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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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Geographic Visualization of Power-Grid Dynamics

The visualization enables the simulation analyst to see changes in the frequency through time and space. With this technology, the analyst has a bird's eye view of the frequency at loads and generators as the simulated power system responds to the loss of a generator, spikes in load, and other contingencies. The significance of a contingency to the operation of an electrical power system depends critically on how the resulting tansients evolve in time and space. Consequently, these dynamic events can only be understood when seen in their proper geographic context. this understanding is indispensable to engineers working on the next generation of distributed sensing and control systems for the smart grid. By making possible a natural and intuitive presentation of dynamic behavior, our new visualization technology is a situational-awareness tool for power-system engineers.

Sukumar, SreenivasR.↗
DOE OSTI2015

Geographic Visualization of Power-Grid Dynamics

The visualization enables the simulation analyst to see changes in the frequency through time and space. With this technology, the analyst has a bird's eye view of the frequency at loads and generators as the simulated power system responds to the loss of a generator, spikes in load, and other contingencies. The significance of a contingency to the operation of an electrical power system depends critically on how the resulting tansients evolve in time and space. Consequently, these dynamic events can only be understood when seen in their proper geographic context. this understanding is indispensable to engineers working on the next generation of distributed sensing and control systems for the smart grid. By making possible a natural and intuitive presentation of dynamic behavior, our new visualization technology is a situational-awareness tool for power-system engineers.

Sukumar, Sreenivas R.↗
DOE OSTI2022

Seeking Repeating Anthropogenic Seismic Sources: Implications for Seismic Velocity Monitoring at Fault Zones

Abstract Seismic velocities in rocks are highly sensitive to changes in permanent deformation and fluid content. The temporal variation of seismic velocity during the preparation phase of earthquakes has been well documented in laboratories but rarely observed in nature. It has been recently found that some anthropogenic, high‐frequency (>1 Hz) seismic sources are powerful enough to generate body waves that travel down to a few kilometers and can be used to monitor fault zones at seismogenic depth. Anthropogenic seismic sources typically have fixed spatial distribution and provide new perspectives for velocity monitoring. In this work, we propose a systematic workflow to seek such powerful seismic sources in a rapid and straightforward manner. We tackle the problem from a statistical point of view, considering that persistent, powerful seismic sources yield highly coherent correlation functions (CFs) between pairs of seismic sensors. The algorithm is tested in California and Japan. Multiple sites close to fault zones show high‐frequency CFs stable for an extended period of time. These findings have great potential for monitoring fault zones, including the San Jacinto Fault and the Ridgecrest area in Southern California, Napa in Northern California, and faults in central Japan. However, extra steps, such as beamforming or polarization analysis, are required to determine the dominant seismic sources and study the source characteristics, which are crucial to interpreting the velocity monitoring results. Train tremors identified by the present approach have been successfully used for seismic velocity monitoring of the San Jacinto Fault in previous studies.

58 GEOSCIENCES↗
DOE OSTI2022

A Hybrid Reinforcement Learning-MPC Approach for Distribution System Critical Load Restoration: Preprint

This paper proposes a hybrid control approach for distribution system critical load restoration, combining deep reinforcement learning (RL) and model predictive control (MPC) aiming at maximizing total restored load following an extreme event. RL determines a policy for quantifying operating reserve requirements, thereby hedging against uncertainty, while MPC models grid operations incorporating RL policy actions, i.e., the reserve requirement, renewable (wind and solar) power predictions, and load demand forecasts. We formulate the reserve requirement determination problem as a sequential decision making problem based on the Markov Decision Process (MDP) and design an RL learning environment based on the OpenAI Gym framework and MPC. The RL agent reward and MPC objective function aim to maximize and monotonically increase total restored load and minimize load shedding and renewable power curtailment. The RL algorithm is trained off-line using historical forecast of renewable generation and load demand. The method is tested using a modified IEEE 13-bus distribution test feeder containing wind turbine, photovoltaic, microturbine and battery. Case studies demonstrated that the proposed method outperforms other operating reserve determination methods.

distribution system↗
DOE OSTI2018

General Requirements for Designing and Implementing a Cryptography Module for Distributed Energy Resource (DER) Systems

Penetration of distributed energy resources (DERs) is rapidly increasing in the bulk power system (BPS); they are growing to be a significant portion of generation. As such, grid-support capabilities are being developed and implemented. However, as their presence increases, the impact of DERs on the BPS also increases. Therefore, if a disturbance occurs in the DER system, its effects could propagate throughout the BPS. These disturbances could range from equipment malfunctions to resource variability to cyber attacks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Changes in European wind energy generation potential within a 1.5 °C warmer world

Global climate model simulations from the 'Half a degree Additional warming, Prognosis and Projected Impacts ' (HAPPI) project were used to assess how wind power generation over Europe would change in a future world where global temperatures reach 1.5 °C above pre-industrial levels. Comparing recent historical (2006–2015) and future 1.5 °C forcing experiments highlights that the climate models demonstrate a northward shift in the Atlantic jet, leading to a significant (p < 0.01) increase in surface winds over the UK and Northern Europe and a significant (p < 0.05) reduction over Southern Europe. We use a wind turbine power model to transform daily near-surface (10 m) wind speeds into daily wind power output, accounting for sub-daily variability, the height of the turbine, and power losses due to transmission and distribution of electricity. To reduce regional model biases we use bias-corrected 10 m wind speeds. We see an increase in power generation potential over much of Europe, with the greatest increase in load factor over the UK of around four percentage points. Increases in variability are seen over much of central and northern Europe with the largest seasonal change in summer. Focusing on the UK, we find that wind energy production during spring and autumn under 1.5 °C forcing would become as productive as it is currently during the peak winter season. Similarly, summer winds would increase driving up wind generation to resemble levels currently seen in spring and autumn. We conclude that the potential for wind energy in Northern Europe may be greater than has been previously assumed, with likely increases even in a 1.5 °C warmer world. While there is the potential for Southern Europe to see a reduction in their wind resource, these decreases are likely to be negligible.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Visualization and Analytics of Distribution Systems with Deep Penetration of Distributed Energy Resources (VADER)

In its current state, the distribution system is incapable of handling small to moderate amounts of photovoltaic (PV) penetration. This is because it was initially designed for handling passive loads which, at the level of a substation, have low variability and are forecastable with high accuracy. It has been an open loop system with little monitoring and control. With the addition of PV energy sources, the overall scenario will change dramatically due to (1) two way power flow on network; and (2) high aggregate variability. Additionally, changes on the consumption side lead to a number of smart loads, Electric Vehicles (EVs), and Demand Response. These fundamental changes in the characteristics of the generation and consumption of power will lead to a number of practical engineering problems which must be overcome to allow increased penetration of Distributed PV. Solving the unique engineering challenges which arise at moderate levels of PV penetration requires closed loop integration of data from (1) PV sources; (2) customer load data from smart meters; (3) EV charging data; and (4) local and line mounted precision instruments. These data are not traditionally used by utilities in operations since they are ”non-SCADA” and the current grid does not require such levels of control. To integrate this data and provide real time intelligence from these non-SCADA data, we created the Visualization and Analytics of Distribution Systems with Deep Penetration of Distributed Energy Resources (VADER) platform. VADER is a collection of analytics enabled by integration of massive and heterogeneous data streams for granular real-time monitoring, visualization and control of Distributed Energy Resources (DER) in distribution networks. VADER analytics enable utilities to have greater visibility into distributed energy resources. We built several batch- and stream-analytics in VADER which help operators better understand the impact of distributed energy resources on the grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Water and Wastewater Systems as Potential Distributed Energy Resources for California - High-level Feasibility Assessment

Water systems in California are a major electricity user, and electricity costs represent a significant portion of water utilities’ operating costs. Water and wastewater utilities have the capacity to shift demand in response to grid needs or price signals and can generate power through biogas, hydropower or onsite renewable energy systems like solar panels and wind turbines. This report points to some of the most promising opportunity areas for water and wastewater utilities to implement distributed energy resources while also carefully laying out practical considerations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Grey-Box System Identification of Grid-Forming Inverters

This paper demonstrates the use of grey-box system identification methods for simplifying and understanding the nonlinear power dynamics of grid-forming inverters (GFMs). The power and frequency outputs of complex high-order GFM models are fed into system identification software in order to fit them to a predetermined LTI system and learn system parameters such as (synthetic) inertia and droop constants. The same process is then run for a high-order synchronous generator model, and the outputs are fit to the same set of LTI equations. Simulation of a network of GFM inverters with diverse control architecture is also performed for the same process. The intent is threefold: first, to demonstrate the appropriateness of unified LTI models for describing the power and frequency dynamics of individual resources and connected networks, in order to facilitate analysis of larger heterogeneous networked systems; second, to discover the relationship between internal control parameters of GFMs and their externally observed values; and third, to validate that grey-box data-driven system identification techniques can be a valuable tool to discover the values of important parameters in the absence of explicit vendor models.

analytical models↗
DOE OSTI2020

The Economic Accessibility of CO2 Sequestration through Bioenergy with Carbon Capture and Storage (BECCS) in the US

Bioenergy with carbon capture and storage (BECCS) is one strategy to remove CO2 from the atmosphere. To assess the potential scale and cost of CO2 sequestration from BECCS in the US, this analysis models carbon sequestration net of supply chain emissions and costs of biomass production, delivery, power generation, and CO2 capture and sequestration in saline formations. The analysis includes two biomass supply scenarios (near-term and long-term), two biomass logistics scenarios (conventional and pelletized), and two generation technologies (pulverized combustion and integrated gasification combined cycle). Results show marginal cost per tonne CO2 (accounting for costs of electricity and CO2 emissions of reference power generation scenarios) as a function of CO2 sequestered (simulating capture of up to 90% of total CO2 sequestration potential) and associated spatial distribution of resources and generation locations for the array of scenario options. Under a near-term scenario using up to 206 million tonnes per year of biomass, up to 181 million tonnes CO2 can be sequestered annually at scenario-average costs ranging from $62 to $137 per tonne CO2; under a long-term scenario using up to 740 million tonnes per year of biomass, up to 737 million tonnes CO2 can be sequestered annually at scenario-average costs ranging from $42 to $92 per tonne CO2. These estimates of CO2 sequestration potential may be reduced if future competing demand reduces resource availability or may be increased if displaced emissions from conventional power sources are included. Results suggest there are large-scale opportunities to implement BECCS at moderate cost in the US, particularly in the Midwest, Plains States, and Texas.

09 BIOMASS FUELS↗
DOE OSTI2015

Use of the Hugoniot Elastic Limit in Laser Shockwave Experiments to Relate Velocity Measurements

---The Idaho National Laboratory (INL) has been developing a Laser Shock system to characterize interface strength in plate fuel for research reactors around the world [1]. This work is in support of the Unites states High Performance Research Reactor program whose goal is to reduce the risk of proliferation of weapons grade fuel while maintaining reactor performance. The INL has been working with National Research Council Canada (NRC) on this project for the last five years. ---One of the concerns of the project is the difficulty of calibrating and standardizing the laser shock technique. The generation of the stress wave by the laser impinging on the plate surface is complex, with amplitude and shape dependence on numerous factors relating to the temporal and spatial distribution of power in the laser spot, surface treatment, and material properties of the plate. Thus the resulting back-face surface velocity, which is used to measure the time-varying stress field within the plate, is difficult to reproduce across different measurement systems. A technique that can generate or indicate a known shock intensity independent of the generating conditions would be valuable and allow us to directly compare results from different systems. ---A Laser Shock round robin test between the system at NRC and the INL was conducted. The goal of the round robin was to determine if there was any bias between the two systems. During the analysis of the data, it was noted that the Hugoniot Elastic Limit (HEL) was consistent within both system data sets independent of the laser power used. An analytical study under development supports that the HEL in metals could be a robust and simple benchmark to compare stresses generated by different laser shock systems. The HEL is a material property that should be insensitive to differences in the shock laser and surface preparation which enhances the reliability of the resulting HEL velocity measurement. 1. J. M. Lacy, J. A. Smith and B. H. Rabin, "Developing a Laser Shockwave Model for Characterizing Diffusion Bonded Interfaces," The 41st Annual Review of Progress in Quantitative Nondestructive Evaluation," Boise, ID, U.S.A., July 2014.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Optimal Regulation of Virtual Power Plants

This paper develops a real-time algorithmic framework for aggregations of distributed energy resources (DERs) in distribution networks to provide regulation services in response to transmission-level requests. Leveraging online primal-dual-type methods for time-varying optimization problems and suitable linearizations of the nonlinear AC power-flow equations, we believe this work establishes the system-theoretic foundation to realize the vision of distribution-level virtual power plants. The optimization framework controls the output powers of dispatchable DERs such that, in aggregate, they respond to automatic-generation-control and/or regulation-services commands. This is achieved while concurrently regulating voltages within the feeder and maximizing customers' and utility's performance objectives. Convergence and tracking capabilities are analytically established under suitable modeling assumptions. Simulations are provided to validate the proposed approach.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Multi-Megawatt-Scale Power-Hardware-in-the-Loop Interface for Testing Ancillary Grid Services by Converter-Coupled Generation

Power-hardware-in-the-loop (PHIL) is a simulation tool that can support electrical systems engineers in the development and experimental validation of novel, advanced control schemes that ensure the robustness and resiliency of electrical grids that have high penetrations of low-inertia variable renewable resources. With PHIL, the impact of the device under test on a generation or distribution system can be analyzed using a real-time simulator (RTS). PHIL allows for the interconnection of the RTS with a 7 megavolt ampere (MVA) power amplifier to test multi-megawatt renewable assets available at the National Wind Technology Center (NWTC). This paper addresses issues related to the development of a PHIL interface that allows testing hardware devices at actual scale. In particular, the novel PHIL interface algorithm and high-speed digital interface, which minimize the critical loop delay, are discussed.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Multi-Megawatt-Scale Power-Hardware-in-the-Loop Interface for Testing Ancillary Grid Services by Converter-Coupled Generation: Preprint

Power-hardware-in-the-loop (PHIL) is a simulation tool that can support electrical systems engineers in the development and experimental validation of novel, advanced control schemes that ensure the robustness and resiliency of electrical grids that have high penetrations of low-inertia variable renewable resources. With PHIL, the impact of the device under test on a generation or distribution system can be analyzed using a real-time simulator (RTS). PHIL allows for the interconnection of the RTS with a 7 megavolt ampere (MVA) power amplifier to test multi-megawatt renewable assets available at the National Wind Technology Center (NWTC). This paper addresses issues related to the development of a PHIL interface that allows testing hardware devices at actual scale. In particular, the novel PHIL interface algorithm and high-speed digital interface, which minimize the critical loop delay, are discussed.

17 WIND ENERGY↗
DOE OSTI2022

Mitigating the Impacts of Uncertain Geomagnetic Disturbances on Electric Grids: A Distributionally Robust Optimization Approach

Severe geomagnetic disturbances (GMDs) increase the magnitude of the electric field on the Earth’s surface (E-field) and drive geomagnetically-induced currents (GICs) along the transmission lines in electric grids. These additional currents can pose severe risks, such as current distortions, transformer saturation and increased reactive power losses, each of which can lead to system unreliability. Today several mitigation actions (e.g., changing grid topology) exist that can reduce the harmful GIC effects on the grids. Making such decisions can be challenging, however, because the magnitude and direction of the E-field are uncertain and non-stationary. In this paper, we model uncertain E-fields using the distributionally robust optimization (DRO) approach that determines optimal transmission grid operations such that the worst-case expectation of the system cost is minimized. We also capture the effect of GICs on the nonlinear AC power flow equations. For solution approaches, we develop an accelerated column-and-constraint generation (CCG) algorithm by exploiting a special structure of the support set of uncertain parameters representing the E-field. Extensive numerical experiments based on “epri-21” and “uiuc-150” systems, designed for GMD studies, demonstrate (i) the computational performance of the accelerated CCG algorithm, (ii) the superior performance of distributionally robust grid operations that satisfy nonlinear, nonconvex AC power flow equations and GIC constraints, in comparison with standard stochastic programming-based methods during the out-of-sample testing.

42 ENGINEERING↗
DOE OSTI2017

Integrated Smart Distribution RD&D Project Final Technical Report

Title XIII of the Energy Independence and Security Act of 2007 (EISA), tasked OE with accelerating the commercialization, deployment and integration of advanced digital systems that are needed to modernize the nation’s electricity delivery network for enhanced interoperability and cyber security. To support this mandated task, a goal of the SGR&D Program is to develop technology with the ability to dynamically optimize grid operations and resources and incorporate demand response and consumer participation. The majority of historical research and development in the domain of distribution management systems (DMS) had focused on classical, radial and passive networks with one-way power flow from transmission to distribution systems and thus to the end customer. With the focus on customers, a bottom-up approach required a completely new thinking in real-time operations, and automation, of smart distribution systems. Thus, the GE team embarked on a project with a plan of two distinct phases. Work during the first phase concentrated on research and development (R&D) for the first three years. The second phase, lasting approximately two years, accomplished the demonstration of the use cases developed during the first phase, with further sharing and dissemination of the research at industry events. The consolidated technical scope of the project can be summarized into the following six areas: Advanced distribution modeling capability to accurately simulate/model smart grid operations. Accurate representation of the distribution system in real- or near real-time (capture real-time topology). Interoperability with, and seamless communication between, other management systems and databases used by the utility Simulation of distribution systems based on real-time operational planning to analyze the benefits of smart grid assets. Integration of network, market, and renewable resource models for next generation DMS. Management and forecasting of DER (Distributed Generation, Storage, Demand Response).

14 SOLAR ENERGY↗
DOE OSTI2015

Systematic Approach to Better Understanding Integration Costs

This research presents a systematic approach to evaluating the costs of integrating new generation and operational procedures into an existing power system, and the methodology is independent of the type of change or nature of the generation. The work was commissioned by the U.S. Department of Energy and performed by the National Renewable Energy Laboratory to investigate three integration cost-related questions: (1) How does the addition of new generation affect a system's operational costs, (2) How do generation mix and operating parameters and procedures affect costs, and (3) How does the amount of variable generation (non-dispatchable wind and solar) impact the accuracy of natural gas orders? A detailed operational analysis was performed for seven sets of experiments: variable generation, large conventional generation, generation mix, gas prices, fast-start generation, self-scheduling, and gas supply constraints. For each experiment, four components of integration costs were examined: cycling costs, non-cycling VO&M costs, fuel costs, and reserves provisioning costs. The investigation was conducted with PLEXOS production cost modeling software utilizing an updated version of the Institute of Electrical and Electronics Engineers 118-bus test system overlaid with projected operating loads from the Western Electricity Coordinating Council for the Sacramento Municipal Utility District, Puget Sound Energy, and Public Service Colorado in the year 2020. The test system was selected in consultation with an industry-based technical review committee to be a reasonable approximation of an interconnection yet small enough to allow the research team to investigate a large number of scenarios and sensitivity combinations. The research should prove useful to market designers, regulators, utilities, and others who want to better understand how system changes can affect production costs.

24 POWER TRANSMISSION AND DISTRIBUTION↗