass and energy transfer rates even more significantly than the corresponding drag forces from momentum exchange. This physical complexity, however, is largely neglected in modern studies from academia and industry. A new set of equations is presented to improve the modeling of drop breakup processes to address the current shortcomings in the prediction of resulting drops proper- ties over the full range of relevant breakup conditions. The framework is based on a refined energy balance equation which explicitly enforces drop momentum conservation during the breakup process. The introduced modeling framework is entirely derived from conservation equations for mass, momentum, and energy and does not, as a consequence, introduce new modeling constants. The significance of the developed modeling advances to fuel injection processes is demonstrated using Large Eddy Simulation (LES) with a Lagrangian-Eulerian modeling approach.

42 ENGINEERING↗

DOE OSTI2017

Building America Case Study: Multifamily Central Heat Pump Water Heaters, Davis, California

Although heat pump water heaters (HPWHs) have gained significant attention in recent years as a high efficiency electric water heating solution for single family homes, central HPWHs for commercial or multi-family applications are not as well documented in terms of measured performance and cost effectiveness. To evaluate this technology, the Alliance for Residential Building Innovation team monitored the performance of a 10.5 ton central HPWH installed on a student apartment building at the West Village Zero Net Energy Community in Davis, California. Monitoring data collected over a 16-month period were then used to validate a TRNSYS simulation model. The TRNSYS model was then used to project performance in different climates using local electric rates. Results of the study indicate that after some initial commissioning issues, the HPWH operated reliably with an annual average efficiency of 2.12 (Coefficient of Performance). The observed efficiency was lower than the unit's rated efficiency, primarily due to the fact that the system rarely operated under steady-state conditions. Changes in the system configuration, storage tank sizing, and control settings would likely improve the observed field efficiency. Modeling results suggest significant energy savings relative to electric storage water heating systems (typical annual efficiencies around 0.90) providing for typical simple paybacks of six to ten years without any incentives. The economics versus gas water heating are currently much more challenging given the current low natural gas prices in much of the country. Increased market size for this technology would benefit cost effectiveness and spur greater technology innovation.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2019

Equation-based object-oriented modeling and simulation for data center cooling: A case study

© 2019 Elsevier B.V. Data center cooling accounts for about 1% of electricity usage in the United States. Computer models are pivotal in designing and operating energy-efficient cooling systems. Compared to conventional building performance simulation programs, the equation-based object-oriented modeling language Modelica is an emerging approach that can enable fast prototyping and dynamic simulation of cooling systems. In this case study, we first modeled the cooling and control systems of an actual data center located in Massachusetts using the open-source Modelica Buildings library, and then calibrated a baseline model based on measurement data. The simulation of the baseline model identified several operation-related issues in the cooling and control systems, such as degraded cooling coils, improper dead band in control settings, and simultaneous cooling and heating in air handlers. Afterwards, we used a sequential search technique as well as an optimization scheme to investigate the energy saving potentials for different energy efficiency measures aiming to address the abovementioned issues. Simulation results show potential energy savings up to 24% by resolving identified control-related issues and optimizing the supply air temperature.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2016

Model-based optimal design of active cool thermal energy storage for maximal life-cycle cost saving from demand management in commercial buildings

This article provides a method in comprehensive evaluation of cost-saving potential of active cool thermal energy storage (CTES) integrated with HVAC system for demand management in non-residential building. The active storage is beneficial by shifting peak demand for peak load management (PLM) as well as providing longer duration and larger capacity of demand response (DR). In this research, a model-based optimal design method using genetic algorithm is developed to optimize the capacity of active CTES aiming for maximizing the life-cycle cost saving concerning capital cost associated with storage capacity as well as incentives from both fast DR and PLM. In the method, the active CTES operates under a fast DR control strategy during DR events while under the storage-priority operation mode to shift peak demand during normal days. The optimal storage capacities, maximum annual net cost saving and corresponding power reduction set-points during DR event are obtained by using the proposed optimal design method. Lastly, this research provides guidance in comprehensive evaluation of cost-saving potential of CTES integrated with HVAC system for building demand management including both fast DR and PLM.

25 ENERGY STORAGE↗

DOE OSTI2024

Review of data-driven models for quantifying load shed by non-residential buildings in the United States

Shifting and shedding power demand in buildings can be cost-effective techniques for grids to function reliably and for end users to earn compensation. Grid operators reimburse customers in proportion to the quantity of load shed. Simple data-driven methods are used to quantify this shed, which is the difference between a measured load during the event and modeled "baseline" that would have occurred in absence of the event. These methods have evolved over the years and in many cases have been integrated with building physics, to make them a hybrid between physics based and empirical models. However, there is no comprehensive analysis that provides guidance to building operators, grid operators and researchers in selecting appropriate models based on their specific needs and available data. Here, this work aims to fill this gap by critically assessing the performance of baseline models put forward from the year 2000 through 2023. The literature reviewed includes reports generated by grid operators, reports from national laboratories and academic journal articles. The work outlines modeling features like the inputs, training period, estimation method, adjustments to fine tune the predictions and metrics to evaluate the performance. A comprehensive list of 50 models has been provided. For each model, the study explores the applicability of the model to weather sensitive buildings, variability in the building profile, timing of the event, and whether the building reduces energy consumption before an event. The work identifies the situations in which a particular model works and draws lessons based on evidence of performance. Finally, recommendations to aid in model selection are given.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2013

Best Practices Guide for High-Performance Indian Office Buildings

This document provides best practice guidance and energy- efficiency recommendations for the design, construction, and operation of high-performance office buildings in India. Through a discussion of learnings from exemplary projects and inputs from experts, it provides recommendations that can potentially help achieve (1) enhanced working environments, (2) economic construction/faster payback, (3) reduced operating costs, and (4) reduced greenhouse gas (GHG) emissions. It also provides ambitious (but achievable) energy performance benchmarks, both as adopted targets during building modeling (design phase) and during measurement and verification (operations phase). These benchmarks have been derived from a set of representative best-in-class office buildings in India. The best practices strategies presented in this guide would ideally help in delivering high-performance in terms of a triad—of energy efficiency, cost efficiency, and occupant comfort and well-being. These best practices strategies and metrics should be normalized—that is, corrected to account for building characteristics, diversity of operations, weather, and materials and construction methods.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2013

Crowder College MARET Center (Final Scientific Technical Report)

Following decades of success in solar energy projects, the Missouri Legislature designated Crowder College in 1992 as the State's renewable energy education center. The resulting Missouri Alternative and Renewable Energy Technology (MARET) Center is recognized internationally for its contributions to the energy field. The mission of the MARET Center is to expand renewable energy throughout the region with education, applied research, and economic development. Educational programs include certification and transfer degrees encompassing green construction, solar thermal energy, solar electricity, and wind. The MARET Center also assists in new product development and other business support services in renewable energy. The Missouri Alternative and Renewable Energy Technology (MARET) Center at Crowder College hopes to eventually develop a 27,500 ft 2 facility as a living laboratory to support solar and other renewable and sustainable energy development through professional degrees, new product development and commercialization, renewable energy business incubation, and consumer education. The primary objective of the current project was to complete Stage One of this building, with solar, wind, and geothermal technologies installed to power its 9,216 ft 2 office, classroom, and research spaces. This MARET Center includes a modular roof structure that permits both solar module mounting and daylighting, PV/thermal hybrid modules pioneered in Crowder Solar Decathlon homes, modular electrical management subsystems; and modular delivery systems for heating and cooling the structure. The MARET Facility will operate as a Net Positive energy building, consistently producing surplus energy for distributed generation on the utility grid. The modular design of the energy systems within the building is to serve as a scalable and repeatable model for a wide variety of building applications and climate zones. As a living laboratory of renewable energy, exploring and validating new applications of solar and other renewable technologies, the MARET Facility will house a wide variety of programs which will advance implementation of renewable energy throughout the region. These program goals include; Curriculum in renewable energy for pre-engineering transfer programs; Certification and degree programs for technical degrees for Energy Efficiency, Wind, Photovoltaic and Solar Thermal professionals; Short courses and workshops for building management and design professionals; Public education and demonstration projects in renewable energy through conferences and K-12 educational outreach; Technical degree offering in building construction incorporating “best practices” for energy efficiency and renewables; and Business incubators for new renewable energy businesses and new product development. The new MARET facility will support the mission of the US Department of Energy (DOE) Solar Program, “to improve America’s security, environmental quality, and economic prosperity through public-private partnerships that bring reliable and affordable solar energy technologies to the marketplace,” through a variety of educational and business assistance programs. Further, technical innovations planned for the MARET facility and its applied research activities will advance the Solar Program strategic goals to “reduce the cost of solar energy to the point it becomes competitive in relevant energy markets (e.g., buildings, power plants) and for solar technology to enable a sustainable solar industry.” Overarching Goals relative to program needs, future expansion, flexibility, quality of materials, and construction and operational costs:; Experimental: The structure and systems of the building operate as an educational resource. The systems are meant to be a source for data collection and study for building users and instructors; Educational: Part of the evolution of this building and its ongoing goals is to use the building as an educational tool, one where new ideas developed in the world and especially at Crowder can be tested further as part of MARET's curriculum; LEED Platinum: achieve highest level of LEED certification; Net Zero: The building will utilize existing wind and alternate energy sources on campus and add solar PVT panels and achieve as close as possible to a net zero energy usage; and Phase II: The phase II portion of this project will expand the Internet student area, additional classrooms, and labs, as well as an auditorium and exhibit area.

14 SOLAR ENERGY↗

DOE OSTI2016

City Scale Modeling with OpenStudio

Assessing the impact of energy efficiency technologies at a district or city scale is of great interest to local governments, real estate developers, utility companies, and policymakers. This paper describes a flexible framework that can be used to create and run district and city scale building energy simulations. The framework is built around the new OpenStudio City Database (CityDB). Building footprints, building height, building type, and other data can be imported from public records or other sources. Missing data can be inferred or assigned from a statistical sampling of other datasets. Once all required data is available, OpenStudio Measures are used to create starting point energy models and to model energy efficiency measures for each building. Together this framework allows a user to pose several scenarios such as 'what if 30% of the commercial retail buildings added rooftop solar' or 'what if all elementary schools converted to ground source heat pumps' and then visualize the impacts at a district or city scale. This paper focuses on modeling existing building stock using public records. However, the framework is capable of supporting the evaluation of new construction, district systems, and the use of proprietary data sources.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗