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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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DOE OSTI2012

Wynkoop Building Performance Measurement: Water

This report is a summary of the water analysis performance for the Denver, Colorado Wynkoop Building. The Wynkoop Building (Figure 1) was built in 2006 as the Environmental Protection Agency (EPA) Region 8 Headquarters intended to house over 900 occupants in the 301,292 gross square feet (248,849 rentable square feet). The building was built on a brownfield in the Lower Downtown Historic District as part of an urban redevelopment effort. The building was designed and constructed through a public-private partnership with the sustainable design elements developed jointly by General Services Administration (GSA) and EPA. That partnership is still active with all parties still engaged to optimize building operations and use the building as a Learning Laboratory. The building design achieved U.S. Green Building Council Leadership in Energy and Environmental Design for New Construction (LEED-NC) Gold Certification in 2008 (Figure 2) and a 2008 EPA Energy Star Rating of 96 with design highlights that include: (1) Water use was designed to use 40% less than a typical design baseline. The design included low flow fixtures, waterless urinals and dual flush toilets; (2) Native and adaptive vegetation were selected to minimize the need for irrigation water for landscaping; and (3) Energy use intensity was modeled at 66.1 kBtus/gross square foot, which is 39% better than ASHRAE 90.1 1999. The Wynkoop Building water use (10 gallons/square foot) was measured at lower than industry average (15 gallons/square foot) and GSA goals (13 gallons/square foot), however, it was higher than building management expected it would be. The type of occupants and number of occupants can have a significant impact on fixture water use. The occupancy per floor varied significantly over the study time period, which added uncertainty to the data analysis. Investigation of the fixture use on the 2nd, 5th, and 7th floors identified potential for water use reduction if the flush direction of the dual-flush toilet handles was reversed. The building management retrofitted the building's toilets with handles that operated on reduced flush when pushed down (0.8 gallons) and full flush when pulled up (1.1 gallons). The water pressure on the 5th floor (< 30 psi) is less than half the pressure on the 7th floor (>80 psi). The measured water savings post-retrofit was lower on the 5th floor than the 7th floor. The differences in water pressure may have had an impact on the quantity of water used per floor. The second floor water use was examined prior to and following the toilet fixture retrofit. This floor is where conference rooms for non-building occupants are available for use, thus occupancy is highly variable. The 3-day average volume per flush event was higher post-retrofit (0.79 gallons per event), in contrast to pre-retrofit (0.57 gallons per event). There were 40% more flush events post retrofit, which impacted the findings. Water use in the third floor fitness center was also measured for a limited number of days. Because of water line accessibility, only water use on the men's side of the fitness center was measured and from that the total fitness center water use was estimated. Using the limited data collected, the fitness center shower water use is approximately 2% of the whole building water use. Overall water use in the Wynkoop Building is below the industry baseline and GSA expectations. The dual flush fixture replacement appears to have resulted in additional water savings that are expected to show a savings in the total annual water use.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

Designing for Zero Energy and Zero Carbon on a Multi-Building Scale Using URBANopt: Preprint

Groundbreaking efforts are necessary to mitigate contributors increasing impacts of climate change. In parallel to inventing pioneering clean energy technologies it is even more fundamental to rethink designing energy systems within a singular facility and collectively to function as a district. Facilities should not be continuously passive by just consuming; there is a need to shift to perform more dynamically. Designing for zero energy and zero carbon on a multi-building scale can uncover opportunities for building energy efficiency, decarbonization, demand flexibility, and resiliency that are not accessible at an individual building scale. This approach can be challenging without innovative tools to evaluate the multitude of possibilities. As an investigated result, we highlight the use of a campus-scale energy modeling platform - URBANopt™ - for the expansion of the National Renewable Energy Laboratory's (NREL's) South Table Mountain campus in Golden, Colorado. Programmatic growth included the design of three new all-electric, zero-energy, and zero-carbon, mixed used buildings (a combination of research laboratories and office space). This investigation is critical to NREL reaching net-zero emissions for its operational footprint, which will occur in phases over the next decade. Leveraging URBANopt's capabilities, we evaluate 1) high-performance building energy efficiency and decarbonization measures, 2) 4th generation district heating and cooling (4th GDHC) systems, 3) optimized onsite generation and energy storage assets that meet zero-energy and zero-carbon targets at minimum life-cycle costs, and 4) cost-optimal distributed energy technology mixes, dispatch strategies, and associated capacities that increase resiliency to grid outages. This work demonstrates the use and capabilities of URBANopt through a real-world case study on a multi-building scale.

community energy model↗

NASA NTRS1987

Magnetohydrodynamic (MHD) analyses of various forms of activity and their propagation through helio spheric space

Theoretical and numerical modeling of solar activity and its effects on the solar atmosphere within the context of magnetohydrodynamics were examined. Specifically, the scientific objectives were concerned with the physical mechanisms for the flare energy build-up and subsequent release. In addition, transport of this energy to the corona and solar wind was also investigated. Well-posed, physically self-consistent, numerical simulation models that are based upon magnetohydrodynamics were sought. A systematic investigation of the basic processes that determine the macroscopic dynamic behavior of solar and heliospheric phenomena was conducted. A total of twenty-three articles were accepted and published in major journals. The major achievements are summarized.

Wu, S. T.↗

DOE OSTI2022

Demonstration of a modeling toolkit for the design of building electrical distribution systems

The deployment of building equipment (e.g., lighting, security) and miscellaneous electrical loads that fundamentally require DC power for operation is increasing. Powering these DC loads has traditionally required an AC/DC converter, but the installation of photovoltaic (PV) and battery energy storage systems that primarily produce DC power eliminates the need for AC/DC converters at each end-device. However, analyzing system energy efficiency and cost for different electrical distribution architectures can be challenging as software tools that support this are not readily available. This paper presents preliminary results from a laboratory verification of the Building Electrical Efficiency Analysis Model (BEEAM) toolkit that was developed to address this gap. Three different eight-luminaire lighting systems comprised of market-available products were designed and modeled: one that used traditional AC distribution, a second that used a hybrid AC -to- centralized DC electrical distribution architecture, and a third that used a hybrid AC -to- distributed DC architecture. Notably, AC/DC conversions are required in all three systems. BEEAM models for LED drivers as well as Power-over-Ethernet (PoE) switches were created using laboratory characterization data. The lighting systems were simulated in Modelica, and the results were compared with each other and physics-based expectations. Simulation results show that PoE system energy efficiency is highly dependent on both device specification (e.g., LED driver and PoE switch efficiency) and system architecture (e.g., PoE switch loading) choices, as expected. For the products and system architectures selected for this study, the two DC systems were found to be less efficient than the AC system over the course of typical operation. In future work, simulation results will be compared with laboratory measurements to validate the usefulness of this software for design, and lighting systems with integrated PV and battery energy storage will be simulated to quantify the energy performance improvements that result from the elimination of some AC/DC converters.

Waghale, Anay S.↗

DOE OSTI2026

Machine learning-enhanced MPC for demand flexibility in small commercial buildings: An experimental study

Small- and medium-sized commercial buildings (SMCBs) represent the majority of U.S. commercial building stock and a significant share of peak electricity demand, yet they often lack centralized building automation systems, representing a significant untapped resource for urban energy management. This infrastructure gap makes advanced control implementation challenging, limiting the potential for widespread demand flexibility. Model Predictive Control (MPC) has shown strong potential for load shifting, peak demand reduction, and cost savings, but its effectiveness is hindered by unmeasured disturbances such as internal heat gains. This paper presents a Hybrid MPC framework that integrates a physics-based gray-box building thermal model, identified using a lumped disturbance (LD) approach, with a machine learning (ML) model for forecasting unmeasured disturbances. The hybrid approach is designed for buildings with multiple individually controlled heat pump and thermostat pairs, common in SMCBs, and aims to optimize coordinated scheduling of multiple heat pumps under dynamic electricity pricing while respecting comfort constraints. The methodology is validated through both simulations of case study buildings and experimental studies at a highly-instrumented test facility. Simulation results show that the Hybrid MPC achieves substantial load shifting and peak demand reduction, approaching the performance of an ideal MPC with perfect disturbance knowledge, and outperforming a conventional MPC without disturbance forecasting. In experiments, the Hybrid MPC reduced daily HVAC energy costs by 8.7%, peak-price time load (load shifting) by 41.7%, and peak demand by 29.2% compared to baseline control, demonstrating comparable benefits to the 11.6% cost savings, 42.9% load shifting, and 23.2% peak reduction of the ideal MPC. These results demonstrate that the proposed hybrid modeling approach can significantly improve MPC performance in real-world SMCB applications without requiring additional disturbance measurements.

Demand Flexibility↗

DOE OSTI2013

A post-occupancy monitored evaluation of the dimmable lighting, automated shading, and underfloor air distribution system in The New York Times Building

With aggressive goals to reduce national energy use and carbon emissions, the US Department of Energy will be looking to exemplary buildings that have already invested in new approaches to achieving the energy performance goals now needed at a national level. The New York Times Building, in New York, New York, incorporates a number of innovative technologies, systems and processes and could become a model for widespread replication in new and existing buildings. Post-occupancy data are invaluable in establishing confidence in innovation. A year-long monitored study was conducted to verify energy performance, assess occupant comfort and satisfaction with the indoor environment, and evaluate impacts on maintenance and operations. Lessons learned were derived from the analysis; these lessons could help identify and shape policy, financial, or supporting strategies to accelerate diffusion in the commercial building market.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Low-cost fin-tube heat exchanger design for building thermal energy storage using phase change material

Heat transfer in phase change materials (PCMs) is complex because the melting and freezing fronts change as functions of stored or released heat. In prior attempts to optimize heat exchangers (HXs) in one or two dimensions, complex geometry has often been used to maximize the melt and freeze front area. This complex geometry is difficult and hence expensive to construct. This paper proposes a multiple-scale 3D finite element modeling approach to design fin-tube HXs for low-cost latent thermal energy storage applications. Further, the optimal fin and tube designs were determined at three scales (unit-scale, medium-scale, and large-scale) by modeling the melt and freeze front in three dimensions and using measured bulk thermal properties. The finite element model was validated by comparing it with the experimental data for a referenced design of a similar type. The results indicate that commercially available organic PCMs with low conductivity (<0.3 W/m·K) can have charge and discharge times appropriate for building thermal energy storage (i.e., 4–5 h) with fin-tube HX designs at costs <$26/kWh, even when the temperature difference (5.56°C) between the heat transfer fluid and the PCM phase change temperature is small. However, as the HX increases in length, the temperature reduction along the tube limits some larger-scale designs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Performance Evaluation of Gray-box and Machine Learning Models of a Thermal Energy Storage System with Active Insulation

An interior partition wall integrated with active thermal storage and a dynamic insulation system was built and then installed in an office building in Oak Ridge, Tennessee, TN. This smart wall, termed the Empower Wall, was equipped with embedded pipes in the building envelope core component and an additional pipe network enclosing rigid insulation to switch on and off the active insulation dynamically. The performance of the wall's contribution to cooling load reduction under different parameters has been investigated in previous publications. Aiming to be deployed into model predictive control and other optimization methods, simplified and reliable models for the developed wall and the room accommodating it are required. They are needed to characterize the properties and thermal response of both Empower Wall and building envelope, which form an essential component for accurate indoor temperature or cooling/heating demand prediction. In this study, simplified gray-box and regression models as well as machine learning model were developed and the performance of them were compared and analyzed.

Cui, Borui↗

DOE OSTI2022

Hierarchical Model-Free Transactive Control of Residential Building Loads: An Actual Deployment

The transformation of electricity systems into more sustainable configurations brought some new challenges. The uncertain, intermittent, and variable nature of renewable energy sources require a significant amount of load demand flexibility, in which grid-interactive buildings (GEBs) are important flexible assets for electricity systems. In this regard, many demand response (DR) tools have been developed to harness this demand flexibility. However, such tools are mostly simulation-based or deal with a single load, which may not be sufficient to demonstrate their effectiveness. Towards this end, this paper presents a real-world field implementation and testing of a hierarchical model-free transactive DR control approach on actual GEBs. The control implementation incorporates elements of virtual battery, game theory, and model-free control mechanisms. The proposed approach was tested using a total of five GEBs, each having three zones. The results show that the proposed approach can mostly achieve all intended objectives, including flexibility estimation, peak load reduction, power tracking, and controlling GEBs while maintaining occupants’ comfort.

Amasyali, Kadir↗

DOE OSTI2019

Community Microgrid Planning Considering Building Thermal Dynamics

In this paper, the building thermal dynamic characteristics are introduced in the community microgrid (MG) planning model. The proposed planning model is formulated as a mixed integer linear programming (MILP) which seeks to determine the optimal deployment strategy for various distributed energy resources (DER). The objective is to minimize the annualized cost of community MG, including investment cost in DER, operation cost for dispatchable fuel-generators (DFG), energy storage system (ESS) degradation cost, energy purchasing and peak demand charge at PCC, customer discomfort cost due to the room temperature deviation and load curtailment cost. Given the slow thermal dynamic characteristics of buildings, the heating, ventilation and air-conditioning (HVAC) system in the proposed model is treated as a demand side management (DSM) component, whose dispatch commands are provided by the central MG controller. Numerical results based on a community MG comprising of 20 residential buildings demonstrate the effectiveness of the proposed planning model and the benefits of introducing the building thermal dynamic model.

Zhang, Xiaohu↗

DOE OSTI2024

New Virtual Test Bed Capabilities: Virtual DOME Model and New Updates to Repository

The Department of Energy (DOE) Office of Nuclear Energy National Reactor Innovation Center accelerates the deployment of novel reactor concepts by establishing both physical and virtual spaces for building and testing various components, systems, and complete pilot plants. The Virtual Test Bed represents the virtual arm of the National Reactor Innovation Center and is a joint effort with the DOE Nuclear Energy Advanced Modeling and Simulation Program. The Virtual Test Bed mission is to accelerate the deployment of advanced reactors by facilitating the adoption of cutting-edge DOE advanced modeling and simulation tools to design, evaluate, and license reactors. This is primarily achieved by storing example challenge problems in an externally available repository and by developing models to fill the M&S gaps needed for potential demonstrators. Activities conducted this fiscal year focused on developing of a Demonstration of Microreactor Experiments shield model to help accelerate the confirmatory analysis required for the reactor demonstration. This model and workflow will allow developers to leverage advanced modeling and simulation tools to ensure their reactor demonstration concept will meet dose requirements and that the surrounding shield will stay within concrete temperature limits during steady-state and transient operation conditions. An initial model has been developed to evaluate the temperature distribution in the concrete shield during steady-state operation, including neutron and gamma heating effects. Various modeling strategies have been examined to understand their applicability and limitations with different reactor designs to make the workflow as reactor-agnostic as possible and computationally effective to maximize its usability. In addition to describing the Demonstration of Microreactor Experiments shield model and associated results, this report summarizes other accomplishments regarding repository maintenance and improvement and new external models hosted on the repository.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2016

Modeling Enclosure Design in Above-Grade Walls

Building Science Corporation modeled typically well-performing wall assemblies using Wärme und Feuchte instationär (WUFI) Version 5.3 software and demonstrated that these models agree with historic experience when calibrated and modeled correctly. This technical report provides a library of WUFI modeling input data and results. Within the limits of existing experience, this information can be generalized for applications to a broad population of houses.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Hierarchical Model-Free Transactional Control of Building Loads to Support Grid Services

A transition from generation on demand to consumption on demand is one of the solutions to overcome the many limitations associated with the higher penetration of renewable energy sources. Such a transition, however, requires a considerable amount of load flexibility in the demand side. Demand response (DR) programs can reveal and utilize this demand flexibility by enabling the participation of a large number of grid-interactive efficient buildings (GEB). Existing approaches on DR require significant modelling or training efforts, are computationally expensive, and do not guarantee the satisfaction of end users. To address the aforementioned limitations, this software code considers a scalable hierarchical model-free transactional control approach that incorporates elements of virtual battery, game theory, and model-free control (MFC) mechanisms. The developed approach separates the control mechanism into upper and lower levels. The MFC modulates the flexible GEB in the lower level with guaranteed thermal comfort of end users in response to the optimal pricing and power signals determined in the upper layer using a Stackelberg game integrated with aggregate virtual battery constraints. Additionally, the usage of MFC necessitates less burdensome computational and communication requirements, thus, it is easily deployable even on small, embedded devices. This software code enables the use of residential and small-size commercial buildings to offer a potentially substantial source of ancillary grid services that are currently underutilized. A hierarchical, model-free transactive building control provides a smooth interface between the grid service requests of utilities and the reliable control required by participating buildings. Model-free control, which supports distributed control architecture, will be a more scalable solution that can be deployed in neighborhood-size systems as well as individual buildings. The proposed approach contributes to the body of knowledge on two main aspects. First, it couples the MFC with the game-theoretic control and proposes a scalable model-free transactive control approach. MFC does not require any modeling effort or model training for the various building loads. This is very beneficial since deriving an accurate model for every single unit participating in DR programs and obtaining all the parameters about the units (e.g., thermal coefficients, standby losses) are infeasible. Also, MFC is computationally efficient, easily deployable even on small, embedded devices, and can be implemented in real time. Second, it integrates the concept of virtual battery into DR via the Stackelberg game. The concept of virtual battery enables efficient coordination and aggregation of a large number of flexible GEB with guaranteed thermal comfort of end users.

Olama, Mohammed [Oak Ridge National Lab. (ORNL), O↗

DOE OSTI2019

Learning occupants’ indoor comfort temperature through a Bayesian inference approach for office buildings in United States

A carefully chosen indoor comfort temperature as the thermostat set-point is the key to optimizing building energy use and occupants’ comfort and well-being. ASHRAE Standard 55 or ISO Standard 7730 uses the PMV-PPD model or the adaptive comfort model that is based on small-sized or outdated sample data, which raises questions on whether and how ranges of occupant thermal comfort temperature should be revised using more recent larger-sized dataset. In this paper, a Bayesian inference approach has been used to derive new occupant comfort temperature ranges for U.S. office buildings using the ASHRAE Global Thermal Comfort Database. Bayesian inference can express uncertainty and incorporate prior knowledge. The comfort temperatures were found to be higher and less variable at cooling mode than at heating mode, and with significant overlapped variation ranges between the two modes. The comfort operative temperature of occupants varies between 21.9 and 25.4 °C for the cooling mode with a median of 23.7 °C, and between 20.5 and 24.9 °C for the heating mode with a median of 22.7 °C. These comfort temperature ranges are similar to the current ASHRAE standard 55 in the heating mode but 2–3 °C lower in the cooling mode. Finally, the results of this study could be adopted as more realistic thermostat set-points in building design, operation, control optimization, energy performance analysis, and policymaking.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2014

Distributed Energy Resources Customer Adoption Model (DER-CAM), Investment & Planing Version 3.10.5.m

Version 3.10.5 is a multi-year Decision Support tool for Distributed Generation (DG). DER-CAM was initially created as an exclusively economic energy model, able to find the cost minimizing combination and operation profile of a set of DER technologies that meet heat and electric loads of a single building or microgrid for a typical test year. Now, version 3.10.5.m solves for a multiple-year horizon the technology choice question, the appropriate capacity for each selected technology as well as the operational and investment schedule. Optimized investment decisions are based on techno-economic criteria, along with site information such as energy loads, economic forecast, and technology characterization. Version 3.10.5 contains: 1. a PV and battery degradation model and 2. variable performance for technologies. Efficiency, investment costs, etc. can vary over time and model technology breakthroughs and advancements.

Source record↗

DOE OSTI2025

Educational Consortium for Energy-related Data Science & Computation in Building Engineering Programs

The project spearheaded by Pennsylvania State University aims to address the growing need for integrating energy-focused computation and data science into building engineering education. As the demand for energy-efficient building designs and operations increases, the educational sector must adapt to equip future engineers with the necessary skills. This initiative responds to this need by developing a consortium that unites multiple institutions to enhance curriculum development, dataset curation, and resource sharing, thereby ensuring students are well-prepared for the evolving energy sector. The primary goal of the project is to establish a consortium that will develop and disseminate educational materials and training programs focused on energy-related data science and computation. Key accomplishments include the creation of a beta website for resource sharing, the development of training programs and standalone modules, and the curation of datasets accessible to the public. This effort will culminate in a curriculum that incorporates advanced modeling technologies and data science skills into building engineering programs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Advanced Guide to Understanding Power System Model Results for Long-Term Resource Plans

This guide is for public utility commission staff, state energy office staff, and other stakeholders who review model results for utility integrated resource plans (IRPs). It builds on the "Beginner's Guide to Understanding Power System Model Results for Long-Term Resource Plans," and delves into more advanced topics that were not included or not fully covered in the beginner's guide. The topics included here are evolving and may or may not be important to the resource plan you are evaluating. Due to limitations in resources, it's also not possible to give the highest level of detail or attention to every topic within a plan. An important part of planning for an uncertain future involves deciding which topics deserve the most focus and resources. It's all about prioritizing efforts where they will have the most impact or be most beneficial despite uncertainties ahead. As with the beginner's guide, we intend for this guide to help improve decision-making in the electricity planning process by strengthening understanding and dialogue between electricity system planners and relevant stakeholders. The following information is designed to allow you to better engage in the planning process by evaluating results, asking questions, and thinking through what is most important. We allocate significant discussion in the guide to electricity demand evolution, demand-side resources, and resource adequacy. These topics have garnered increasing attention, hence their prominence in this guide. Other topics are also presented, but their incorporation into the planning process might vary based on interest and relevance. The absence of certain topics doesn't diminish their importance; rather, it reflects the reality that in planning, trade-offs necessitate prioritizing certain aspects over others.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2019

Future integrated mobility-energy systems: A modeling perspective

After over a century of petroleum dominance, the transportation sector is on the verge of radical transformations driven by rapid technology advancement of alternative fuels, automation, information technologies that create new mobility options and business models, and policies at all levels of government. While the technologies and fuels that will move people and goods in the future remain uncertain, the future transportation system will be more integrated with smart buildings, the electric grid, renewables, and information ecosystems, allowing for great opportunities to exploit these interconnections. Modeling tools for analyzing integrated mobility-energy systems require a deep understanding of these interconnections, of the infrastructure required to support alternative fuel vehicles, and a more nuanced understanding of transportation energy needs across multiple segments and spatiotemporal scales. In this paper, we assess the landscape of existing tools used to represent and model future mobility systems and their interactions with other energy systems. Here, we conclude that (a) out-of-sample extrapolation of emerging trends and future anticipated developments is more important than ever due to the plethora of factors driving disruptive change in mobility systems; (b) understanding adoption opportunities for alternative fuel light-duty vehicles requires modeling intra-household decisions affecting travel demand and mode choice; (c) mobility and energy systems need to be modeled as an integrated continuum, breaking the traditional approach in which dynamic energy supply models use relatively simple transportation demand and vice-versa; and (d) increased spatiotemporal fidelity and scalability are required to dynamically couple transportation/mobility and energy supply models and capitalize on these unprecedented interconnection opportunities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗