Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Grid”

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 1,459 records · Page 81
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Design of the new extraction grid for the NIO1 negative ion source

NIO1 is a compact source of negative ions jointly developed by RFX and INFN, to study the physics of production and acceleration of H{sup −} beams. Negative ions, up to 120 mA of current, are extracted from a radiofrequency driven plasma, by means of a gridded electrode (plasma grid, PG) featuring 9 apertures arranged in a 3x3 square lattice. The same aperture pattern is replicated in the following electrodes, allowing ion acceleration up to 60 keV. All electrodes are realized in copper, by electro-deposition technique, leaving empty slots in the metal to place magnets and to flow water for the grid cooling. The first set of electrodes was completed, installed in the source and tested. At the same time, an upgrade of the extraction system was carried out, in order to optimize the beam optics and to explore alternative electrostatic configurations. In particular, the accelerator will be modified by completely replacing the EG grid, exploiting the modularity of NIO1. The new electrode will feature other slots in between apertures, to place additional magnets. This allows testing different magnetic configurations, to optimize electron filtering and residual ion deflection. The present paper describes the theoretical activities driving the design of these new extractors, carried out with most updated numerical codes, and exploiting the synergy with the refined modeling of the 40 A ITER negative ion sources, under development at Consorzio RFX. Beam simulations are performed both with tracing codes (SLACCAD and OPERA) and with particle in cell codes (ACCPIC)

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Fusion energy in an inertial electrostatic confinement device using a magnetically shielded grid

Theory for a gridded inertial electrostatic confinement (IEC) fusion system is presented, which shows a net energy gain is possible if the grid is magnetically shielded from ion impact. A simplified grid geometry is studied, consisting of two negatively biased coaxial current-carrying rings, oriented such that their opposing magnetic fields produce a spindle cusp. Our analysis indicates that better than break-even performance is possible even in a deuterium-deuterium system at bench-top scales. The proposed device has the unusual property that it can avoid both the cusp losses of traditional magnetic fusion systems and the grid losses of traditional IEC configurations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Optimizing Grid Regulation With Gravity Storage Systems: A Comparative Analysis With Different Motor Inertias

The integration of renewable energy sources into power grids necessitates solutions for grid support and stability during fluctuations in electricity generation and demand. Gravity energy storage systems (GESS) are emerging as a promising technology for managing the balance between energy supply and demand. However, their capacity to optimize energy flow and offer voltage and frequency regulation amid imbalances in generation and demand is less reported. This paper investigates the control of GESS for optimizing energy flow during voltage and frequency regulation. The study evaluates the regulation capabilities of GESS with different motor inertias during a Texas grid event: one with a high-speed, low-inertia motor and another with a low-speed, high-inertia motor. Results indicate that both GESS scenarios provide fast frequency response by converting potential energy into kinetic energy and vice versa, with a response time of 1.5 s from the frequency variation. This aligns with grid requirements for primary frequency response from traditional synchronous generators and motors with large inertia. Furthermore, a GESS based on a high-inertia motor may be able to operate over a broader range of frequency variations, whereas a low-inertia system may be limited by thermal constraints of the motor.

frequency regulation↗
DOE OSTI2018

Risk aware net load balancing in micro grids with high DER penetration

The rapid transformation of micro grids due to the accelerated integration of renewables, storage systems and IoT enabled monitoring and control has opened up new opportunities as well as challenges. Future micro grids will be characterized by high DER penetration and will require sophisticated net load balancing frameworks which explicitly consider the errors in prediction of load and generation due to uncertainty in weather conditions while making decisions. Traditional techniques for grid net load management which rely on isolated shaping of load and supply curves are inadequate and inefficient. For micro grids with high PV penetration, the intermittent and unpredictable nature of PV based energy generation can lead to dramatic and sudden supply demand imbalances thus requiring a holistic framework for balancing net load over the entire horizon. In this paper, we develop a sequential decision making framework for net load management that optimally balances the usage of storage and energy market transactions as a mechanism for mitigating supply demand imbalances (net load imbalances) over the horizon. Our framework specifically accounts for prediction uncertainty of future net load imbalances and minimizes the tail end risk of storage shortfall at the end of the horizon. Using qualitative analysis, we show that our framework achieves its objective of minimum cost net load balancing while accounting for the tail end risk.

14 SOLAR ENERGY↗
DOE OSTI2023

Resilient Inverter-Driven Black Start with Collective Parallel Grid-Forming Operation

As modern power systems are experiencing exceptional changes with increasing penetrations of inverter-based resources (IBRs), system restoration using IBRs has received attention. Using local grid-forming (GFM) assets near consumers, engineered to establish grid voltages in the absence of a stiff grid, i.e., bottom-up restoration, a distribution system could obtain high system resilience by not relying on the bulk power system restoration, which requires significant human intervention and procedure. This paper studies the technical feasibility of the novel approach with detailed electromagnetic transient (EMT) simulations. To thoroughly evaluate the potential of GFM inverters and the technical challenges in IBR-driven black start, a detailed three-phase inverter model is developed, including negative-sequence control for voltage balance and a phase-by- phase current limiter to sustain momentary overloading during the black start. To examine dynamic aspects of the black-start process, the EMT simulation also models transformer and motor dynamics to emulate their inrush and startup behaviors as well as network dynamics. In addition, active involvement of grid- following distributed energy resources is also studied to facilitate the black-start process. By allowing multiple GFM inverters to collectively black start without leader-follower coordination, we demonstrate that a system can achieve high resilience even with a fraction of assets lost. Two test cases of inverter-driven black start, using two and one GFM inverters, respectively, for a heavily unbalanced 2-MVA distribution feeder are demonstrated. Takeaways for further study and field deployment are provided.

grid-forming inverter↗
DOE OSTI2017

Potential For Plug-In Electric Vehicles To Provide Grid Support Services

Since the modern-day introduction of plug-in electric vehicles (PEVs), scientists have proposed leveraging PEV battery packs as distributed energy resources for the electric grid. PEV charging can be controlled not only to provide energy for transportation but also to provide grid services and to facilitate the integration of renewable energy generation. With renewable generation increasing at an unprecedented rate, most of which is non-dispatchable and intermittent, the concept of using PEVs as controllable loads is appealing to electric utilities. This additional functionality could also provide value to PEV owners and drive PEV adoption. It has been widely proposed that PEVs can provide valuable grid services, such as load shifting to provide voltage regulation. The objective this work is to address the degree to which PEVs can provide grid services and mutually benefit the electric utilities, PEV owners, and auto manufacturers.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Medium Voltage Converter Inductor Insulation Design Considering Grid Requirements

Medium voltage (MV) SiC devices facilitate direct (without 50-/60-Hz transformer) connection of the power electronics converter to the MV grid using simple topology. Compared to the insulation design of MV inductors that have been widely used in the power system, the insulation design of the MV converter filter inductors has new challenges. Particularly, the grid impact on insulation requirements on converter filter inductors is rarely discussed. This article introduces the insulation design of a grid-side filter inductor for a 13.8-kV power conditioning system converter. The grid insulation requirements, including the short-duration power frequency overvoltage and the lightning impulse voltage, are considered in the design. To meet the requirements, the layer-to-layer insulation, winding-to-core/ground insulation, the air gap discharge between the winding and the core, the local electric field, as well as the interturn transient voltage distribution are considered. Furthermore, the designed inductors are validated by the 46 kV (>1 min) dc hi-pot test, 12-kV ac partial discharge test, one-hour single-phase converter full rating test, as well as three-phase converter full rating test.

42 ENGINEERING↗
DOE OSTI2024

Feedback Optimization of Incentives for Distribution Grid Services

Energy prices and net power injection limitations regulate the operations in distribution grids and typically ensure that operational constraints are met. Nevertheless, unexpected or prolonged abnormal events could undermine the grid's functioning. During contingencies, customers could contribute effectively to sustaining the network by providing services. Herein this paper proposes an incentive mechanism that promotes users' active participation by essentially altering the energy pricing rule. The incentives are modeled via a linear function whose parameters can be computed by the system operator (SO) by solving an optimization problem. Feedback-based optimization algorithms are then proposed to seek optimal incentives by leveraging measurements from the grid, even in the case when the SO does not have a full grid and customer information. Numerical simulations on a standard testbed validate the proposed approach.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Welcome to the Special Issue on Grid-Edge Computing With Behind-the-Meter Resources [Guest Editorial]

The integration of distributed energy resources (DERs), such as solar photovoltaic systems, as well as other synergistic assets, including electric vehicles, energy storage, and smart appliances, in electric power systems has been dramatically increasing in the past few years. These assets have the capability to provide much-needed flexibility to electric power systems for improved grid reliability, resilience, and economic efficiency; however, most of these resources are located behind the meter (BTM) on customer premises, and their flexibility is not fully used in current grid operations. Grid-edge computing plays an important role in unlocking the great benefits and potential that BTM resources could provide to electric power systems by enhancing visibility and controllability at the grid edge.

behind-the-meter resources↗
DOE OSTI2022

Advanced Metering Infrastructure for Distribution Planning and Operation: Closing the Loop on Grid-Edge Visibility

In the recent history of electric utilities, the potential to have visibility of the grid edge is gaining significance for the reliable planning and operation of a clean energy smart grid. Before the recent large-scale customer adoption of distributed energy resources (DERs), distribution networks were planned with a simpler fit-and-forget philosophy. The importance of customer-sited DERs to achieve climate change goals marks a major shift for utility operations. Changes to traditional fit-and-forget planning paradigms require better availability of grid-edge data. Smart metering is an enterprise-wide tool that is enabling visibility when and where it has been most needed. As of 2020, the rollout of smart metering, or advanced metering infrastructure (AMI), had reached more than 100 million meters in the United States, and nearly half of all electricity customers are now equipped with a smart meter (Figure 1). Smart meters are quickly becoming a ubiquitous data capture feature of smart grids. AMI enables utilities to record and measure electricity usage and power-flow metrics at a minimum of hourly intervals and at least once a day. At a minimum, AMI enables interval metering, automatic meter reading enabling accurate and time-interval billing, and the ability to provide feedback on customer energy consumption.

advanced metering infrastructure↗
DOE OSTI2019

Neural Network Predictive Controller for Grid-Connected Virtual Synchronous Generator

In this paper, a neural network predictive controller is proposed to regulate the active and the reactive power delivered to the grid generated by a three-phase virtual inertia-based inverter. The concept of the conventional virtual synchronous generator (VSG) is discussed, and it is shown that when the inverter is connected to non-inductive grids, the conventional PI-based VSGs are unable to perform acceptable tracking. The concept of the neural network predictive controller is also discussed to replace the traditional VSGs. This replacement enables inverters to perform in both inductive and non-inductive grids. The simulation results confirm that a well-trained neural network predictive controller illustrates can adapt to any grid impedance angle, compared to the traditional PI-based virtual inertia controllers.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

A Framework to Evaluate the Grid Impacts of EV Fleet Charging Solutions

Growing Electric vehicle (EV) adoption in residential and commercial applications is driving the need for the charging infrastructures required to fulfill the charging needs. The resulting increase in demand for electric power will add a significant load to the electric grid, which could negatively impact the grid operation. EVs are power electronic loads and draw harmonic currents which can lead to a host of power quality issues. Therefore, it is crucial to assess the grid impacts and management of EV charging loads to ensure the reliable operation of the electric grid. In this paper, we develop a framework to help determine power-quality impacts given an EV charging schedule on the system. We compare the performance of unmanaged and managed charging solutions on factors like voltage drop, flicker, harmonic distortion and the peak site load - based on the EV depot in Hazelwood school district. The results allow insights into operation and site design of EV depots.

ADVANCED PROPULSION SYSTEMS,POWER TRANSMISSION AND↗
DOE OSTI2023

Fuel Cell Stack Model for Real-Time Simulation of Grid-Connected Applications

Fuel cell stacks coupled with electrolyzers and hydrogen storage sites can be a promising category of distributed energy resources for both grid-connected and stand-alone power systems. However, because of high costs, at-scale hardware testing of fuel cell stacks for grid-connected applications is not economically viable at present. A model-based system that can accurately captures the steady-state and dynamic response of fuel cell stacks over long time periods (hours), is needed. This paper demonstrate a real-time electromagnetic transient model of a megawatt-scale, grid-connected proton exchange membrane fuel cell stack, coupled with a mass-based hydrogen storage system. This model can emulate the electrical steady-state and dynamic response of grid-connected fuel cell stacks. We validate the model using the response of commercial hardware fuel cell stacks and analytical models in the literature - using a digital real-time simulator (RSCAD). The proposed real-time model is then used to simulate cases spanning different time horizons and to design controller-hardware-in-the-loop experiments to evaluate controllers for hydrogen stations.

activation potential↗
DOE OSTI2021

EV Hosting Capacity Analysis on Distribution Grids

The increasing trend in electric vehicle (EV) adoption can cause challenges to traditional electric grid operations if utilities are not equipped with tools and methods to effectively manage these fleets. Growing EV charging loads will alter the magnitude and duration of conventional peaks in demand profiles and even significantly shift them, potentially causing operational violations in the distribution grid. This paper presents the development and results of an EV hosting capacity tool to quantify the impacts of injecting large numbers of EV charging loads and to determine the available capacity of existing distribution feeders to continue providing reliable and affordable grid operations. Tools like the hosting capacity analysis would enable utilities to better prepare for grid operations in the near future while exploring the impact and effectiveness of strategies to manage these loads, such as peak pricing and smart charging. This paper evaluates the hosting capacity of some real-world feeders to accommodate EV charging loads, including extreme fast-charging options.

distribution grid↗
DOE OSTI2023

A Voltage Inference Framework for Real-Time Observability in Active Distribution Grids

Active distribution grids are gaining traction to meet the growing environmental, socio-economic, and sustainability targets. Various advanced smart grid technologies facilitate the integration of Distributed Energy Resources (DERs) by supporting the bi-directional power flow. The limited observability of distribution grids, primarily related to their location at the very edge of power system infrastructure, brings challenges to optimal grid management. Moreover, only a limited number of measurements at regular intervals are usually available. This paper presents a novel inference framework, referred to as “Voltage Inference”, to overcome the observability issues. The proposed framework employs a prediction step based on the Multivariate Taylor series approximation, followed by a corrector step that minimizes the estimation error to infer the otherwise unknown voltages from the available measurements. Furthermore, numerical results on the IEEE 13-bus test feeder validate the accuracy and computational performance of the proposed framework.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

IEEE 1547 Standards Advancing Grid Modernization

Technology advances including development of advanced distributed energy resources (DER) and grid-integrated operations and controls functionalities have surpassed the requirements in current standards and codes for DER interconnection with the distribution grid. The full revision of IEEE Standards 1547 (requirements for DER-grid interconnection and interoperability) and 1547.1 (test procedures for conformance to 1547) are establishing requirements and best practices for state-of-the-art DER including variable renewable energy sources. The revised standards will also address challenges associated with interoperability and transmission-level effects, in addition to strictly addressing the distribution grid needs. This paper provides the status and future direction of the ongoing development focus for the 1547 standards.

1547↗
DOE OSTI2019

Generative Adversarial Network for Synthetic Time Series Data Generation in Smart Grids

The availability of fine grained time series data is a pre-requisite for research in smart-grids. While data for transmission systems is relatively easily obtainable, issues related to data collection, security and privacy hinder the widespread public availability/accessibility of such datasets at the distribution system level. This has prevented the larger research community from effectively applying sophisticated machine learning algorithms to significantly improve the distribution-level accuracy of predictions and increase the efficiency of grid operations. Synthetic dataset generation has proven to be a promising solution for addressing data availability issues in various domains such as computer vision, natural language processing and medicine. However, its exploration in the smart grid context remains unsatisfactory. Previous works have tried to generate synthetic datasets by modeling the underlying system dynamics: an approach which is difficult, time consuming, error prone and often times infeasible in many problems. In this work, we propose a novel data-driven approach to synthetic dataset generation by utilizing deep generative adversarial networks (GAN) to learn the conditional probability distribution of essential features in the real dataset and generate samples based on the learned distribution. To evaluate our synthetically generated dataset, we measure the maximum mean discrepancy (MMD) between real and synthetic datasets as probability distributions, and show that their sampling distance converges. To further validate our synthetic dataset, we perform common smart grid tasks such as k-means clustering and short-term prediction on both datasets. Experimental results show the efficacy of our synthetic dataset approach: the real and synthetic datasets are indistinguishable by solely examining the output of these tasks.

14 SOLAR ENERGY↗
DOE OSTI2020

Joint Estimation of Topology and Injection Statistics in Distribution Grids with Missing Nodes

Optimal operation of distribution grid resources relies on accurate estimation of its state and topology. Practical estimation of such quantities is complicated by the limited presence of real-time meters. This article discusses a theoretical framework to jointly estimate the operational topology and statistics of injections in radial distribution grids under limited availability of nodal voltage measurements. In particular, we show that our proposed algorithms are able to provably learn the exact grid topology and injection statistics at all unobserved nodes as long as they are not adjacent. The algorithm design is based on novel ordered trends in voltage magnitude fluctuations at node groups, that are independently of interest for radial physical flow networks. The complexity of the designed algorithms is theoretically analyzed and their performance is validated using both linearized and nonlinear ac power flow samples in test distribution grids.

97 MATHEMATICS AND COMPUTING↗