Search NASA⌕ Search

SEARCH · Search NASA

Results for “grid flexibility”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Applying Particle Swarm Optimization and Extended Kalman Filtering to Model Kaplan Generation Dynamics for Hydropower Systems

Variable renewable generation is increasing the need for hydropower plants to provide fast and flexible grid support, which places new demands on plant-level dynamic models used for monitoring, control, and operational decision-making. This need is especially important for hydroelectric systems, where turbine and generator dynamics are strongly coupled, nonlinear, and time-varying, making accurate real-time representation difficult. To address this problem, this paper develops a digital twin (DT) framework for a synchronous generator–Kaplan turbine system using an explicit separation of slow turbine dynamics and fast generator dynamics. The turbine subsystem is represented by a six-coefficient model, whose parameters are identified offline using particle swarm optimization, while the generator subsystem is updated online through an extended Kalman filter for real-time state and parameter estimation. These models are integrated within a closed-loop simulation that includes a proportional–integral–derivative–double-derivative governor and excitation system, allowing the DT to track plant behavior under realistic operating conditions. Unlike prior studies that treat turbine and generator modeling separately or rely mainly on simulated inputs, the proposed framework is validated using real operational data from a hydropower plant. Results show that the DT reproduces terminal voltage, active power, and reactive power with a normalized root mean square error of approximately 5%. This hybrid offline–online formulation constitutes the main contribution of the work, providing an adaptive and practically deployable DT for hydropower systems with direct relevance to control improvement, performance monitoring, and grid-support applications under high renewable penetration.

13 HYDRO ENERGY↗
DOE OSTI2025

HP-FLEX: Field Demonstration of the Semantics-Driven Configuration of a Model Predictive Control System to Make Heat Pumps Flexible

Model Predictive Control (MPC) has demonstrated significant potential for optimizing building operations and enabling demand flexibility. However, the widespread adoption of MPC is hindered by complex manual configuration and commissioning processes that must be conducted by control experts working alongside building operators. These challenges drive up costs and reduce scalability, particularly when technical human resources and building automation systems are limited, such as in small and medium commercial buildings (SMCBs). This paper demonstrates how semantic standards, specifically ASHRAE 223P, can accelerate the adoption of MPC applications for load flexibility in SMCBs. The authors present a replicable control framework, titled “HP-FLEX” that leverages a building’s semantic model to bootstrap the required data configuration for an MPC controller developed for optimizing heat pump systems as flexible grid resources. The semantic model helps streamline the deployment workflow, particularly for site setup, data/control commissioning, and model setup. This integration enhances portability, transferability, and scalability of the HP-FLEX MPC, which has been developed to support MPC-based supervisory HVAC controllers in SMCBs. Additionally, the paper details the required building and thermostat metadata information to enable the HP-FLEX MPC based on field demonstrations. The new workflow was tested in a small commercial building located in California, U.S., and demonstrated a load shifting performance of 9% based on a dynamic pricing signal that varies by the hour. This work provides a practical pathway for transitioning sophisticated building applications from custom to standardized semantic representations, supporting the broader adoption of advanced control strategies like MPC. The framework also establishes a foundation for evolving metadata requirements as applications mature while maintaining compatibility with industry standards.

Paul, Lazlo↗
NASA NTRS1985

Adaptive identification and control of structural dynamics systems using recursive lattice filters

A new approach for adaptive identification and control of structural dynamic systems by using least squares lattice filters thar are widely used in the signal processing area is presented. Testing procedures for interfacing the lattice filter identification methods and modal control method for stable closed loop adaptive control are presented. The methods are illustrated for a free-free beam and for a complex flexible grid, with the basic control objective being vibration suppression. The approach is validated by using both simulations and experimental facilities available at the Langley Research Center.

Sundararajan, N.↗
NASA NTRS1988

Analytic redundancy management for systems with appreciable structural dynamics

This paper deals with analytic redundancy management of systems that have appreciable structural dynamics and require active control. The class of systems considered is large, lightweight spacecraft that have large numbers of distributed sensors and actuators. Both preliminary design and on-line operations are studied. For the preliminary design we deal with the placement of the sensor and actuator components on a highly flexible spacecraft. For on-line operation an analytic redundancy management system based on examination of the residuals of a Kalman filter is considered. A large, flexible grid made of overlapping aluminum bars is used to experimentally evaluate this analytic redundancy management system. Results of the experimental evaluation are included in the paper.

Montgomery, Raymond C.↗
NASA NTRS1988

Model reference, sliding mode adaptive control for flexible structures

A decentralized model reference adaptive approach using a variable-structure sliding model control has been developed for the vibration suppression of large flexible structures. Local models are derived based upon the desired damping and response time in a model-following scheme, and variable structure controllers are then designed which employ colocated angular rate and position feedback. Numerical simulations have been performed using NASA's flexible grid experimental apparatus.

Yurkovich, S.↗
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 OSTI2020

Performance Assessments of Demand Flexibility from Grid-Interactive Efficient Buildings: Issues and Considerations

This SEE Action Network report explains basic concepts and fundamental considerations for assessing the actual demand flexibility performance of buildings participating in demand flexibility programs and responding to time-varying retail rates. Demand flexibility is the capability of distributed energy resources (DERs) to adjust a building’s load profile across different timescales. Assessments determine the timing, location, quantity, and quality of grid services provided. The results can be used for financial settlements and to improve performance of demand flexibility, support its consideration in resource potential studies and electricity system planning, and contribute to cost-effectiveness evaluations. While practitioners and regulators regularly find opportunities to improve performance assessments of demand-related services, to a large degree current best practices are sufficient for basic service offerings as demand flexibility is implemented today. However, advances in assessment practices will be required in a future with grid-interactive efficient buildings (GEBs) that provide continuous demand flexibility by integrating multiple DERs and flexibility modes (load shed, load shift, modulate, and generate). Example practices include using new baseline constructs—including whether baselines are even required for certain building flexibility modes or configurations, deploying more advanced metering and analytics, further developing cybersecurity standards, improving communication standards for increased interoperability, and establishing performance metrics and assessment procedures for load modulation as it is more fully defined and implemented. This report provides information on prioritizing and designing performance assessment elements for demand flexibility programs and time-varying retail rates, assessment protocols, and research and development needs. Additional research sponsored by DOE’s Building Technologies Office offers more detailed technical information on assessing performance of demand flexibility, including definition of performance metrics.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Valuing Demand Flexibility During a Grid Disturbance: A Granular Approach to Resilience Valuation

As research continues to investigate how demand flexibility can aid in power system resilience so does the need for an approach to determine the value of resilience. This work utilizes visual modeling principles to model the value exchanges that take place within the system. These models can be used in analysis design as the foundation of a valuation analysis for each participant in the system. Utilizing a consistent approach for valuation will allow for different approaches in improving system resilience to be compared against each other in terms of economic outcomes of participants.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

A Transactive Approach for Service Restoration Utilizing Customer Load Flexibility and Grid-Edge Resources

This paper develops a transactive energy system model to restore electricity to customers in an isolated distribution system after an outage. The model engages a variety of customer types -- prosumers, flexible loads, critical/noncritical customers, and distributed generators -- as active participants in the restoration process. Unlike many existing transactive approaches, the proposed model is developed for service restoration and accounts for various customer types and their autonomy and privacy through an iterative approach to determine the optimal market price, while maintaining system-level power flow and voltage constraints. The advantages of the proposed approach are numerically validated on a modified IEEE 123-bus test system.

distributed energy resources↗
DOE OSTI2024

A Transactive Approach for Service Restoration Utilizing Customer Load Flexibility and Grid-Edge Resources: Preprint

This paper develops a transactive energy system model to restore electricity to customers in an isolated distribution system after an outage. The model engages a variety of customer types -- prosumers, flexible loads, critical/noncritical customers, and distributed generators -- as active participants in the restoration process. Unlike many existing transactive approaches, the proposed model is developed for service restoration and accounts for various customer types and their \textit{autonomy} and \textit{privacy} through an iterative approach to determine the optimal market price, while maintaining system-level power flow and voltage constraints. The advantages of the proposed approach are numerically validated on a modified IEEE 123-bus test system.

distributed energy resources↗
DOE OSTI2026

EXERGETIC: De-Risking Next-Generation Resilient Geothermal Hybrids via At-Scale Evaluation Using Virtual Emulation Digital Twin Environment for Efficient Operation

The DOE-GTO-funded project, award number 5.1.2.12, entitled "EXERGETIC - De-risking Next Generation Resilient Geothermal Hybrids via at-Scale Evaluation Using a Virtual Emulation Digital Twin Environment for Efficient Operation," advances the solution to these challenges by developing and validating a geothermal co-emulation environment implemented at the National Laboratory of the Rockies (NLR)'s Advanced Research on Integrated Energy Systems (ARIES) platform. This framework enables the de-risking of next-generation geothermal and geothermal hybrid systems through high-fidelity modeling, real-time digital emulation, advanced control strategies, and techno-economic assessment. The project focused on geothermal hybrid configurations that integrate geothermal power plants with concentrated solar power and underground thermal energy storage, enabling enhanced efficiency, flexibility, and grid support capabilities. The main goal of this project was the development of a geothermal digital co-emulation environment to demonstrate the technical and economic value of geothermal hybrid systems and their contribution to grid stability and flexibility. The EXERGETIC framework combined physics-based models, controls, and real assets at ARIES, including digital real-time simulators (DRTS), a 20-MW-scale controllable grid interface (CGI), and a 2-MW conventional generator. Detailed transient models were developed for the key subsystems of a hybrid geothermal plant, including parabolic trough solar collectors, reservoir thermal energy storage (RTES), and a binary Organic Rankine Cycle (ORC) power plant. The ORC model explicitly captured thermal inertia and off-design operation and integrated control strategies to dynamically respond to electric load profiles. The models were validated against published experimental and numerical studies, demonstrating strong agreement and confirming the accuracy and robustness of the modeling approach. The resulting digital twin represents geothermal-solar-storage systems at multiple scales (1 MW to 100 MW) and enables realistic emulation of grid-connected operation. The control architecture allows the geothermal resource to provide stable baseload generation, while solar and stored thermal energy supply flexible, dispatchable support during periods of high demand or variable grid conditions. A key contribution of the EXERGETIC project is the demonstration that geothermal hybrid systems can be designed to be active grid assets rather than passive baseload generators. Using the ARIES platform, the digital twin was evaluated under multiple grid scenarios, including load following, voltage support at the distribution level, and frequency response at the transmission level. Results show that hybrid geothermal systems can respond effectively to dynamic grid conditions, providing inertia-like behavior, primary frequency support, and voltage regulation through coordinated control. In addition to the performance and grid services capability analysis of geothermal and hybrid geothermal systems, the EXERGETIC project also focused on scalability and techno-economic analysis of geothermal hybrid plants. In particular, for the scalability analysis, machine-learning (ML)-based surrogate models were trained using data generated from the geothermal digital twin under different grid-connected scenarios and plant capacities. These ML models demonstrated strong interpolation and extrapolation capabilities across plant sizes, accurately reproducing both steady-state and transient responses with very low errors. Regarding the techno-economic analysis, plant performance results were integrated with cost models for hybrid geothermal systems, and the levelized cost of electricity (LCOE) was used as the main economic metric to evaluate system performance across a range of system capacities, solar shares, solar multiples, and storage durations. Results indicate that economies of scale significantly reduce geothermal LCOE as plant capacity increases, with large-scale systems (25-100 MW) achieving substantially lower costs than small plants. Hybridization with solar thermal energy and storage further improves economic performance by increasing capacity utilization and enabling flexible dispatch. In addition, thermal storage plays a critical role in reducing LCOE by maximizing geothermal, solar, and stored energy resources. In summary, the results from this project demonstrate that geothermal hybrid systems represent a promising alternative for increasing the energy conversion efficiency of geothermal technologies, contributing to the preservation of geothermal resources, and supporting the transition of geothermal plants from traditional baseload resources into flexible, resilient, and cost-competitive energy conversion technologies.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

A Transactive Approach for Service Restoration Utilizing Customer Load Flexibility and Grid-Edge Resources

This paper develops a transactive energy system model to restore electricity to customers in an isolated distribution system after an outage. The model is developed to engage a variety of customer types - prosumers, flexible loads, critical/noncritical customers, and distributed generators - as active participants in the restoration process. Unlike many existing transactive approaches, the proposed model is developed for service restoration and accounts for various customer types and their autonomy and privacy through an iterative approach to determine the optimal market price, while maintaining systemlevel power flow and voltage constraints. The advantages of the proposed approach are numerically validated on a modified IEEE 123-bus test system.

distributed energy resources↗
DOE OSTI2022

How to Build a Connected Community: Policies to Promote Grid-interactive Efficient Buildings and Demand Flexibility

Efficient, connected, grid-interactive, smart, and flexible buildings are key to decarbonizing the U.S. energy economy, optimizing energy use, reducing electric consumers’ bills, integrating variable renewable energy resources, and improving the reliability and performance of the nation’s electricity grids. Such grid-interactive efficient buildings have high levels of energy efficiency layered with other distributed energy resources (DERs) and intelligent controls to provide demand flexibility. Policy support is unfolding at the federal, state, and local levels to transform homes and workplaces into state-of-the-art energy-efficient buildings and community-level grid services. This paper starts by describing the potential benefits. Next, it highlights existing policies — with a focus on state-level actions — that support grid-interactive efficient building deployment and demand flexibility. Finally, it identifies current trends and gaps, policies and programs that promote grid-interactive efficient buildings, and aggregations of grid-interactive efficient buildings referred to as Virtual Power Plants.

Schwartz, Lisa C↗
DOE OSTI2022

Distributed Grid Control of Flexible Loads and DERs for Optimized Provision of Synthetic Regulating Reserves

Over the course of this project, we have successfully de-risked our distributed microgrid control architecture by tightly integrating its associated control algorithms into a unified software library, installing the software library on several industrial-grade target hardware platforms, and validating the performance of the resulting microgrid controller in a real-life microgrid. Upon completion of the project, we demonstrated that our distributed control architecture is resilient against (i) failures in control devices, (ii) unreliable communication links, (iii) delays in transmitted data, and (iv) imperfect knowledge of the number of (and state of) generation and load assets in the microgrid. In this final report, we present results from all the milestones that were accomplished over the course of this project.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Concrete Thermal Energy Storage Enabling Flexible Operation without Coal Plant Cycling

The work described in this report is responsive to the Office of Fossil Energy program “Energy Storage for Fossil Power Generation.” The pilot plant built as a result of this project demonstrated the feasibility and performance of a concrete thermal energy storage (CTES) system integrated with a supercritical coal power plant. The 10 MWh electrical (>25 MWh thermal) CTES unit, developed by Storworks Power, was designed to enable flexible operation of coal plants without cycling damage. The project's key technical achievements showcase a significant advancement in energy storage technology. A modular CTES system using 42 “Bolderblocs” units was successfully designed and constructed at Alabama Power’s Plant Gaston Unit 5, with each block containing embedded stainless-steel coils in specialized, cost-effective high-temperature concrete. The system interfaced seamlessly with the plant's 3500 psig (241 barg), 1000°F (538°C) supercritical steam, demonstrating operational flexibility. Over 86 full cycles, the CTES exhibited rapid charging and discharging capabilities, effectively mimicking steam turbine feed conditions and handling varying load profiles and storage durations. Performance validation confirmed the system's ability to consistently meet design target steam conditions of 75 bar-a and ~400°C for nominal baseline discharge. The concrete material withstood repeated thermal cycling without degradation, validating earlier lab-scale tests. Integration of balance of plant components, including a condensate management system with storage tank and air-cooled condenser, minimized plant interfaces and water consumption. A robust control scheme ensured safe, automated operation across various scenarios. Key learnings from the project were invaluable: 1. Initial concrete drying and commissioning procedures were refined for future deployments, enhancing efficiency in subsequent installations. 2. System flexibility exceeded expectations, with rapid response to changing conditions. 3. Design improvements were identified including optimized insulation and piping that will enhance overall system efficiency in future deployments 4. Full cycle thermal roundtrip efficiencies exceeded 88%. While the roundtrip electrical efficiency was somewhat limited by known challenges using input steam, such constraints may be mitigated by swapping steam for hot air as thermal input. 5. A summary of key performance parameters for the pilot test and predicted performance of a full scale commercial system with specified improvements determined from the pilot are shown in Section 8. The project faced challenges, including COVID-19 delays and host plant availability constraints. However, these were overcome through adaptive planning and execution. The successful management of these obstacles demonstrated the resilience and adaptability of the project team and the robustness of the CTES technology. This successful pilot demonstrates the potential for CTES to enhance coal plant flexibility, supporting grid stability as renewable penetration increases. The validated design and operational data provide a solid foundation for scaling up to utility-scale implementations, potentially transforming how thermal plants operate in evolving energy landscapes. The system's ability to rapidly respond to changing grid conditions while maintaining high efficiency makes it a promising solution for balancing intermittent renewable energy sources. Furthermore, the project highlighted the potential for even greater efficiencies in future iterations. The use of air as an input medium could potentially eliminate the limitations observed with steam input, opening new possibilities for energy storage applications beyond coal plant integration. In conclusion, this pilot project not only achieved its primary goals but also uncovered additional benefits and potential applications of the CTES technology. It represents a significant step forward in addressing the challenges of grid stability and flexibility in an increasingly renewable-driven energy landscape.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2026

Flexible AI Models for Grid Resilience

The rapid growth in size and complexity of artificial intelligence (AI) and machine learning (ML) models has led to increased energy demands, posing a threat to the reliability of the existing power grid. This project addresses the challenge of highly intermittent and energy-intensive inference workloads by (1) developing fidelity-adaptive neural networks capable of dynamic response to grid conditions and (2) integrating these networks with power flow simulations to assess their impact on power grid reliability. We will explore both top-down and bottom-up approaches to create hierarchies of submodels that provide a controlled trade-off between power draw and prediction accuracy. The top-down method utilizes NN pruning to reduce a flagship model into progressively smaller, energy-efficient variants. The bottom-up approach employs geometrically principled weight setting strategies to construct depth-efficient models from the ground up. A real-time hardware-in-the-loop (HIL) platform will be developed to simulate a scaled AC power grid, integrating live AI workload power draw and enabling dynamic model switching in response to grid feedback. This work will provide a novel framework for evaluating the impact of flexible AI/ML workloads on grid performance and establish new methodologies for energy-aware computing in data centers. The outcomes will demonstrate that adaptive AI/ML can play a critical role in improving grid stability while advancing NREL's leadership in energy-efficient computing research.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Simulating dispatchable grid services provided by flexible building loads: State of the art and needed building energy modeling improvements

End-use electrical loads in residential and commercial buildings are evolving into flexible and cost-effective resources to improve electric grid reliability, reduce costs, and support increased hosting of distributed renewable generation. This article reviews the simulation of utility services delivered by buildings for the purpose of electric grid operational modeling. We consider services delivered to (1) the high-voltage bulk power system through the coordinated action of many, distributed building loads working together, and (2) targeted support provided to the operation of low-voltage electric distribution grids. Although an exhaustive exploration is not possible, we emphasize the ancillary services and voltage management buildings can provide and summarize the gaps in our ability to simulate them with traditional building energy modeling (BEM) tools, suggesting pathways for future research and development.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗