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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗
DOE OSTI2021

The Impacts of Distinct Flexibility Enhancements on the Value and Dynamics of Natural Gas Power Plant Operations

The rapid increase of renewable generation and its anticipated continued growth requires greater operational flexibility in modern power systems. Previous studies explored the addition of more flexible resources to improve system flexibility, but this may also be achieved at lower cost by enhancing existing power plants via flexibility retrofits. Potential flexibility upgrades to existing thermal plants include modifications that enable faster ramp rates, increase maximum load levels, decrease minimum load levels, and provide faster and lower cost startup operations. In this paper, we focus on improvements to existing natural gas combined cycle generators, and apply a unit commitment model to analyze the impact that each specific upgrade has on their operational dynamics and profitability from both the system perspective and from the asset owner perspective. We show that the value of each type of flexibility improvement varies depending on the capacity factor and usage pattern of the generator before the upgrade, and that the relative benefit of each type of flexibility varies. We demonstrate diminishing returns to increased flexibility when upgrading multiple generators simultaneously. Sensitivity tests for several shares of renewable generation, different generation mixes and different net load realizations confirm the generality of the results shown.

03 NATURAL GAS↗
DOE OSTI2025

Integration of a grey-box refrigerated case model in EnergyPlus via Python plugin

Commercial buildings, in particular grocery stores (due mainly to their large refrigeration load), provide opportunities for energy cost reductions. Grocery stores could offer substantial load flexibility to the power grid through participation in demand response programs because of their usage patterns and relatively high energy intensity. This load flexibility could come from modifying the control of heating, ventilation, and air conditioning (HVAC) systems, refrigeration systems, or both. Although estimation of the HVAC system’s load flexibility potential is relatively targeted in the literature, estimating load flexibility of refrigeration systems is nascent and has been a challenge, in part because of the lack of proper simulation tools that capture the dynamics in the refrigeration cases. The existing refrigerated case model within EnergyPlus, a whole building energy simulation program, assumes a constant case temperature throughout the simulation period and does not explicitly model the cycling of the compressor serving the refrigerated case. In addition, it does not encompass modeling of temperatures of the product inside the refrigerated case. This difference between modeled and actual operation can be a barrier to the development of demand control algorithm and accurate analysis of load flexibility potential. In this paper, we present a grey-box model for modeling refrigerated cases in grocery stores, which include medium temperature and low temperature. Four cases are modeled; two are low-temperature closed cases and two are medium-temperature cases with one closed and one open. Data from an experimental facility are used to train and test the models. Results demonstrate the efficacy of the grey-box models in predicting the temperatures. This model is integrated into EnergyPlus to capture the dynamic effects of case temperature on the environment and enhance the calculation of sensible and latent heat exchange with the environment (case credits). These enhancements can be leveraged more broadly to model advanced refrigeration controls such as defrost, develop and test unique algorithms that could affect refrigeration interactions with HVAC, and refine store design for any commercial building with refrigeration.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Potential of Data Center Controls in Grid Services

The rapid proliferation of large data centers brings both challenges and opportunities for grid reliability. The data center resources and their potential flexibility have the potential to contribute resources to grid operations. Through capabilities like energy shifting and resource coordination, data centers can help reduce their net demand on the transmission network, as well as provide additional grid services to support reliable operation on the grid. While transient and long-term grid planning and operations are the scenarios that draw most attention, the quasi-steady state timeseries (QSTS) operation of data centers and grid bring interesting scenarios that can help evaluate the data center controls to aid grid services. This work is focused on modeling data centers for QSTS applications – incorporating the AI data center load profiles and building on the PNNL digital twin model for the thermal management loads to enable simulation studies to reveal the impact of data center controls on grid performance. This includes the integration of a QSTS battery and natural gas generator model to incorporate local resource impacts to the system. The simulation study is performed with a modified IEEE 24-Bus transmission system. Scenarios are focused on evaluating the data center load impacts on the transmission system and leveraging both data center and local generation controls to mitigate those impacts and provide additional grid services. The data center controls revealed the ability to contribute to two main kinds of grid services: preventing congestion on a weak grid by coordinating the data center resources with the collocated BESS and onsite generation; and the ability to help the grid operations during stressed times of operation like during a contingency. Leveraging these and other capabilities has the potential to help data centers become grid responsive assets, aiding in both their integration into the power system and grid reliability.

power grid simulation↗
DOE OSTI2024

Exploring Multidimensional Spatial-Temporal Hydropower Operational Flexibilities by Modeling and Optimizing Water-Constrained Cascading Hydroelectric Systems

Because of unique characteristics such as clean and cost-competitive electricity as well as fast-ramping and storage abilities, the power industry continues to evolve its operation strategies for cascading hydroelectric (CHE) systems for providing enhanced values to the grid, especially under the deeper renewable resource integration. However, existing operation practices of CHEs predate the integration of renewables, which could prohibit the effective utilization of their inherent flexibilities in delivering maximum financial benefits and providing valuable grid services to the power system and electricity market operations. Indeed, modeling and optimizing these resource-limited while flexible CHE assets with uncertainties and imperfect information across multiple spatial-temporal dimensions present significant challenges. To facilitate CHE facility operators in effectively coordinating water usage and hydropower plant operations across multiple timescales, this project aims to fill the existing gaps by developing a suite of accurate water inflow (WI) forecast models as well as enhanced CHE modeling and optimization approaches with proper consideration of their unique characteristics, which would help explore their multidimensional spatial-temporal operational flexibility potentials. The developed approaches could better align reservoir operation strategies with variability and uncertainty of future water availability. They can also promote more effective utilization of multidimensional spatial-temporal hydropower operational flexibility potentials by designing long-term evacuation plans of reservoirs and short-term operation of CHEs, along with their coordination with other types of renewables. The project leverages various resources to facilitate the research and development activities, including actual characteristics data of CHE systems and a library of current and future cases of Portland General Electric (PGE). These realistic data enable the project team to study how to maximize the value of CHEs under current and future portfolios and evaluate opportunities to improve operation practices.

13 HYDRO ENERGY↗
DOE OSTI2023

A Simulation Framework for Analyzing the Impact of Stochastic Occupant Behaviors on Demand Flexibility in Typical Commercial Buildings

As one of the primary users of the electric grid, buildings and building equipment, including heating, ventilation, and air conditioning (HVAC) systems, can be leveraged to provide the flexible demand needed to balance the grid. Typical strategies to achieve demand flexibility are to reduce electricity use during peak or critical periods by shutting down equipment or relaxing system setpoints, which will inevitably impact the occupants’ comfort. When occupants feel uncomfortable, they may take actions to regain their comfort, and some of those actions (such as turning on a personal fan) may have a negative impact on meeting the demand response goal. Therefore, it is important to incorporate occupant behaviors into the assessment ofthe building demand flexibility potential. In this study, a simulation framework that includes simulation of zone thermal loads, an HVAC system, and occupant behaviors, was developed to investigate the impact of occupant behaviors on demand flexibility. A case study was conducted using a small office model from the U.S. Department of Energy (DOE) Commercial Prototype Building Models to simulate the building envelope and zone loads. An agent-based occupant thermal behavior model was adapted to forecast occupants’ thermal comfort and their resulting thermal behaviors. An artificial neural network (ANN) based airflow model trained from a computational fluid dynamics (CFD) model of the zone was adopted to better predict the ambient environment of each occupant. An air-source heat pump simulation model that was calibrated from a real two-stage air-source heat pump system was used as the HVAC system. A typical load shedding event during peak hours was studied. Repeated simulations were conducted to capture the stochastic effects of occupant behaviors. The interplay between the demand flexibility, occupant comfort and behavior were analyzed by evaluating key performance indicators, including the energy use, occupant discomfort duration, and occupant behavior duration during the peak period. The results suggest that this framework can be used to analyze typical commercial buildings and their HVAC systems in terms ofdemand flexibility potential under the impact of occupant behaviors.

Chen, Zhelun↗
DOE OSTI2024

Identifying Hydropower Operational Flexibilities in Presence of Streamflow and Net-load Uncertainty (Final Technical report)

In the existing operations, hydropower contributions to future system flexibility are generally modeled while maintaining traditional operating rules and constraints in supporting grid operation, such as the balancing of variable renewable energy production. Moreover, operation of large scale hydropower systems on major rivers has been investigated for decades, utilizing various systems engineering approaches, with the evolving electric grid, as the result of renewable resources integration, compounded by the changing climate (variability of river flows, intensification of hydrologic cycle resulting in more frequent extreme events) affecting water availability, the need for more advanced stochastic modeling and effective uncertainty analysis approaches have become necessary. The research results supported by this funding and presented in this report provide a new look at hydropower operational flexibility enforced by the changes identified above. Understanding how hydropower operates in response to the underlying uncertainties with respect to the system constraints is crucial in identifying its operational flexibility potentials. In this project, the flexibility of the operating hydropower facility is described by capturing uncertainties in both water and power system and formulating the operations as a multistage stochastic optimization problem. The proposed approach supports short- to seasonal-term operations and planning decision horizons.

13 HYDRO ENERGY↗
DOE OSTI2025

Optimizing district energy systems under uncertainty: Insights from a case study from Washington D.C., USA

This study investigates solutions for delivering affordable heating and cooling to a brownfield site, focusing on a case study in Washington, DC. Moving towards more diverse and resilient energy systems, we identify the optimal portfolio for a district energy system with diverse energy sources to meet the area’s energy demands. Our methodological approach integrates two detailed models: one calculating building-level energy demand and the other optimizing district energy technology choices based on their demand profiles, accounting for uncertainties in energy prices, policies, and other parameters. The results provide an economic comparison of district and individual supply options at the building level, emphasizing the flexibility district systems can offer to the electricity sector. District energy systems demonstrate cost-stabilization benefits amidst volatile energy prices and external uncertainties. For heating, district systems yield significant cost savings compared to individual solutions, driven by fuel flexibility and the use of local renewable energy sources. For cooling, district systems also show advantages, though individual systems may remain more cost-effective for smaller buildings. Additionally, district systems exhibit considerable flexibility on the heating side, as evidenced by variations in electricity consumption. We recommend future research to explore the relationship between the economics of district energy systems, particularly at the building level, and their flexibility potential for the electricity sector across diverse geographic contexts to reduce overall grid costs and promote grid reliability. This includes areas with distinct zoning laws, municipal priorities, utility structures, and funding mechanisms, such as the United States, and regions like Europe with pronounced electricity price volatility.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Managing Solar Photovoltaic Integration in the Western United States: Power System Flexibility Requirements and Supply

As penetrations of variable renewable energy generation technologies such as wind and solar photovoltaics (PV) continue to increase across the United States, greater uncertainty and variability in the net load often lead to a concern about how power systems may adapt. Managing the system net load (i.e., load minus contribution from variable generation technologies) may become more challenging with increasing variable generation, as the magnitude and frequency of net ramps increase. However, there is inherent flexibility in power systems through the conventional generator fleet (under least-cost unit commitment and economic dispatch), less-conventional generation sources (e.g., storage, demand response, concentrating solar power with thermal energy storage), and imports and exports with neighbors. In this analysis, we create an open-source tool to analyze the flexibility of the results of a specific commercial unit commitment and economic dispatch tool (PLEXOS), but the code can be applied generically as well. The tool assesses the flexibility requirements (or demand) of a system through a net load analysis. The constraints and limitations of each generator are then considered to determine the availability (or supply) of flexibility. Then, the supply and demand of flexibility are compared to gain a more complete picture of potential flexibility concerns. We apply this open-source tool to high-penetration PV scenarios constructed for three focus regions in the western United States defined using the Resource Planning Model (RPM) capacity expansion modeling tool: RPM-OR, RPM-CO, and RPM-AZ. Generally, we find few flexibility concerns, as the western United States represents a large and interconnected power system with significant inherent flexibility. In addition, the PV scenarios we analyzed are overbuilt on capacity, leaving plenty of ramping ability on the system. We do find that for each focus region, the impact of imports on meeting ramping needs is essential. This means the PV integration in each focus region impacts the entire rest of the system. Each system has different dominant sources of flexibility. The conventional generator fleet (especially coal and gas combined-cycle technologies) as well as less-conventional sources such as storage are all shown to be important sources of flexibility. The scenarios evaluated here were designed to study the planning and operations impact of high solar penetration in each of three focus regions. However, none of the three focus regions likely will deploy PV in isolation, meaning the ability of imports and exports to provide flexibility may be considerably different in scenarios with strong PV deployment in every region. Overall, we intend that the framework we present here will be useful in future analysis of other system evolutions to identify whether and how flexibility may constrain the successful deployment of variable generation technologies.

14 SOLAR ENERGY↗
DOE OSTI2025

DFAT: A web-based toolkit for estimating demand flexibility in building-to-grid integration

Demand Flexibility Assessment Tool (DFAT) is an open source web-based tool that estimates the demand flexibility potential of common control strategies in commercial buildings. The toolkit features a demand flexibility estimation tool that contains two calculators, basic and advanced, based on the level of input of customer data. The basic version calculates demand shed metrics for the control strategy “global temperature adjustment” and “cycle on/off compressors” using customer building information, local weather data, and electrical meter data. The advanced version, which uses detailed HVAC equipment data, calculates demand flexibility metrics for control strategies such as static pressure reset, global temperature adjustment, and cycle on/off compressors. In addition to the demand flexibility estimation tool, this toolkit offers a benchmarking tool that helps facility operators, aggregators, and utility resource managers assess demand flexibility opportunities, quantify/verify performance, and compare their performance against that of their peers.

Leong, Michael↗
DOE OSTI2023

Development of a hardware-in-the-loop testbed for laboratory performance verification of flexible building equipment in typical commercial buildings

The goals of reducing energy costs, shifting electricity peaks, increasing the use of renewable energy, and enhancing the stability of the electric grid can be met in part by fully exploiting the energy flexibility potential of buildings and building equipment. The development of strategies that exploit these flexibilities could be facilitated by publicly available high-resolution datasets illustrating how control of HVAC systems in commercial buildings can be used in different climate zones to shape the energy use profile of a building for grid needs. This article presents the development and integration of a Hardware-In-the-Loop Flexible load Testbed (HILFT) that integrates physical HVAC systems with a simulated building model and simulated occupants with the goal of generating datasets to verify load flexibility of typical commercial buildings. Compared to simulation-only experiments, the hardware-in-the-loop approach captures the dynamics of the physical systems while also allowing efficient testing of various boundary conditions. The HILFT integration in this article is achieved through the co-simulation among various software environments including LabVIEW, MATLAB, and EnergyPlus. Although theoretically viable, such integration has encountered many real-world challenges, such as: 1) how to design the overall data infrastructure to ensure effective, robust, and efficient integration; 2) how to avoid closed-loop hunting between simulated and emulated variables; 3) how to quantify system response times and minimize system delays; and 4) how to assess the overall integration quality. Lessons-learned using the examples of an AHU-VAV system, an air-source heat pump system, and a water-source heat pump system are presented.

Chen, zhelun↗
DOE OSTI2024

Frozen Freedom: Unleashing Grocery Store Demand Flexibility: Preprint

Grocery stores consumed approximately 3% of total electricity used by commercial buildings in the U.S. in 2018 (EIA 2018), representing a unique end-use load profile characterized by the critical use of refrigerated display cases. Exploring demand response (DR) scenarios in grocery stores presents an opportunity to enhance the efficiency and sustainability of surrounding communities. In addition, recent studies demonstrate that implementing control algorithms considering demand flexibility strategies can lead to load and peak reductions in standalone refrigerated display cases. Because small business grocery stores operate on thin margins, the energy bill cost savings DR might provide could make a positive difference toward continued operations. Still, uncertainty remains about the extent of demand flexibility potential controls could provide when coupling refrigeration with whole building operation. To enhance economic viability and grid stability, it is essential to quantify the load flexibility capability of grocery stores. Advanced controls can optimize energy consumption by responding to load shedding, shifting, and DR events, as well as daily Time-of-Use (TOU) rates without compromising food safety. Using both quantitative data and interviews with community-based organizations, we developed a full-size store model and two small store models with controlled refrigerated cases, HVAC, and lighting systems based on actual grocery store properties. Through simulations, we have assessed load flexibility strategies with varied DR events. The results highlight potential for energy and peak reduction with advanced or basic controls. However, interviews and data indicate that more support is needed to make DR strategies consistently accessible to small grocery stores.

demand flexibility↗
NASA NTRS1993

Path planning for robotic truss assembly

A new Potential Fields approach to the robotic path planning problem is proposed and implemented. Our approach, which is based on one originally proposed by Munger, computes an incremental joint vector based upon attraction to a goal and repulsion from obstacles. By repetitively adding and computing these 'steps', it is hoped (but not guaranteed) that the robot will reach its goal. An attractive force exerted by the goal is found by solving for the the minimum norm solution to the linear Jacobian equation. A repulsive force between obstacles and the robot's links is used to avoid collisions. Its magnitude is inversely proportional to the distance. Together, these forces make the goal the global minimum potential point, but local minima can stop the robot from ever reaching that point. Our approach improves on a basic, potential field paradigm developed by Munger by using an active, adaptive field - what we will call a 'flexible' potential field. Active fields are stronger when objects move towards one another and weaker when they move apart. An adaptive field's strength is individually tailored to be just strong enough to avoid any collision. In addition to the local planner, a global planning algorithm helps the planner to avoid local field minima by providing subgoals. These subgoals are based on the obstacles which caused the local planner to fail. A best-first search algorithm A* is used for graph search.

Sanderson, Arthur C.↗
DOE OSTI2021

Electric Water Heaters for Transactive Systems: Model Evaluations and Performance Quantification

Electric water heaters (EWHs) are opportune appliances for implementing demand-side control. EWH models serve as a fundamental step toward accurately estimating EWH flexibility potential and designing proper control strategies. Existing studies have adapted numerous modeling approaches in evaluating the potential of EWHs for a variety of grid applications. This paper presents an analytical study that evaluates the performance of state-of-art EWH models in terms of accuracy and computational complexity for adaptation in evaluation studies for the transactive system. The work proposes a transactive control strategy that optimally utilizes the thermal inertia of EWHs for providing grid services. Here, the performance of the control strategy and the impact of modeling accuracy is evaluated for device-level and feeder-level use cases using the IEEE 123 node test distribution system appropriately populated with EWHs. The simulation results illustrate the effectiveness of the control strategy in reducing the feeder demand during peak period by 13% and also quantities the impact of using simplified modeling approaches for determining the potential of EWHs for providing grid services.

42 ENGINEERING↗
DOE OSTI2021

Domain patterns and super-elasticity of freestanding BiFeO 3 membranes via phase-field simulations

Super-elasticity of functional ferroelectric oxides offers promises for integrating ferroelectric films into flexible electronics. However, super-elastic deformation is a complex phenomenon related to possibly multiple concurrent mechanisms. Fundamentally understanding how multiple mechanisms contribute to the super-elasticity of ferroelectric oxides is crucial to realizing their potential flexible electronic applications. In this study, we employ phase-field simulations to model the dynamics of ferroelectric domain patterns of freestanding BiFeO 3 membranes to understand the origin of their super-elasticity under substantial bending deformation (5% strain). It is demonstrated that both a reversible Rhombohedral-Tetragonal (R-T) phase transition and a nearly reversible domain evolution of BiFeO 3 membranes contribute to accommodating the large deformation and thus their super-elasticity. The dynamics of domain evolution also reveal the formation of an exotic ferroelectric vortex and polarization rotation before the phase transition. We constructed a diagram of phases and domain patterns as a function of the membrane thickness and bending angle, which allows one to readily predict the emergence of T phase and ferroelectric vortex in bent BFO membranes. These results not only provide fundamental understanding of mesoscale super-elastic mechanisms but also reveal exotic domain states of ferroelectric membranes.

36 MATERIALS SCIENCE↗
DOE OSTI2024

The Lithuania 100% Renewable Energy Study - Interim Results: Electricity System Scenarios for 2030 [Slides]

Lithuania's Energy Vision aims to achieve self-sufficiency in electricity generation by 2035 and transition to 100% renewable energy as soon as possible while maintaining affordability, reliability, and energy security. The Lithuania Energy Agency (LEA) is partnering with the National Renewable Energy Laboratory (NREL) to conduct the Lithuania 100% Renewable Energy Study (Lithuania 100) to provide evidence-based analysis for development of Lithuania's National Energy Independence Strategy. The Lithuania 100 Study leverages unique tools and capabilities of NREL to provide rigorous technical analysis of clean energy policies to achieve 100% renewable energy, and assess impacts on electricity grid operations, hydrogen system development, electricity distribution networks, air quality, and human health outcomes. The study is supported by a stakeholder committee chaired by the Ministry of Energy of Lithuania and implemented by four technical working groups. This report provides highlights of key interim results from modeling of Lithuania's near-term electricity grid through the year 2030. Results show that Lithuania has sufficient renewable energy potential, flexible generation capacity, and interconnection with neighboring European Union countries to reliably meet projected 2030 electricity demand with 100% renewable energy. A range of scenarios were modeled, each of which achieves at least 100% renewable energy in electricity, on average over the year, by 2030. Potential demands for hydrogen across industrial and transportation sectors were also evaluated, as well as the cost of hydrogen produced in Lithuania by 2030.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Advanced co-simulation framework for assessing the interplay between occupant behaviors and demand flexibility in commercial buildings

With buildings contributing significantly to electricity usage, enabling demand flexibility becomes a challenge, especially when accounting for occupant comfort. This study introduces an innovative co-simulation framework integrating multiple models: heating, ventilation, and air conditioning (HVAC) system, building zone load, indoor airflow, supervisory control, and occupant comfort and behavior. Uniquely, this framework allows for a comprehensive and dynamic analysis of building systems and occupant interactions in demand response events. Using this framework, we conducted a case study using a typical small office building model. Specifically, we focused on three areas: (1) the impact of indoor airflow modeling on energy use, occupant comfort, and behaviors forecasting, (2) the impact of occupant behaviors on demand flexibility, and (3) occupant comfort and behaviors under demand response events. Key performance indicators such as energy use, flexibility factor, durations of occupant discomfort and occupant behaviors were analyzed. Our findings indicated variations in energy usage and occupant comfort within demand flexibility events, marked by uncertainty boundaries, with variability in demand shedding up to 57.9%. Here, we concluded that this framework is suitable for analyzing typical commercial buildings and their HVAC systems in terms of demand flexibility potential under the impact of occupant behaviors.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗