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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 973 records · Page 54

Impedance Analysis and PHIL Demonstration of Reactive Power Oscillations in a Wind Power Plant Using a 4-MW Wind Turbine

This paper presents impedance-based analysis, mitigation, and power-hardware-in-the-loop (PHIL) demonstration of reactive power oscillations in a wind power plant using a 4-MW Type III wind turbine drivetrain. Because such low-frequency oscillations result from interactions among slower control loops of wind turbines regulating phasor quantities—active and reactive power output of the wind turbine and the magnitude of voltages at the point of interconnection (POI)—a new type of admittance is defined in terms of phasor quantities for their analysis. The so-called power-domain admittance of a wind turbine is defined as the transfer function from the frequency and magnitude of voltages at the POI to the active and reactive power output of the turbine. The power-domain admittance responses of the 4-MW wind turbine are measured using a 7-MVA grid simulator to identify the source of the reactive power oscillations. Power-domain impedance analysis and PHIL experiments are performed to explain how a resonant mode manifests as turbine-to-turbine and plant-to-grid reactive power oscillations. It is discovered that weaker grids exhibiting high inductive impedance mitigate oscillations in the reactive power output of wind power plants; however, a higher grid impedance does not help in damping turbine-to-turbine reactive power oscillations. This paper presents a simple droop-based solution to eliminate both turbine-to-turbine and plant-to-grid reactive power oscillations.

17 WIND ENERGY↗

Detailed Hydrodynamic Feasibility Assessment for Leque Island and Zis a Ba Restoration Projects

Numerous restoration projects are underway in Puget Sound, Washington, USA with the goal of re-establishing intertidal wetlands that were historically lost due to dike construction for flood protection and agricultural development. One such effort is the restoration effort within the Stillaguamish Delta, benefitting from the cumulative effects from the Leque Island and zis a ba restoration projects. The preferred restoration design calls for the removal of perimeter dikes at the two sites and the creation of tidal channels to facilitate the drainage of tidal flows. A 3-D high-resolution unstructured-grid coastal ocean model based on FVCOM was developed to evaluate the hydrodynamic response of the estuary to restoration alternatives. A series of hydrodynamic modeling simulations were then performed to quantify the hydrodynamic response of the nearshore restoration project, such as periodic inundation, suitable currents, and desired habitat/salinity levels. Sediment impacts were also examined, including the potential for excessive erosion or sedimentation requiring maintenance. Simulation results indicate that the preferred alternative scenario provides the desired estuarine response, which is consistent with the planned design. A decrease in velocities and bed shear in the main river channels was noted for the restored condition associated with the increased inundation of tidal flat area and reduced tidal flows through the main channels. High bed shear near the restored tidal channel entrances indicates that the inlets may evolve in size until equilibrium is established.

hydrodynamics, feasibility assessments, nearshore ↗

Effect of Carbon Nanofiber Clustering on the Micromechanical Properties of a Cement Paste

The use of carbon nanofibers (CNFs) in cement systems has received significant interest over the last decade due to their nanoscale reinforcing potential. However, despite many reports on the formation of localized CNF clusters, their effect on the cement paste micromechanical properties and relation to the mechanical response at the macroscopic scale are still not fully understood. In this study, grid nanoindentation coupled with scanning electron microscopy and energy dispersive spectroscopy was used to determine the local elastic indentation modulus and hardness of a portland cement paste containing 0.2% CNFs with sub-micro and microscale CNF clusters. The presence of low stiffness and porous assemblage of phases (modulus of 15–25 GPa) was identified in the cement paste with CNFs and was attributed primarily to the interfacial zone surrounding the CNF clusters. The CNFs favored the formation of higher modulus C–S–H phases (>30 GPa) in the bulk paste at the expense of the lower stiffness C–S–H. Nanoindentation results combined with a microscale–macroscale upscaling homogenization method further revealed an elastic modulus of the CNF clusters in the range from 18 to 21 GPa, indicating that the CNF clusters acted as compliant inclusions relative to the cement paste.

36 MATERIALS SCIENCE↗

A detailed model for simulation of catchment scale subsurface hydrologic processes

A catchment scale numerical model is developed based on the three-dimensional transient Richards equation describing fluid flow in variably saturated porous media. The model is designed to take advantage of digital elevation data bases and of information extracted from these data bases by topographic analysis. The practical application of the model is demonstrated in simulations of a small subcatchment of the Konza Prairie reserve near Manhattan, Kansas. In a preliminary investigation of computational issues related to model resolution, we obtain satisfactory numerical results using large aspect ratios, suggesting that horizontal grid dimensions may not be unreasonably constrained by the typically much smaller vertical length scale of a catchment and by vertical discretization requirements. Additional tests are needed to examine the effects of numerical constraints and parameter heterogeneity in determining acceptable grid aspect ratios. In other simulations we attempt to match the observed streamflow response of the catchment, and we point out the small contribution of the streamflow component to the overall water balance of the catchment.

Paniconi, Claudio↗

Distribution Grid Incentive Design with Unknown Agent Behavior

Motivation: During extreme events, traditional grid regulation methods (e.g., energy prices, net power injection limits) may be insufficient. While system operators typically lack control over end-user grid interactions, (e.g., energy demand), incentives can influence behavior - for example, a user that receives a grid-driven incentive may adjust their consumption or expose relevant control variables in response. Problem: Optimize for the best incentive subject to system stability constraints. However, user behavior is unknown to the SO - i.e., for a given incentive, the amount of curtailed load or control variables exposed is unknown.

feedback based control↗

Dynamically Learning Incentives for Load Control

As electrical generation becomes more distributed and volatile, and loads become more uncertain, controllability of distributed energy resources (DERs), regardless of their ownership status, will be necessary for grid reliability. Grid operators lack direct control over end-users' grid interactions, such as energy usage, but incentives can influence behavior -- for example, an end-user that receives a grid-driven incentive may adjust their consumption or expose relevant control variables in response. A key challenge in studying such incentives is the lack of data about human behavior, which usually motivates strong assumptions, such as distributional assumptions on compliance or rational utility-maximization. In this paper, we propose a general incentive mechanism in the form of a constrained optimization problem -- our approach is distinguished from prior work by modeling human behavior (e.g., reactions to an incentive) as an arbitrary unknown function. We propose feedback-based optimization algorithms to solve this problem that each leverage different amounts of information and/or measurements. We show that each converges to an asymptotically stable incentive with (near)-optimality guarantees given mild assumptions on the problem. Finally, we evaluate our proposed techniques in voltage regulation simulations on standard test beds. We test a variety of settings, including those that break assumptions required for theoretical convergence (e.g., convexity, smoothness) to capture realistic settings. In this evaluation, our proposed algorithms are able to find near-optimal incentives even when the reaction to an incentive is modeled by a theoretically difficult (yet realistic) function.

demand response↗

A Community-Based Approach to Leading the Nation in Smart Energy Use

Project Objectives The AEP Ohio gridSMART® Demonstration Project (Project) achieved the following objectives: • Built a secure, interoperable, and integrated smart grid infrastructure in northeast central Ohio that demonstrated the ability to maximize distribution system efficiency and reliability and consumer use of demand response programs that reduced energy consumption, peak demand, and fossil fuel emissions. • Actively attracted, educated, enlisted, and retained consumers in innovative business models that provided tools and information reducing consumption and peak demand. • Provided the U.S. Department of Energy (DOE) information to evaluate technologies and preferred smart grid business models to be extended nationally. Project Description Ohio Power Company (the surviving company of a merger with Columbus Southern Power Company), doing business as AEP Ohio (AEP Ohio), took a community-based approach and incorporated a full suite of advanced smart grid technologies for 110,000 consumers in an area selected for its concentration and diversity of distribution infrastructure and consumers. It was organized and aligned around: • Technology, implementation, and operations • Consumer and stakeholder acceptance • Data management and benefit assessment Combined, these functional areas served as the foundation of the Project to integrate commercially available products, innovative technologies, and new consumer products and services within a secure two-way communication network between the utility and consumers. The Project included Advanced Metering Infrastructure (AMI), Distribution Management System (DMS), Distribution Automation Circuit Reconfiguration (DACR), Volt VAR Optimization (VVO), and Consumer Programs (CP). These technologies were combined with two-way consumer communication and information sharing, demand response, dynamic pricing, and consumer products, such as plug-in electric vehicles and smart appliances. In addition, the Project incorporated comprehensive cyber security capabilities, interoperability, and a data assessment that, with grid simulation capabilities, made the demonstration results an adaptable, integrated solution for AEP Ohio and the nation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Laboratory Testing of Demand-Response Enabled Household Appliances

With the advent of the Advanced Metering Infrastructure (AMI) systems capable of two-way communications between the utility's grid and the building, there has been significant effort in the Automated Home Energy Management (AHEM) industry to develop capabilities that allow residential building systems to respond to utility demand events by temporarily reducing their electricity usage. Major appliance manufacturers are following suit by developing Home Area Network (HAN)-tied appliance suites that can take signals from the home's 'smart meter,' a.k.a. AMI meter, and adjust their run cycles accordingly. There are numerous strategies that can be employed by household appliances to respond to demand-side management opportunities, and they could result in substantial reductions in electricity bills for the residents depending on the pricing structures used by the utilities to incent these types of responses.The first step to quantifying these end effects is to test these systems and their responses in simulated demand-response (DR) conditions while monitoring energy use and overall system performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Indoor Wireless Localization of Uncooperative Sources Using a Ray Tracing Model

Indoor geolocation of radio frequency (RF) trans- mitters is challenging due to site-specific multipath effects, especially when the sources are uncooperative. A source being uncooperative means that a-priori the transmit time, location, and power are unknown. It is proposed to use a site-specific ray tracing model to generate realistic indoor RF responses, perform geolocation using multiple methods, and compare their performance. This work will look at two types of geolocation algorithms: (1) time-difference of arrival (TDOA) and (2) re- ceived signal strength Indicator (RSSI) fingerprinting or pattern- matching-based methods. An indoor space will be simulated with a grid of fixed receivers and a grid of transmit locations using Remcom’s Wireless InSite. Using the output of the Wireless InSite simulation the response from any given transmit location can be generated and used to evaluate geolocation performance.

indoor source localization, Wireless InSite, re- c↗

CRADA Number NFE-19-07846 with Grid Fruit, LLC (CRADA Final Report)

Cooperative Research and Development Agreement (CRADA) NFE-19-07846 between Oak Ridge National Laboratory (ORNL) and Grid Fruit, LLC (Grid Fruit) focused on simulating, monitoring, and adjusting controls of commercial refrigerator and freezer systems to provide load flexibility and demand response services from these machines. Viewing these medium and low-temp coolers as thermal masses, the volumes of chilled air in these coolers make them time-shiftable loads ripe for deployment at optimal times. Grid Fruit is a startup company developing methods to schedule the chilling cycles (e.g., in “build load” and “shed load” grid events) to provide energy efficiency, peak shifting, and other benefits both to the grid and the broader environment. These benefits can be magnified by coordinating chillers with HVAC, lights, computers, and other loads. Grid Fruit completed simulations and then selected and ordered controls hardware to prove the technology were successful, but the diversity of chiller models in the field without digital controls, as well as limited market demand at present, make further exploration necessary before commercialization.

42 ENGINEERING↗

Occupant-Centric Demand Response for Thermostatically-Controlled Home Loads

Efficiently managing energy usage to balance supply and demand on the electric grid is crucial, especially with the widespread deployment of distributed variable renewable electricity generation. This paper introduces two duty-cycle control methods for heating systems, adjusting thermostat setpoints to limit and shift electricity demand. The control approaches employ innovative techniques, such as adaptive duty cycling, to prioritize household thermal comfort while reducing peak demand. These control methods can respond to signals from the electric grid, including demand targets and time-of-use tariffs, and were tested physically on an electric furnace and heat pump in a test home during winter conditions in 2021 and 2022. The results are given as average demand reductions and energy use impacts with respect to the average indoor-outdoor temperature difference during the control period. For heat pumps, demand limiting control reduced power by 18.5% and 23.3% for indoor-outdoor temperature differences of 30°F and 40°F. Preheating-based demand shifting achieved reductions of 34.8% and 33.2% for the same temperature differences. Electric furnace tests showed demand reductions of 33.8% and 25.3% for demand limiting, and 56.1% and 45.7% for preheating-based demand shifting. These findings highlight the potential for innovative control methods to enhance grid efficiency and reduce energy consumption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

WE-E-BRE-06: High-Dose Microbeam Radiation Induces Different Responses in Tumor Microenvironment Compared to Conventional Seamless Radiation in Window Chamber Tumor Models

Purpose: Microbeam radiation therapy and GRID therapy are different forms of Spatially-Fractioned Radiation Therapy (SFRT) that is fundamentally different from the conventional seamless and temporally fractionated radiation therapy. SFRT is characterized by a ultra-high dose (10s –100s Gy) dose single treatment with drastic inhomogeneity pattern of given spatial frequencies. Preclinical and limited clinical studies have shown that the SFRT treatments may offer significant improvements in reducing treatment toxicity, especially for those patients who have not benefited from the state-of-the-art radiation therapy approaches. This preliminary study aims to elucidate the underlying working mechanisms of SFRT, which currently remains poorly understood. Methods: A genetically engineered 4T1 murine mammary carcinoma cell line and nude mice skin fold window chamber were used. A nanotechnology-based 160kV x-ray irradiator delivered 50Gy (entrance dose) single treatments of microbeam or seamless radiation. Animals were in 3 groups: mock, seamless radiation, and 300μm microbeam radiation. The windows were imaged using a hyperspectral system to capture total hemoglobin/saturation, GFP fluorescence emission, RFP fluorescence emission, and vessel density at 9 time points up to 7 days post radiation. Results: We found unique physiologic changes in different tumor/normal tissue regions and differential effects between seamless and microbeam treatments. They include 1) compared to microbeam and mock radiation seamless radiation damaged more microvasculature in tumor-surrounding normal tissue, 2) a pronounced angiogenic effect was observed with vascular proliferation in the microbeam irradiated portion of the tumor days post treatment (no such effect observed in seamless and mock groups), and 3) a notable change in tumor vascular orientation was observed where vessels initially oriented parallel to the beam length were replaced by vessels running perpendicular to the irradiation portion of the tumor. Conclusion: Our preliminary study indicated that microbeam radiation modified tumor microenvironment in ways significantly different than of the conventional seamless radiation.

60 APPLIED LIFE SCIENCES↗

Clean Grid Vision: A U.S. Perspective - Chapter 4. Demand-Side Development

This chapter focuses on recent developments on the demand side of the electricity system in the United States and beyond. After decades of slow-moving change in power system technology, business models, regulatory structures, and even financing schemes, changes on the demand side are accelerating rapidly. These changes are also more tightly linking the supply side with the demand side. This chapter provides high-level summaries of traditional subjects like demand-side management, which includes energy efficiency and demand response, and then transition to a subject that has gathered increasing attention as the most dynamic change likely to impact power systems in the coming decades: beneficial electrification. In each case, we attempt to address the impacts on system flexibility to the degree possible. These demand-side subjects are widely considered essential elements of a clean grid strategy.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Defining and applying an electricity demand flexibility benchmarking metrics framework for grid-interactive efficient commercial buildings

Building demand flexibility (DF) research has recently gained attention. To unlock building DF as a predictable grid resource, we must establish a quantitative understanding of the resource size, performance variability, and predictability based on large empirical datasets. Researchers have proposed various sets of theoretical metrics to measure this performance. Some metrics have been applied to simulation results, but most fall short of exploring the complexities in real building applications. There are practical metrics used in individual demand response field studies but they alone cannot fulfil the job of DF benchmarking across a diverse group of buildings. The electrical grid's geographically diverse and changing nature presents challenges to comparing building DF performance measured under different conditions (i.e., benchmarking DF). To address this challenge, a novel DF benchmarking framework focused on load shedding and shifting is presented; the foundation is a set of simple, proven single-event metrics with attributes describing event conditions. These enable benchmarking and visualization in different dimensions for identifying trends that represent how these attributes influence DF. To test its feasibility and scalability, the DF framework was applied to two case studies of 11 office buildings and 121 big-box retail buildings with demand response participation data. Furthermore, these examples provided a pathway for using both building level benchmarking and aggregation to extract insights into building DF about magnitude, consistency, and influential factors. Potential applications of the framework and real-world values have been identified for grid and building stakeholders.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Machine Learning-based Approach to Predict the Aggregate Flexibility of HVAC Systems

Use of renewable energy resources can play a significant role in mitigation of climate change since they reduce the dependency on fossil fuels. However, high penetration of renewable energy resources into the power grid may cause some reliability problems. Ancillary services are key to realize the potential of renewable resources without disturbing the grid reliability. In recent years, many control approaches focused on exploiting the aggregate flexible heating, ventilation, and air-conditioning (HVAC) loads of buildings. However, there are still research gaps in assessing in advance the resulting indoor temperature responses for given total power and weather profiles before implementing the controls in the buildings. Such an assessment is critical to guarantee satisfying both the grid related objective (reliability) and the building related objective (occupants' comfort). Towards addressing this research gap, this paper presents a machine-learning approach for predicting the ratings of indoor temperature responses. In this approach, a prediction model was developed using a dataset generated by a set of model-free control simulations. The developed model achieved high prediction accuracy and showed the potential of the proposed approach.

Amasyali, Kadir↗

Modeling of GE Appliances: Final Presentation

The Energy Information Administration (EIA) estimates that electricity use will increase by more than 30 percent by 2035, and that residential electricity usage will increase by 23 percent. During this time, peak electricity demand is expected grow at an even greater rate, requiring significant investment in system capacity. In addition, increased penetration of intermittent renewable resources will increase system variability, requiring additional resources to mitigate the variability associated with generator output. Widespread adoption of demand response (DR) enabled appliances, thermostats, and other demand-side resources can result in significant reduction to peak electrical demand and provide potential grid stabilization benefits. The key to adoption is to provide this resource at a cost commensurate with traditional grid capabilities, and to appropriately share both the costs and the benefits between the consumer and the service provider (i.e., the utility). However, the business model for investing in demand-side resources cannot be determined without an estimation of the possible technical benefits and how those benefits translate to monetary value in current electrical market structures. GE Appliances has developed a line of appliances that will have the capability of offering several levels of demand reduction actions based on information received from the utility grid, often in the form of price or grid status. However due to a number of factors, including the number of DR-enabled appliances available at any given time, the reduction of diversity factor due to the synchronizing control signal, and the percentage of consumers who may override the utility signal, it can be difficult to predict the aggregate response of a large number of residences. The effects of these behaviors have been modeled and simulated in the Pacific Northwest National Laboratory (PNNL) developed open-source software, GridLAB-D™, including evaluation of appliance controls, improvement to current algorithms, and development of aggregate control methodologies. The results of these simulations provide an estimation of the possible technical benefits (e.g., peak load reduction) attributable to smart appliances, but do not describe the monetary value of these services. This report is the final in a series of three reports funded by U.S. Department of Energy Office of Electricity Delivery and Energy Reliability (DOE-OE) in collaboration with GE Appliances’ through a Cooperative Research and Development Agreement (CRADA) to describe the potential of GE Appliances’ DR-enabled appliances to provide benefits to the utility grid.

Demand Response↗

Model Based Predictive Control for Frequency Support in Multi-port Autonomous Reconfigurable Solar Plants

Primary frequency support functionality can be an added advantage for any new grid integrated power electronics resource. With increased penetration of power electronics resources, inertial and primary frequency response capabilities are decreasing. In this research paper, an advanced model-based predictive control (MBPC) algorithm for providing frequency support to a new topology of integrated photovoltaic(PV), batterybased energy storage systems (ESS), and high-voltage direct current (HV dc) systems called multi-port autonomus reconfigurable solar (MARS) plants is based on the synchronverter-based control. The simulation of MARS-HV dc system with proposed control strategy is simulated and validated for MARS connected to low short circuit ratio (SCR) grids in PSCAD/EMTDC simulation environment. The control algorithm proposed showcases better performance in terms of frequency nadir improvement and frequency steady state improvemnt with respect to no frequency control.

Marthi, Phani Ratna Vanamali↗

Electric Grid Reliability in an Era of Unprecedented Uncertainty: A Review of Advances in Electric Sector Resource Adequacy Assessment and Planning

Recent changes to the principal causes of energy shortage events on the electric grid have necessitated are thinking of paradigms for resource adequacy (RA) assessment and the related topic of procurement of a reliable portfolio. Prior studies have laid out elements of a modern paradigm for these planning activities, but there does not exist a comprehensive overview of the topic spanning academic and gray literature, and the relationship of these suggested paradigms to methods used in industry has also not been surveyed. In this paper we review recent literature establishing best practices for RA assessment and reliable portfolio procurement, and survey current practices used in industry in relation to these best practices. We establish seven key best practices for RA assessment, cover a modern methodology for capacity accreditation, and find that industry practices are not far behind the identified best practices, though some key gaps remain. We also present a suggested agenda for both academic research on the topic and opportunities for advancement in the industry.

24 POWER TRANSMISSION AND DISTRIBUTION↗