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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 433 records · Page 24

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DOE OSTI2023

US 2023/0182605 A1 Network constraint energy management system for electric vehicle depot charging and scheduling

Network constraint energy management system for electric vehicle (EV) depot charging and scheduling. In an embodiment, a power schedule is received from an economic dispatch application for a charging depot comprising EV charging station(s) and distributed energy resource(s). The power schedule may be simulated on a distribution network model of the charging depot, according to load flow analysis, to determine whether any grid-code violations occur. In response to the detection of violation(s), a constraint may be generated for each violating node, and the economic dispatch application may be re-executed with the constraint(s) to produce a new power schedule, until no violations are detected. When not all load demand can be satisfied by the power schedule, a charging schedule may be adjusted to ensure that critical energy requirements are satisfied. The final power and charging schedules may be used to schedule and control power generation and charging in the charging depot.

Hafiz, Faeza↗

DOE OSTI2024

Proactive and Reactive Thermal Comfort Behaviors

The expansion of renewable electricity generation, growing demands due to electrification, greater prevalence of working from home, and increasing frequency and severity of extreme weather events, will place new demands on the electric supply and distribution grid. Broader adoption of demand response programs (DRPs) for the residential sector may help meet these challenges; however, experience shows that occupant overrides in DRPs compromises their effectiveness. There is a lack of formal understanding of how discomfort, routines, and other motivations affect DRP overrides and other related human building interactions (HBI). This paper reports preliminary findings from a study of 20 households in Colorado and Massachusetts, US over three months. Participants responded to ecological momentary assessments (EMA) triggered by thermostat interactions and at random times throughout the day. EMAs included Likert-scale questions of thermal preference, preference intensity, and changes to 7 different activity types that could affect thermal comfort, and an opened ended question about motivations of such actions. Twelve tags were developed to categorize motivation responses and analyzed statistically to identify associations between motivations, preferences, and HBI actions. Reactions to changes in the thermal environment were the most frequently observed motivation (118 of 220 responses). On the other hand, almost half (47%) responses were at least partially motivated by non-thermal factors, suggesting limited utility for occupant behavior models founded solely on thermal comfort. Changes in activity level and clothing were less likely to be reported when EMAs were triggered by thermostat interactions, while fan interactions were more likely. Windows, shades, and portable heater interactions had no significant dependence on how the EMA was triggered. These results suggest that better understanding of motivations for HBI may improve effectiveness of demand response programs.

Pathak, Maharshi↗

DOE OSTI2012

Fixed-Speed and Variable-Slip Wind Turbines Providing Spinning Reserves to the Grid: Preprint

As the level of wind penetration increases, wind turbine technology must move from merely generating power from wind to taking a role in supporting the bulk power system. Wind turbines should have the capability to provide inertial response and primary frequency (governor) response so they can support the frequency stability of the grid. To provide governor response, wind turbines should be able to generate less power than the available wind power and hold the rest in reserve, ready to be accessed as needed. This paper explores several ways to control wind turbine output to enable reserve-holding capability. This paper focuses on fixed-speed (also known as Type 1) and variable-slip (also known as Type 2) turbines.

17 WIND ENERGY↗

DOE OSTI2022

GIST (Grid Impedance Scan Tool) [SWR-22-73]

NREL has developed GIST (Grid Impedance Scan Tool) to scan the impedance response of inverter-based resources such as land-based and offshore wind power plants, solar power plants, etc., from their electromagnetic transient simulation models to evaluate their impact on grid stability. GIST can scan impedance response of inverter-based resources from vendor-supplied black-box simulation models without requiring internal proprietary details, enabling detailed stability analysis of power systems with high levels of inverter-based generation.

Shah, Shahil↗

NASA NTRS1995

Algorithms for parallel flow solvers on message passing architectures

The purpose of this project has been to identify and test suitable technologies for implementation of fluid flow solvers -- possibly coupled with structures and heat equation solvers -- on MIMD parallel computers. In the course of this investigation much attention has been paid to efficient domain decomposition strategies for ADI-type algorithms. Multi-partitioning derives its efficiency from the assignment of several blocks of grid points to each processor in the parallel computer. A coarse-grain parallelism is obtained, and a near-perfect load balance results. In uni-partitioning every processor receives responsibility for exactly one block of grid points instead of several. This necessitates fine-grain pipelined program execution in order to obtain a reasonable load balance. Although fine-grain parallelism is less desirable on many systems, especially high-latency networks of workstations, uni-partition methods are still in wide use in production codes for flow problems. Consequently, it remains important to achieve good efficiency with this technique that has essentially been superseded by multi-partitioning for parallel ADI-type algorithms. Another reason for the concentration on improving the performance of pipeline methods is their applicability in other types of flow solver kernels with stronger implied data dependence. Analytical expressions can be derived for the size of the dynamic load imbalance incurred in traditional pipelines. From these it can be determined what is the optimal first-processor retardation that leads to the shortest total completion time for the pipeline process. Theoretical predictions of pipeline performance with and without optimization match experimental observations on the iPSC/860 very well. Analysis of pipeline performance also highlights the effect of uncareful grid partitioning in flow solvers that employ pipeline algorithms. If grid blocks at boundaries are not at least as large in the wall-normal direction as those immediately adjacent to them, then the first processor in the pipeline will receive a computational load that is less than that of subsequent processors, magnifying the pipeline slowdown effect. Extra compensation is needed for grid boundary effects, even if all grid blocks are equally sized.

Vanderwijngaart, Rob F.↗

DOE OSTI2016

Defending the Power Grid from Hackers

A new initiative underway at the National Renewable Energy Laboratory is intended to prevent hackers from gaining control of parts of the nation's power grid, potentially damaging electrical equipment and causing localized power outages. Our nation's power grid is evolving to be more responsive to changing power needs, more able to integrate renewable energy, more efficient, and more reliable. One key element of this evolution is adding communication and control devices to the power grid, closer to the end user, so that utilities have greater situational awareness of the grid and can respond quickly to disturbances. But these new devices and their communications requirements can also open up the power grid to potential cyber attacks.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2016

Analyzing Resiliency of the Smart Grid Communication Architectures

Smart grids are susceptible to cyber-attack as a result of new communication, control and computation techniques employed in the grid. In this paper, we characterize and analyze the resiliency of smart grid communication architecture, specifically an RF mesh based architecture, under cyber attacks. We analyze the resiliency of the communication architecture by studying the performance of high-level smart grid functions such as metering, and demand response which depend on communication. Disrupting the operation of these functions impacts the operational resiliency of the smart grid. Our analysis shows that it takes an attacker only a small fraction of meters to compromise the communication resiliency of the smart grid. We discuss the implications of our result to critical smart grid functions and to the overall security of the smart grid.

None, None↗

DOE OSTI2016

Analyzing Resiliency of the Smart Grid Communication Architectures

Anas AlMajali, Anas↗

DOE OSTI2021

Economic Analysis of an Electric Thermal Energy Storage System Using Solid Particles for Grid Electricity Storage

As renewable power generation becomes the mainstream new-built energy source, energy storage will become an indispensable need to complement the uncertainty of renewable resources to firm the power supply. When phasing out fossil-fuel power plants to meet the carbon neutral utility target in the midcentury around the world, large capacity of energy storage will be needed to provide reliable grid power. The renewable power integration with storage can support future carbon-free utility and has several significant impacts including increasing the value of renewable generation to the grid, improving the peak-load response, and balancing the electricity supply and demand. Long-duration energy storage (10–100 hours duration) can potentially complement the reduction of fossil-fuel baseload generation that otherwise would risk grid security when a large portion of grid power comes from variable renewable sources. Current energy storage methods based on pumped storage hydropower or batteries have many limitations. Thermal energy storage (TES) has unique advantages in scale and siting flexibility to provide grid-scale storage capacity. A particle-based TES system has promising cost and performance for the future growing energy storage needs. This paper introduces the system and components required for the particle TES to be technically and economically competitive. A technoeconomic analysis based on preliminary component designs and performance shows that the particle TES integrated with an efficient air-Brayton combined cycle power system can provide power for several days by low-cost, high-performance storage cycles. It addresses grid storage needs by enabling large-scale grid integration of intermittent renewables like wind and solar, thereby increasing their grid value. The design specifications and cost estimations of major components in a commercial scale system are presented in this paper. The cost model provides insights for further development and cost comparison with competing technologies.

27 ARPA - Advanced Research Projects Agency-Energy↗

DOE OSTI2021

Economic Analysis of a Novel Thermal Energy Storage System Using Solid Particles for Grid Electricity Storage: Preprint

As renewable power generation becomes the mainstream new-built energy source, energy storage will become an indispensable need to complement the uncertainty of renewable resources to firm the power supply. When phasing out fossil-fuel power plants to meet the carbon neutral utility target in the midcentury around the world, large capacity of energy storage will be needed to provide reliable grid power. The integration of renewable power and storage to support future carbon-free utility has several significant and positive impacts including expanding the renewable generation into the grid, improving the peak-load response, and balancing the electricity supply and demand. Long-duration energy storage (10–100 hours duration) can potentially complement the reduction of fossil-fuel baseload generation that otherwise would risk grid security when a large portion of grid power comes from variable renewable sources. Current energy storage methods based on pumped storage hydropower or batteries have many limitations. Thermal energy storage (TES) has unique advantages in scale and siting flexibility to provide grid-scale storage capacity. A particle-based TES system has promising cost and performance for the future growing energy storage needs. This paper introduces the system and components required for the particle TES to be technically and economically competitive. A technoeconomic analysis based on preliminary component designs and performance shows that the particle TES integrated with an efficient air-Brayton combined cycle power system can provide power for several days by low-cost, high-performance storage cycles. It addresses grid storage needs by enabling large-scale grid integration of intermittent renewables like wind and solar, thereby increasing their grid value. The design specifications and cost estimations of major components in a commercial scale system are presented in this paper. The cost model provides insights for further development and cost comparison with competing technologies.

27 ARPA - Advanced Research Projects Agency-Energy↗

DOE OSTI2015

Opportunities for Automated Demand Response in California’s Dairy Processing Industry

During periods of peak electrical demand on the energy grid or when there is a shortage of supply, the stability of the grid may be compromised or the cost of supplying electricity may rise dramatically, respectively. Demand response programs are designed to mitigate the severity of these problems and improve reliability by reducing the demand on the grid during such critical times. In 2010, the Demand Response Research Center convened a group of industry experts to suggest potential industries that would be good demand response program candidates for further review. The dairy industry was suggested due to the perception that the industry had suitable flexibility and automatic controls in place. The purpose of this report is to provide an initial description of the industry with regard to demand response potential, specifically automated demand response. This report qualitatively describes the potential for participation in demand response and automated demand response by dairy processing facilities in California, as well as barriers to widespread participation. The report first describes the magnitude, timing, location, purpose, and manner of energy use. Typical process equipment and controls are discussed, as well as common impediments to participation in demand response and automated demand response programs. Two case studies of demand response at dairy facilities in California and across the country are reviewed. Finally, recommendations are made for future research that can enhance the understanding of demand response potential in this industry.

25 ENERGY STORAGE↗

DOE OSTI2015

Framework for Modeling High-Impact, Low-Frequency Power Grid Events to Support Risk-Informed Decisions

Natural and man-made hazardous events resulting in loss of grid infrastructure assets challenge the electric power grid’s security and resilience. However, the planning and allocation of appropriate contingency resources for such events requires an understanding of their likelihood and the extent of their potential impact. Where these events are of low likelihood, a risk-informed perspective on planning can be problematic as there exists an insufficient statistical basis to directly estimate the probabilities and consequences of their occurrence. Since risk-informed decisions rely on such knowledge, a basis for modeling the risk associated with high-impact low frequency events (HILFs) is essential. Insights from such a model can inform where resources are most rationally and effectively expended. The present effort is focused on development of a HILF risk assessment framework. Such a framework is intended to provide the conceptual and overarching technical basis for the development of HILF risk models that can inform decision makers across numerous stakeholder sectors. The North American Electric Reliability Corporation (NERC) 2014 Standard TPL-001-4 considers severe events for transmission reliability planning, but does not address events of such severity that they have the potential to fail a substantial fraction of grid assets over a region, such as geomagnetic disturbances (GMD), extreme seismic events, and coordinated cyber-physical attacks. These are beyond current planning guidelines. As noted, the risks associated with such events cannot be statistically estimated based on historic experience; however, there does exist a stable of risk modeling techniques for rare events that have proven of value across a wide range of engineering application domains. There is an active and growing interest in evaluating the value of risk management techniques in the State transmission planning and emergency response communities, some of this interest in the context of grid modernization activities. The availability of a grid HILF risk model, integrated across multi-hazard domains which, when interrogated, can support transparent, defensible and effective decisions, is an attractive prospect among these communities. In this report, we document an integrated HILF risk framework intended to inform the development of risk models. These models would be based on the systematic and comprehensive (to within scope) characterization of hazards to the level of detail required for modeling risk, identification of the stressors associated with the hazards (i.e., the means of impacting grid and supporting infrastructure), characterization of the vulnerability of assets to these stressors and the probabilities of asset compromise, the grid’s dynamic response to the asset failures, and assessment of subsequent severities of consequence with respect to selected impact metrics, such as power outage duration and geographic reach. Specifically, the current framework is being developed to;1. Provide the conceptual and overarching technical paradigms for the development of risk models; 2. Identify the classes of models required to implement the framework - providing examples of existing models, and also identifying where modeling gaps exist; 3. Identify the types of data required, addressing circumstances under which data are sparse and the formal elicitation of informed judgment might be required; and 4. Identify means by which the resultant risk models might be interrogated to form the necessary basis for risk management.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Synchronous Machine Governor Upgrade

Conventional generation sources play a critical role in the stability and reliability of the electrical grid, particularly as we transition towards more renewable energy sources. To understand and accurately emulate their behavior for optimizing grid operations and ensuring seamless integration with renewable technologies, it is essential to better emulate the grid- and plant-level impacts of conventional generation sources, such as natural gas (NG) driven heat recovery steam generators (HRSGs) and combustion turbines (CTs). Therefore, a governor model is developed in a programmable logic controller (PLC) to investigate the performance of the conventional generator under various dynamic operating conditions and to identify the impact on grid stability in a controlled environment. The governor model aims to enable the hardware-in-the-loop (HIL) based emulation of these conventional generation sources using the existing 2 MVA synchronous machine/generator that is driven by a flexible 2.5 MW variable speed drive. This setup will allow us to replicate the dynamic characteristics and response behaviors of NG-driven HRSGs and CTs. The controls for the emulated conventional plants follow the industry standard and are adjustable, ensuring they accurately reflect the operational capabilities and limitations of real-world systems. These controls include load-following capabilities, ramp rates, startup and shutdown sequences, and emissions characteristics. By incorporating these adjustable controls, we aim to capture the nuanced impacts of conventional generation, such as their ability to provide ancillary services like frequency regulation, voltage support, and spinning reserve. In this report, we simulate two types of dynamic operations: grid-connected and islanding. For each dynamic operation, representative starting sequences are tested, including turbine purge, ignition, speed ramping up, generator excitation and synchronizing, and breaker close. The HIL based tests provides insights for field deployment, specifically the high-fidelity governor model provides results to predict the potential stability and reliability risk and suggest possible integration measures (e.g., generation and load balancing, tuning of governor control parameters). Ultimately, this enhanced emulation capability will be integrated into our Advanced Research on Integrated Energy Systems (ARIES), enabling us to conduct comprehensive studies on the interactions between conventional and renewable energy sources. By better understanding these interactions, we can develop strategies to optimize the overall performance and reliability of the grid. This will support the deployment of advanced grid management techniques, such as demand response, grid-forming inverters, and energy storage systems. The main contributions are summarized as follows: (1) This report introduces a PLC-based governor model for gas turbines. This model accurately simulates the dynamic behavior of conventional generation sources under various operational scenarios; (2) The model is integrated with an HIL testbed that includes a 2.5 MW variable speed drive and a 2 MVA synchronous machine. This setup enables realistic, real-time emulation of conventional power plants, particularly NG driven HRSGs and CTs; (3) The developed model is adaptable to various gas turbine configurations and allows for precise control over parameters such as MW ramp rates. This flexibility makes it a valuable tool for future research and industry collaboration; and (4) By incorporating the model into the National Renewable Energy Laboratory's Advanced Research on Integrated Energy Systems, the report lays the groundwork for future studies on interactions between conventional and renewable energy sources, enhancing the ability to develop advanced grid management strategies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2012

Reduced-Order Modeling of Aggregated Thermostatic Loads With Demand Response

Demand Response is playing an increasingly important role in smart grid control strategies. Modeling the behavior of populations of appliances under demand response is especially important to evaluate the effectiveness of these demand response programs. In this paper, an aggregated model is proposed for a class of Thermostatically Controlled Loads (TCLs). The model efficiently includes statistical information of the population, systematically deals with heterogeneity, and accounts for a second-order effect necessary to accurately capture the transient dynamics in the collective response. However, an accurate characterization of the collective dynamics however requires the aggregate model to have a high state space dimension. Most of the existing model reduction techniques require the stability of the underlying system which does not hold for the proposed aggregated model. In this work, a novel model reduction approach is developed for the proposed aggregated model, which can significantly reduce its complexity with small performance loss. The original and the reducedorder aggregated models are validated against simulations of thousands of detailed building models using GridLAB-D, which is a realistic open source distribution simulation software. Index Terms – demand response, aggregated model, ancillary

Zhang, Wei↗

NASA NTRS1992

Prediction of asymmetric vortical flows around slender bodies using Navier-Stokes equations

Steady and unsteady asymmetric vortical flows around slender bodies at high angles of attack are solved using the unsteady, compressible, thin-layer Navier-Stokes equations. An implicit, upwind-biased, flux-difference splitting, finite-volume scheme is used for the numerical computations. For supersonic flows past point cones, the locally conical flow assumption have been used for efficient computational studies of this phenomenon. Asymmetric flows past a 5-deg semiapex-angle circular cone at different angles of attack, free-stream Mach numbers, and Reynolds numbers have been studied in responses to different sources of disturbances. The effects of grid fineness and computational domain size have also been investigated. Next, the responses of three-dimensional supersonic asymmetric flow around a 5-deg circular cone at different angles of attack and Reynolds numbers to short-duration sideslip disturbances are presented. The results show that flow asymmetry becomes stronger as the Reynolds number and angles of attack are increased. One of the cases of flow over a cone-cylinder configuration is validated fairly well by experimental data.

Liu, C. H.↗

DOE OSTI2014

Western Wind and Solar Integration Study Phase 3 – Frequency Response and Transient Stability

Power system operators and utilities worldwide have concerns about the impact of high-penetration wind and solar generation on electric grid reliability (EirGrid 2011b, Hydro-Quebec 2006, ERCOT 2010). The stability of North American grids under these conditions is a particular concern and possible impediment to reaching future renewable energy goals. Phase 3 of the Western Wind and Solar Integration Study (WWSIS-3) considers a 33% wind and solar annual energy penetration level that results in substantial changes to the characteristics of the bulk power system, including different power flow patterns, different commitment and dispatch of existing synchronous generation, and different dynamic behavior of wind and solar generation. WWSIS-3 evaluates two specific aspects of fundamental frequency system stability: frequency response and transient stability.

14 SOLAR ENERGY↗

DOE OSTI2015

Grid Integration Studies: Data Requirements, Greening the Grid

A grid integration study is an analytical framework used to evaluate a power system with high penetration levels of variable renewable energy (VRE). A grid integration study simulates the operation of the power system under different VRE scenarios, identifying reliability constraints and evaluating the cost of actions to alleviate those constraints. These VRE scenarios establish where, how much, and over what timeframe to build generation and transmission capacity, ideally capturing the spatial diversity benefits of wind and solar resources. The results help build confidence among policymakers, system operators, and investors to move forward with plans to increase the amount of VRE on the grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Validating Protection System Behavior with Machine Learning in a Master State Overseer

As power system protection devices continue the widespread transition from analog to digital, they become increasingly intricate. The internal functions and communication between critical grid components must now be significantly more complex to keep up with the demands of the modern smart grid. This brings increased difficulty in maintenance and monitoring, making it harder to identify potential misoperation, power anomalies, and cyber threats. Such issues are often only pinpointed after an exhaustive and costly post-mortem analysis, when a major outage or damage has already occurred. A solution is needed for validating protection systems as they operate, independently evaluating grid state and confirming whether the protection system is behaving accordingly. As opposed to incident response, this acts as a constant verification mechanism that raises a flag when subtler issues are noticed, catching them earlier and preventing larger incidents. This work presents the implementation of such a system, expanding on the prototype developed by the authors in a previous paper. This is accomplished with a machine learning (ML) system capable of validating the performance of protection systems by classifying anomalous events and characterizing protection system responses based solely on available current and voltage measurements. Additionally, this system is contextualized within a larger, modular Master State awareness Overseer (MSO) framework, responsible for monitoring, analyzing, and managing an electric grid.

24 - POWER TRANSMISSION AND DISTRIBUTION↗