DER-Aware Grid Orchestration and Service Restoration for Enhanced Distribution Resilience
This presentation provides an overview of our work on DER-aware grid orchestration and service restoration.
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SEARCH · Engineering Papers
Results for “distribution power grids”
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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Situational awareness-enhancing community-level load mapping with opportunistic machine learning
Motivated by present and forthcoming challenges in the adoption and integration of distributed renewable energy, we develop a machine learning (ML) approach that builds short-fuse mappings connecting the occasionally-unobservable true load in one target community with information-rich signals collected from relatively more instrumented reference communities. Our setting is inspired by and tailored to target communities with significant unobservable behind-the-meter solar generation, where true load (a relatively well-behaved quantity of interest to grid operators) is hard to discern during daytime due to insufficient instrumentation and/or privacy reasons, but that can be related to reference communities with low unobservable distributed variable generation or with sufficient instrumentation. The developed mapping, herein realized with Support Vector Machine regression, is built using nighttime data from all communities, when their distributed generation is low or zero. Our ML algorithm opportunistically learns to correlate signals of interest and then is operationally used the next day to shed light into target community load evolution. The mapping is subsequently rebuilt, rolling its short-fuse scope perpetually forward in time. Here, we demonstrate the efficacy of our approach on nine synthetically generated topologies and associated timeseries stemming from real-world data, on which we observe cumulative error performance that yields lower than 10% and 15% daily-averaged mean absolute percentage errors in target community load estimation on more than about 75% and 90% of days, respectively, in multiple yearly evaluations that shed light on long-term performance also under seasonal and one-off effects. The proposed ML-powered methodology can offer grid operators much-improved visibility into a previously obscure space and can also serve as an additional source of information in broader, multi-modal solar disaggregation solutions.
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Topology property analysis and application of stable time-delay regions for linear multiple time-delay systems
This study examines the relationship between the topology of stable time-delay regions and the stability analysis of an linear multiple time delay system. To analyze the topology of stable time-delay regions, we construct a function with a value equal to zero for the time-delay points on the boundaries of stable time-delay regions. The function is continuous and differentiable in the whole defining field with a global minimum of zero so that we can locate the boundaries by minimizing the value of the function. Based on the topology analysis, we proposed a performance validation approach for controllers that are designed to stabilize the system using feedback signals with time delays. The method based on the topology analysis is simple and reliable so that can deal with a linear time-invariant system with high order and multiple time delays (more than 3). The example case study shows that the above method is reliable and enables ultra-low latency coordination and control for the future power grid with ubiquitous power electronics.
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UNIFI Specifications for GFM IBRs (V3) and Transitioning to an IEEE Standard [Slides]
This presentation describes version 3 of the grid-forming (GFM) specifications for inverter-based resources developed by the UNIFI (Uniform Interoperability for Grid-Forming Inverters) Consortium. It summarizes the requirements for GFM inverters, the four categories of GFM capability, and the tests designed to assess GFM capability. The tests including time-domain tests similar to those in use by some industry entities and frequency-domain tests that are largely new. This presentation also describes ongoing efforts to use the UNIFI GFM specifications as the starting point for a new IEEE standard called IEEE P2800.1.
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Understanding the Value of Energy Storage for Power System Reliability and Resilience Applications
Abstract Purpose of Review The need for energy storage in the electrical grid has grown in recent years in response to a reduced reliance on fossil fuel baseload power, added intermittent renewable investment, and expanded adoption of distributed energy resources. While the methods and models for valuing storage use cases have advanced significantly in recent years, the value of enhanced resilience remains an open research question. Recent Findings The findings of the recent research indicate that energy storage provides significant value to the grid, with median benefit values for specific use cases ranging from under $10/kW-year for voltage support to roughly $100/kW-year for capacity and frequency regulation services. While the value of lost load is used widely to estimate the benefits of mitigating short-duration outages, reaching as high as $719/kilowatt-year, there is no consensus when it comes to monetizing the value of improving grid resilience. Summary This paper presents a use case taxonomy for energy storage and uses the taxonomy to conduct a meta-analysis of an extensive set of energy storage valuation studies. It reviews several approaches for monetizing reliability and resiliency services and presents a proposed approach for valuing resiliency for energy storage investments.
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Hardware Design of Medium Voltage SiC-Based Modular Multilevel Converters for Grid-Tied Applications
This paper presents a design of a 10 kV silicon carbide (SiC) MOSFET based modular multilevel converter (MMC). The MMC functions as the interconnection between a 24 kV dc bus and a 13. SkV distribution grid. This paper focuses on the hardware design of the MMC and its submodules. The gate driver, auxiliary power supply and bus bur in submodules are major components that need to meet high dv/dt immunity and high insulation voltage requirements. The gate driver achieves over 200 kV/us common mode transient immunity (CMTI). Its associated auxiliary power supply is based on an on-board transformer with over 30 kV insulation capability and 1.4 pF barrier capacitance. The busbar achieves less than 11 kV/cm electric field in the air to avoid partial discharges. Validation tests of the MMC submodule were performed by double pulse tests at 5 kV and buck converter tests at3 kV, 52A (peak). Reliable operations were achieved in validation tests.
auxiliary power supply↗
Hardware-in-the-Loop Evaluation of Grid-Edge DER Chip Integration Into Next-Generation Smart Meters
To facilitate the implementation of distributed energy resource management systems (DERMS), we propose to insert a grid-edge distributed energy resource (DER) chip hosting a DERMS algorithm into the next generation of smart meters. This will create a pathway for the wide adoption of DERMS technology because many utilities plan to invest in advanced metering infrastructure in the near future. This will also bridge the gap between an electrical power utility and DERs behind the meter. The DER chip is designed to follow power direction signals from the DERMS coordinator while balancing its local objectives. We tested the chip using a controller- and power-hardware-in-the-loop evaluation under three scenarios that a DERMS could face in the real world. The DER chip was capable of and effective at directing four heterogeneous DERs to respond to a DERMS coordinator for grid services (e.g., voltage regulation and a virtual power plant).
distributed energy resource management system↗
Hardware-in-the-Loop Evaluation of Grid-Edge DER Chip Integration Into Next-Generation Smart Meters: Preprint
To facilitate the implementation of distributed energy resource management systems (DERMS), we propose to insert a grid-edge distributed energy resource (DER) chip hosting a DERMS algorithm into the next generation of smart meters. This will create a pathway for the wide adoption of DERMS technology because many utilities plan to invest in advanced metering infrastructure in the near future. This will also bridge the gap between an electrical power utility and DERs behind the meter. The DER chip is designed to follow power direction signals from the DERMS coordinator while balancing its local objectives. We tested the chip using a controller- and power-hardware-in-the-loop evaluation under three scenarios that a DERMS could face in the real world. The DER chip was capable of and effective at directing four heterogeneous DERs to respond to a DERMS coordinator for grid services (e.g., voltage regulation and a virtual power plant).
distributed energy resource management system↗
Designing resilient decentralized energy systems: The importance of modeling extreme events and long-duration power outages
Mitigating and adapting to climate change requires decarbonizing electricity while ensuring resilience of supply, since a warming planet will lead to greater extremes in weather and, plausibly, in power outages. Although it is well known that long-duration outages severely impact economies, such outages are usually not well characterized or modeled in grid infrastructure planning tools. Here, we bring together data and modeling techniques and show how they can be used to characterize and model long-duration outages. We illustrate how to integrate outages in planning tools for one promising mode of resilient energy supply—microgrids. Failing to treat these extremes in models can lead to microgrid designs (1) that do not realize their full value of resilience, since models do not see the benefits of protecting against extremes, and (2) that appear reliable on paper yet do not actually protect against extremes. Although utilities record power interruptions, lack of access to that data is hindering research on resilience; making datasets available publicly would substantially aid efforts to improve grid planning tools.
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Deep Learning-Based Dynamic Modeling of Three-Phase Voltage Source Inverters
Inverter-based resource (IBR) models are necessary to analyze modern power system stability and create effective control strategies. Modeling IBRs in converter-rich power systems is crucial, yet challenging due to the lack of commercial information on converter topologies and control parameters. This paper proposes novel convolutional neural network (CNN)–based data-driven techniques for modeling IBRs, addressing adaptability and proprietary concerns without requiring internal system physics knowledge. The proposed method is tested using real grid-tied commercial IBR transient data and demonstrates effectiveness and accuracy. Furthermore, the developed modeling approach is integrated and implemented in the open-source power distribution simulation and analysis tool, GridLAB-D, to illustrate the potentiality of dynamic analysis of large-scale power systems with high IBRs.
deep learning, artificial intelligence↗
Optimized allocation method of the VSC-MTDC system for frequency regulation reserves considering the cost
In recent years, the interconnection of asynchronous power grids through the VSC-MTDC system has been proposed and extensively studied in light of the potential benefits of economical bulk power exchanges and frequency regulation reserves sharing. This paper proposed an optimized allocation method for sharing frequency regulation reserves among the interconnected power systems and the corresponding frequency regulation control of the VSC-MTDC system under emergency frequency deviation events. Firstly, the frequency regulation reserve classification is proposed. In the classification, the available frequency response capacity reserves of each interconnection are divided into commercial reserves and regular reserves. While the commercial reserves are procured through long-term contracts, the regular reserves are purchased based on market prices of frequency regulation services. Secondly, based on the proposed frequency regulation reserve classification, a novel frequency regulation control is then introduced for the VSC-MTDC system. This control method could minimize the costs of the disturbed power grid for the needed frequency response supports from the other power grids. Simulation verifications are performed on a modified IEEE 39 bus system and a highly reduced power system model representing the North American grids. The simulation verification indicates that the developed frequency regulation control significantly reduced ancillary service costs of the disturbed power grid.
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Leveraging Cloud Platforms for Grid Modernization
Presentation held on Friday December 5th, 2025 at the “San Diego Tech Conference and Expo” about “Advanced Sensor Data Analytics and Cloud Computation for Grid Modernization”
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Voltage Regulation Operational Strategies
These posters describe results of the VROS project between HECO and NREL showing the impacts to the utility and to the solar customer of different grid support functions.
advanced inverters↗
Rapid Event Detection via Synchro-Waveform Based Temporal Attention Network in Distributed Grid
Compared with the information collected from phasor measurement units, synchro-waveforms contain high-fidelity disturbances of the grid, which can be a granular and authentic representation of measurements in the modern power system. However, the dynamic changing morphology makes it challenging to effectively capture various disturbance information from the synchro-waveforms. To tackle this issue, this paper proposes a Synchro-waveform based Temporal Attention (STA) network to achieve rapid event detection. First, a multi-scenario distributed model with renewable integration is established to generate synchro-waveforms under various uncertainties. Then, three typical temporal features are extracted directly from the synchro-waveform measurements. Additionally, the lightweight STA network is deployed to identify the most common event types in renewable energy systems via the self-attention based vision transformer module. The results from simulated experiments demonstrate that the proposed approach can achieve rapid and real-time detection within 0.81 ms and over 96.27 % accuracy.
Dong, Yuqing [University of Tennessee (UT)]↗
Modified Virtual Oscillator-Based Operation of Grid-Forming Converters with Single Voltage Sensor: Preprint
This paper proposes a virtual oscillator-based control architecture for a grid-forming converter with an inner current control loop. In general, the virtual oscillator is based on a Lienard type of oscillator equation with a cubic nonlinearity. A virtual oscillator alone cannot accommodate unbalanced or harmonic mitigation while operating converters in grid-forming mode. Therefore, to accomplish better tracking performance, incorporating the provision for nonlinear and/or unbalanced loads, an inner current control loop is utilized that is based on the Lyapunov energy function type control architecture. To reduce the overall cost of implementation and ensure proper phase difference in the generated voltages, the implemented virtual oscillator operates with only one voltage feedback from the point of common coupling. To verify the effectiveness of the proposed approach, the overall system has been modeled in MATTLAB/Simulink and PLECS domain. This paper also presents case studies showing the successful production of low harmonic load voltages under nonideal loading conditions, along with other important results.
dual second order generalized integrator↗
UNIFI's Grid-Forming (GFM) Inverter Reference Design: A Tutorial on Modeling, Control, and Experimental Implementation of GFM Inverters
The UNIFI Consortium's tutorial on grid-forming (GFM) inverters provides a comprehensive guide to the modeling, control, and experimental implementation of GFM inverters. As the integration of renewable energy accelerates, the transition from traditional grid following (GFL) to GFM inverters is crucial to ensure stable and sustainable power systems. This document outlines a reference design for three-phase and single-phase GFM inverters developed at the University of Texas at Austin. The tutorial also provides step-by-step guidance for accessing and using UNIFI’s GitHub repository, enabling users to design, build, and test GFM inverters efficiently. By fostering collaboration and equipping users with accessible resources, this initiative aims to drive widespread adoption of GFM technology across academia, utilities, and industries.
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Demand response for variable renewable energy integration: A proposed approach and its impacts
Not Available
McPherson, Madeleine↗
Design and evaluation of a cyber‐physical testbed for improving attack resilience of power systems
Abstract A power system is a complex cyber‐physical system whose security is critical to its function. A major challenge is to model, analyse and visualise the communication backbone of the power systems concerning cyber threats. To achieve this, the design and evaluation of a cyber‐physical power system (CPPS) testbed called Resilient Energy Systems Lab (RESLab) are presented to capture realistic cyber, physical, and protection system features. RESLab is architected to be a fundamental platform for studying and improving the resilience of complex CPPS to cyber threats. The cyber network is emulated using Common Open Research Emulator (CORE), which acts as a gateway for the physical and protection devices to communicate. The physical grid is simulated in the dynamic time frame using Power World Dynamic Studio (PWDS). The protection components are modelled with both PWDS and physical devices including the SEL Real‐Time Automation Controller (RTAC). Distributed Network Protocol 3 (DNP3) is used to monitor and control the grid. Then, the design is exemplified and the tools are validated. This work presents four case studies on cyberattack and defence using RESLab, where we demonstrate false data and command injection using Man‐in‐the‐Middle and Denial of Service attacks and validate them on a large‐scale synthetic electric grid.
Sahu, Abhijeet↗