An Inrush Current Limiting Strategy for Virtual-Oscillator-Controlled Grid-Forming Inverters
Not provided.
Energy & Fuels↗
SEARCH · Engineering Papers
Results for “electric power systems”
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.
Multi-Agent Graph-Attention Deep Reinforcement Learning for Post-Contingency Grid Emergency Voltage Control
Grid emergency voltage control (GEVC) is paramount in electric power systems to improve voltage stability and prevent cascading outages and blackouts in case of contingencies. While most deep reinforcement learning (DRL)-based paradigms perform single agents in a static environment, real-world agents for GEVC are expected to cooperate in a dynamically shifting grid. Moreover, due to high uncertainties from combinatory natures of various contingencies and load consumption, along with the complexity of dynamic grid operation, the data efficiency and control performance of the existing DRL-based methods are challenged. To address these limitations, we propose a multi-agent graph-attention (GATT)-based DRL algorithm for GEVC in multi-area power systems. Here, we develop graph convolutional network (GCN)-based agents for feature representation of the graph-structured voltages to improve the decision accuracy in a data-efficient manner. Furthermore, a cutting-edge attention mechanism concentrates on effective information sharing among multiple agents, synergizing different-sized subnetworks in the grid for cooperative learning. We address several key challenges in the existing DRL-based GEVC approaches, including low scalability and poor stability against high uncertainties. Test results in the IEEE benchmark system verify the advantages of the proposed method over several recent multi-agent DRL-based algorithms.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Modeling and Rapid Prototyping of Integrated Transmission-Distribution OPF Formulations with PowerModelsITD.jl
Conventional electric power systems are composed of different unidirectional power flow stages of generation, transmission, and distribution, managed independently by transmission system and distribution system operators. However, as distribution systems increase in complexity due to the integration of distributed energy resources, coordination between transmission and distribution networks will be imperative for the optimal operation of the power grid. However, coupling models and formulations between transmission and distribution is non-trivial, in particular due to the common practice of modeling transmission systems as single-phase, and distribution systems as multi-conductor phase-unbalanced. To enable the rapid prototyping of power flow formulations, in particular in the modeling of the boundary conditions between these two seemingly incompatible data models, we introduce PowerModelsITD.jl, a free, open-source toolkit written in Julia for integrated transmission-distribution (ITD) optimization that leverages mature optimization libraries from the InfrastructureModels.jl-ecosystem. The primary objective of the proposed framework is to provide baseline implementations of steady-state ITD optimization problems, while providing a common platform for the evaluation of emerging formulations and optimization problems. In this work, we introduce the nonlinear formulations currently supported in PowerModelsITD.jl, which include AC-polar, AC-rectangular, current-voltage, and a linear network transportation model. Results are validated using combinations of IEEE transmission and distribution networks.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Anomaly Detection, Localization and Classification using Drifting Synchrophasor Data Streams
With ongoing automation and digitization of the electric power system, several Phasor Measurement Units(PMUs) have been deployed for monitoring and control. PMU data can have multiple anomalies, and many of the researchers in the past have concentrated on training machine/deep learning algorithms offline for anomaly detection over PMU data (i.e., not in real time). These machine/deep learning algorithms, when trained offline on a sample rather than a population of the dataset, fail to consider the dynamic behavior of the power grid in real-time, resulting in low accuracy. Considering the dynamic behavior of the power grid (e.g., change in load, generation, distributed energy resources (DERs) switching, network, controls), the definition of data anomalies varies in time and requires online training. A fundamental challenge is to enable online (i.e., real-time) training of machine/deep learning algorithms for anomaly detection over streaming PMU data. While machine/deep learning is often desirable to manage data streams, training a deep learning algorithm over streaming PMU data is nontrivial due to changes in data statistics caused by dynamic streaming data. This paper proposes PMUNET: a novel device-level deep learning-based data-driven approach for anomaly detection, localization, and classification over streaming PMU data, using online learning and multivariate data-drift detection algorithm .Two variants of PMUNET, Dynamic data Change Driven Learning (DCDL) and Continuity Driven Learning (CDL), are proposed and compared. DCDL aims to train the deep learning algorithm whenever the definition of anomaly changes due to the power grid dynamics. On the other hand, CDL continuously trains the deep learning algorithm over the PMU data-stream. The experimental results verify that DCDL outperforms CDL and other efficient anomaly detection methods over multiple events such as faults and load/ generator/capacitor/DERs variations/switching for IEEE 14 and 39 Bus test system as well as real PMU industrial data. The result verifies that DCDL variant of PMUNET improves over existing approach with a gain of 2% - 10% in terms of accuracy, false-positive rate, and false-negative rate.
adversarial deep learning↗
Grid Forming Fast Frequency Response for PMSG-Based Wind Turbines
Electric power systems are undergoing a rapid transition from fuel-based generation using synchronous generators to renewable generation interfaced by power electronics. In this context, a key challenge is using renewable generation with limited controllability to contribute to power system stability. In this work, we investigate grid-forming control of permanent magnet synchronous generator (PMSG) wind turbines. The proposed control and curtailment strategy supports the entire spectrum of standard functions of grid-following (e.g. maximum power point tracking (MPPT) and grid-forming control (e.g., primary frequency control) without explicit mode switching. A detailed case study is used to compare the performance of the proposed control at operating points corresponding to MPPT and frequency control with standard grid-forming and grid-following controls. Further, the results demonstrate that (i) the proposed energy balancing grid forming control is self-synchronizing in MPPT mode, (ii) the (limited) energy storage and controllability of wind turbines can be adequately utilized to provide grid support, and (ii) the proposed control exhibits good performance under variable wind speeds and does not result in a significant increase of wind turbine fatigue loads.
17 WIND ENERGY↗
Ultrahigh capacitive energy density in ion-bombarded relaxor ferroelectric films
Dielectric capacitors can store and release electric energy at ultrafast rates and are extensively studied for applications in electronics and electric power systems. Among various candidates, thin films based on relaxor ferroelectrics, a special kind of ferroelectric with nanometer-sized domains, have attracted special attention because of their high energy densities and efficiencies. We show that high-energy ion bombardment improves the energy storage performance of relaxor ferroelectric thin films. Intrinsic point defects created by ion bombardment reduce leakage, delay low-field polarization saturation, enhance high-field polarizability, and improve breakdown strength. We demonstrate energy storage densities as high as ~133 joules per cubic centimeter with efficiencies exceeding 75%. Deterministic control of defects by means of postsynthesis processing methods such as ion bombardment can be used to overcome the trade-off between high polarizability and breakdown strength.
Kim, Jieun↗
Load Composition Analysis Tools
Methods and tools to support load composition analysis for bulk electric power systems.
Chassin, David P.↗
GridSTIX
SF-25-112 Grid-STIX is a comprehensive extension of the STIX (Structured Threat Information Expression) 2.1 ontology specifically designed for electrical grid cybersecurity applications. This ontology provides a standardized, machine-readable framework for modeling grid assets, operational technology devices, threats, vulnerabilities, supply chain risks, and security relationships in electrical power systems. ## Key Features - **Comprehensive Grid Coverage**: Physical assets, OT devices, grid components, sensors, and energy storage systems - **Zero Trust Architecture**: Policy decision points, enforcement points, trust brokers, and continuous monitoring - **AMI Infrastructure**: Advanced metering networks, head-end systems, mesh gateways, and MDM systems - **Advanced Security Modeling**: Attack patterns, vulnerabilities, mitigations, and supply chain risks - **Critical Grid Relationships**: Power flow, protection, control, and synchronization relationships - **Supply Chain Security**: Supplier modeling, country of origin tracking, and risk assessment - **Protocol Support**: DNP3, Modbus, IEC 61850, IEC 60870-5-104, OPC-UA, and IEEE standards - **Python Code Generation**: Automated STIX-compliant Python class generation from ontologies - **Interactive Visualization**: Enhanced HTML network graphs with grid-specific categorization - **STIX 2.1 Compliance**: Full compatibility with STIX threat intelligence ecosystem
Blakely, Benjamin [Argonne National Laboratory (AN↗
HEMP Transformer Defense Through Power Electronics
High altitude electromagnetic pulses and geo-magnetic disturbances have the potential to severely impact the electric power grid by damaging large power transformers and causing severe power quality issues. This impact comes as a result of a quasi-static bias induced on transmission lines by geomagnetically induced currents which saturate magnetic components in the electric power system. This paper introduces the concept of utilizing a h-bridge inverter on the neutral of a LPT to inject a DC bias equivalent voltage onto the neutral side of the transformer windings. This biasing floats the transformer windings, eliminating the effect of the DC current and keeping the transformer from saturating. Schematic diagrams will be presented, along with simulation model data using Typhoon and PLECS, and finally test results from a benchtop hardware test.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Machine Learning Guided Operational Intelligence from Synchrophasors (Final Report)
Schweitzer Engineering Laboratories (SEL) and Oregon State University (OSU) received over 27 terabytes of electrical power system phasor measurement unit (PMU) data for the Eastern, Western, and ERCOT interconnections. The dataset includes measurements spread across 446 PMUs from early 2016 to mid 2018 depending on the interconnect. The full dataset was split into a training and test (holdout) dataset by PNNL. All data was received in the Apache Parquet format. The overarching goal of this project is to develop and execute a strategy to mitigate data anomalies, perform analysis on the dataset, and detect anomalous events in the data.
24 POWER TRANSMISSION AND DISTRIBUTION↗
An Overview of Inverter-based Resource Interconnection Standards
For the past century, electric power systems have primarily been bulk power systems consisting of generation, transmission, and distribution networks. Now the rapid expansion of distributed renewable power sources (RESs) and the shift from large, conventional synchronous machine resources to smaller-sized resources with diverse generation characteristics become the most significant change in modern power systems. With the increasing penetration of RESs, which are inverter-based resources (IBRs), it is important to develop interconnection standards that define performance and capability criteria for these IBRs. This is necessary to ensure the stable and reliable operation of power systems. This report summarizes the standards for IBRs interconnection in North America.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Guide to Developing Energy Services Interfaces
This document provides guidance to develop communications interfaces that are highly interoperable and adhere to a set of energy services interface (ESI) principles. It can be applied in the context of information and communications technology interface standards and implementation profiles that enable the integration of a facility with responsive distributed energy resources (DER) into an electric power system consistent with the fundamental ESI principles. In this context, a DER facility may consist of a single DER with a communicating controller or may be as complex as a microgrid campus with several buildings and many DERs. This document is not a technical interface standard, but the requirements described can be used to check that existing, augmented, or new interface standards meet the interoperability requirements of the ESI concept. In this way, this guide for the ESI specification can support future advancements in developing interoperability standards and implementation profiles. The intended audience for this document is DER integration practitioners and ecosystem groups that are in the business of developing and implementing communications interfaces for DER integration. It is intended that these groups apply the information and processes in this document to develop communications standards and implementation profiles that are consistent with fundamental ESI principles.
2030.5↗
Communication-Constrained Robust Control and Learning of Grid-Connected
The electric grid of things (EGoT) promises great potential for innovative grid services by tapping into vast load flexibility. However, the unique characteristics of EGoT, being a part of the cyber-physical electric power system, present both opportunities and challenges, especially concerning supply-demand balancing, stability, and communication constraints. Traditionally, centralized control was employed to ensure balance and stability in power systems. However, with the massive influx of EGoT devices, new strategies are needed to efficiently coordinate and control these distributed devices for optimal grid operations. While some studies have explored efficiency and economic models, there remains a gap in ensuring reliability under everyday operations and resilience during extreme conditions. Addressing this gap, this project develops the technology for an Energy Service Interface (ESI) that includes novel pricing, control, learning, and distributed optimization algorithms, which will enable utilities to recruit EGoT assets for crucial grid services such as load flexibility, voltage regulation, and situation-awareness. The key novelty of the proposed technology is the careful distribution of learning and control functions across utility and EGoT asset owners such that provably efficient and resilient grid operations are attained while respecting communication and information-exchange constraints. Specifically, the project team develops machine-learning enhanced load modeling methods to allow EGoT asset owners to learn their load capability and flexibility, and develops pricing-based and decentralized learning-based control so that asset owners can coordinate to meet system-wide demand-supply balance and reliability goals. For extreme situations involving high-impact, low-probability catastrophic events (termed the “black-sky” events), the team also develops (1) a “Feeder-Operating Center-on-a-Laptop” (FOCAL) software that can assist utility personnel in leveraging EGoT assets to accelerate the service recovery of damaged feeders, and (2) distributed optimization algorithms that can coordinate the operation points of EGoT devices under severe communication constraints. The proposed technology has been extensively tested and evaluated through simulations and on a testbed. In summary, as we transition into a more interconnected and digital power grid era, our project’s findings and developments offer a pivotal step toward guaranteeing both efficiency and resilience in the face of both everyday operations and rare “black-sky” events.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Current Practices in Distribution Utility Resilience Planning for Wildfires
This report is part of a series of hazard-focused case studies examining common practices in electric utility resilience planning. We use standard terminology defining resilience as the ability to anticipate, withstand, absorb, and recover from hazards that cause long duration outages. We distinguish between reliability and resilience using IEEE 1366-2022, which defines major events as "an event that exceeds reasonable design and/or operational limits of the electric power system." Resilience planning is focused on major event days, and reliability planning is focused on non-major event days. Utility resilience plans are assessed according to common resilience components identified in existing resilience frameworks. The focus of this report is on wildfires. Standalone reports focusing on severe storms (including hurricanes and non-winter storms) and winter storms have been published in parallel with this report. This report can be used as a starting point for understanding potential investment prioritization processes and investment options. This report is intended to improve utility resilience planning by supporting constructive dialogue among utilities, regulators, and other stakeholders.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Current Practices in Distribution Utility Resilience Planning for Hurricanes and Non-Winter Storms
This report is part of a series of hazard-focused case studies examining common practices in electric utility resilience planning. We use standard terminology defining resilience as the ability to anticipate, withstand, absorb, and recover from hazards that cause long duration outages. We distinguish between reliability and resilience using IEEE 1366-2022, which defines "major events" as "an event that exceeds reasonable design and/or operational limits of the electric power system." Resilience planning is focused on "major event days" and reliability planning is focused on non-major event days. Utility resilience plans are assessed according to common recommended resilience components that we have identified in existing resilience frameworks. The focus of this report is on hurricanes and severe storms in which the primary hazards are precipitation or high winds. We exclude winter storms with primary hazards of ice and extreme cold, as they are a unique set of hazards with different resilience considerations. Standalone reports focusing on wildfires and winter storms have been published in parallel with this report. This report can be used as a starting point for understanding potential investment prioritization processes and investment options. This report is intended to improve utility resilience planning by supporting constructive dialogue among utilities, regulators, and other stakeholders.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
A Review on Protection Challenges on Transmission Lines Connected to Inverter Based Resources
The increased penetration of inverter-based resources (IBRs) connected to transmission grids is challenging how traditional electric power systems operate. Such systems were originally designed based on the dominant presence of synchronous generators. Some main challenges include the increased concerns about system stability due to the reduced system inertia caused by IBRs and the reduced protection reliability caused by the non-deterministic fault current response of IBRs. The protection relays’ algorithms have been designed and validated based on well-known fault current characteristics of synchronous generations, while the short-circuit responses of IBRs heavily depend on their vendor-specific control schemes, which are mainly set to protect inverter semiconductor switches and DC components. The magnitude of short current that IBRs contribute is typically between 1.1–1.5 times the rated current that may behave unstably and incoherently with the voltages. The control scheme of the IBRs also controls the active (P) and reactive (Q) support during system voltage sag and swell conditions. These characteristics challenge not only protective relay schemes but also existing short-circuit software tools to correctly model IBRs for fault studies and protection coordination analyses. Utilities, university researchers, research institutes, and relay manufacturers have performed studies to investigate different aspects of high IBR penetration. Almost all studies support 1) creating international and national standards to regulate the IBRs, 2) revising engineering tools to address shortcomings, and 3) adjusting the protective relay settings to resolve protection problems. This paper summarizes the studies and research conducted in recent years to quantify the impact of IBR penetration on transmission line protection and to identify potential solutions to improve the dependability and reliability of grid protection systems.
14 SOLAR ENERGY↗
Control Oriented Models for Co-Design: Technical Overview of MT HVDC, MVDC, and Solid State Transformer Building Blocks
The electric power system is shifting toward a power electronics–enabled grid, where converter based “building blocks” (e.g., high voltage direct current (HVDC) links, multi terminal HVDC (MT HVDC) networks, medium voltage DC (MVDC) links, and solid state transformers (SSTs)) provide fast, precise control of power flows, voltage, and frequency. This report develops and applies publicly shareable electromagnetic transient (EMT) and phasor models to examine how such building blocks can be composed and coordinated to support offshore wind integration, inter area transfers, feeder support, and resilience. Section 2 documents a modular multilevel converter (MMC)–based MT HVDC modeling framework and two use cases: a compact WSCC/IEEE 9 bus test system and a 240 bus “mini WECC” case with five offshore wind plants (OWFs). Phasor to EMT transfer, initialization, and sanity checks are summarized, and neutral demonstrations of normal and contingency operation are reported. Section 3 frames the problem of wind plant inertial frequency response (IFR): shaping energy release and recovery to improve nadir while avoiding aerodynamic stall; representative simulations illustrate the issues without disclosing proprietary control. Section 4 develops MVDC concepts through an IEEE 16 bus loop and an Olympic Peninsula case study that compares AC vs. MVDC corridors and shows how feeder headroom can be pooled via DC couplers. Section 5 surveys SST architectures and identifies a gap: scalable, communication free coordination of multiple SSTs for islanded feeder networks. Across the report, novel methods and configurations under separate publication and IP review are not disclosed; only topic oriented, replicable setups and non proprietary results are shown. These models and use cases are intended as foundations for future publications and co design studies on architecture, control, and coordination of PE enabled grids.
24 POWER TRANSMISSION AND DISTRIBUTION↗
A General Method for Estimating Zonal Transmission Interface Limits from Nodal Network Data: Preprint
Capacity expansion models for the electric power system often employ zonal (rather than nodal) resolution, necessitating estimates of aggregate power transfer limits across the interfaces between model zones. Interface limits between planning areas are sometimes published, but they are not generalizable to arbitrary zone shapes. There is thus a need for a reproducible method for estimating interface transfer limits (ITLs) between user-defined zones directly from nodal transmission system data. Here, we present a simple method for estimating ITLs using a DC power flow approximation via the power transfer distribution factor (PTDF) matrix. Linear optimization is performed to identify the distribution of power flows that maximizes the total flow on interface-crossing lines, subject to individual line ratings, limits on bus injection/withdrawal, and the relationships among flows, injections, and withdrawals imposed by the PTDF matrix. We demonstrate the application of the method on a 134-zone ~65000-bus system, and we explore the influence of flow direction, contingency level, and zone size on the estimated ITLs. There is significant heterogeneity in the ratio of the ITL to the sum of interface-crossing line ratings, which highlights the importance of accounting for the physical constraints on power flows imposed by Kirchhoff's laws when estimating zonal ITLs.
17 WIND ENERGY↗