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At least 217 records · Page 12

Intelligent sensor and controller framework for the power grid

Disclosed below are representative embodiments of methods, apparatus, and systems for monitoring and using data in an electric power grid. For example, one disclosed embodiment comprises a sensor for measuring an electrical characteristic of a power line, electrical generator, or electrical device; a network interface; a processor; and one or more computer-readable storage media storing computer-executable instructions. In this embodiment, the computer-executable instructions include instructions for implementing an authorization and authentication module for validating a software agent received at the network interface; instructions for implementing one or more agent execution environments for executing agent code that is included with the software agent and that causes data from the sensor to be collected; and instructions for implementing an agent packaging and instantiation module for storing the collected data in a data container of the software agent and for transmitting the software agent, along with the stored data, to a next destination.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Applications of Solid-State Transformers for Electric Power Grid HEMP/GMD Resilience

A high-altitude electromagnetic pulse (HEMP) or geomagnetic disturbance (GMD) can disrupt power grids by inducing low-frequency common-mode (CM) currents. When these currents flow through grounded transformers, they can bias the magnetic core, driving it into saturation and reducing performance or damaging equipment. This work presents a solid-state transformer (SST) to replace vulnerable assets and improve grid resilience. The paper reviews half-cycle saturation in conventional transformers, then describes an SST architecture that neutralizes and redirects CM currents during HEMP/GMD events. A prototype SST is built and validated, demonstrating stable CM-disturbance operation and protection of nearby transformers. Finally, large-scale simulations show how coordinated SST deployment mitigates CM disturbances and strengthens overall grid resilience.

four-leg inverter↗

Accessing Wind Tunnels From NASA's Information Power Grid

The NASA Ames wind tunnel customers are one of the first users of the Information Power Grid (IPG) storage system at the NASA Advanced Supercomputing Division. We wanted to be able to store their data on the IPG so that it could be accessed remotely in a secure but timely fashion. In addition, incorporation into the IPG allows future use of grid computational resources, e.g., for post-processing of data, or to do side-by-side CFD validation. In this paper, we describe the integration of grid data access mechanisms with the existing DARWIN web-based system that is used to access wind tunnel test data. We also show that the combined system has reasonable performance: wind tunnel data may be retrieved at 50Mbits/s over a 100 base T network connected to the IPG storage server.

Becker, Jeff↗

Data-Driven Security Assessment of Power Grids Based on Machine Learning Approach: Preprint

Data-driven security assessment provides key indicators on power system stability using simulations on scheduling models, as opposed to dynamic simulations that are more time-consuming. This paper investigates data-driven security assessment of power grids based on machine learning. Multivariate random forest regression is used as the machine learning algorithm due to its high robustness to the input data. Three stability issues are analyzed using the proposed machine learning tool, including transient stability, frequency stability and small signal stability. The estimation values from machine learning tool are compared with those from dynamic simulations. Results show that the proposed machine learning tool can effectively predict the stability margins for the three stability metrics.

14 SOLAR ENERGY↗

Asymmetry underlies stability in power grids

Abstract Behavioral homogeneity is often critical for the functioning of network systems of interacting entities. In power grids, whose stable operation requires generator frequencies to be synchronized—and thus homogeneous—across the network, previous work suggests that the stability of synchronous states can be improved by making the generators homogeneous. Here, we show that a substantial additional improvement is possible by instead making the generators suitably heterogeneous. We develop a general method for attributing this counterintuitive effect to converse symmetry breaking , a recently established phenomenon in which the system must be asymmetric to maintain a stable symmetric state. These findings constitute the first demonstration of converse symmetry breaking in real-world systems, and our method promises to enable identification of this phenomenon in other networks whose functions rely on behavioral homogeneity.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Emerging Technologies: Integrating with the Power Grid of Tomorrow

Traditional interactions between the built environment and the electric utility industry are changing rapidly. Rather than a one-way flow of electricity where utilities produce and transmit the electricity that buildings then consume, buildings are becoming efficient energy consumers that can dynamically adjust loads to ensure grid-provided energy is used effectively. Buildings are transitioning to now be at the intersection of forecasting loads and demand response, forecasting and control of output from distributed generation and renewable energy systems, and the optimal dispatch of energy storage. Because residential and commercial buildings consume 74.7% of the electricity generated in the United States, grid-integrated buildings represent an important solution to addressing challenges facing the power sector. In addition to the electric power grid, buildings will be increasingly interactive with water, transportation, and telecommunications networks, and will also more strongly affect surrounding buildings and other civic infrastructure.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Topology Estimation using Graphical Models in Multi-Phase Power Distribution Grids

Power distribution grids are structurally operated radially, such that energized lines form a collection of trees with a substation at the root of each tree. The operational topology may change from time to time, however tracking these changes, even though important for the distribution grid operation and control, is hindered by limited real-time monitoring. This work develops a learning framework to reconstruct the radial operational structure of the distribution grid from synchronized voltage measurements. To detect operational lines our learning algorithm uses conditional independence tests for continuous random variables that is applicable to a wide class of probability distributions and Gaussian injections in particular. Furthermore, our algorithm applies to the practical case of unbalanced three-phase power flow. The performance is validated on AC power flow simulations over three phase IEEE distribution grid test cases.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Digital Twin: Visualizing the Future of the Power Grid [Slides]

The energy systems are generating data at a scale and complexity that increasingly outpaces our ability to analyze it. This talk argues that rigorous, large-scale visualization is a critical tool for meeting that challenge. Drawing on recent work in the Computational Science Center at the National Laboratory of the Rockies, we trace a progression of visualization research culminating in an immersive digital twin of a real campus power grid. Along the way, we examine why visualization matters at all, where widely-used techniques quietly fail, and what becomes analytically possible when you match the display environment to the scale of the problem.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Harnessing distributed GPU computing for generalizable graph convolutional networks in power grid reliability assessments

Although machine learning (ML) has emerged as a powerful tool for rapidly assessing grid contingencies, prior studies have largely considered a static grid topology in their analyses. This limits their application, since they need to be re-trained for every new topology. Here, this paper explores the development of generalizable graph convolutional network (GCN) models by pre-training them across a range of grid topologies and contingency types. We found that a GCN model with auto-regressive moving average (ARMA) layers with a line graph representation of the grid offered the best predictive performance in predicting voltage magnitudes (VM) and voltage angles (VA). We introduced the concept of phantom nodes to consider disparate grid topologies with a varying number of nodes and lines. For pre-training the GCN ARMA model across a variety of topologies, distributed graphics processing unit (GPU) computing afforded us significant training scalability. The predictive performance of this model on grid topologies that were part of the training data is substantially better than the direct current (DC) approximation. Although direct application of the pre-trained model to topologies that are not part of the grid is not particularly satisfactory, fine-tuning with small amounts of data from a specific topology of interest significantly improves predictive performance. In general, this paper highlights the feasibility of training large-scale GNN models to assess the reliability of power grids by considering a wide variety of grid topologies and contingency types. With the advent of foundational models in ML and the exponential increase in GPU computing clusters, generalizable ML models will significantly enhance how utilities manage power systems and make decisions in real-time or near-real-time.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Computational and numerical analysis of AC optimal power flow formulations on large-scale power grids

We report that alternating current optimal power flow (AC-OPF) is a fundamental tool in electric utilities to determine optimal operation of the various resources. Typically, the AC-OPF problem uses power balance formulation containing voltages and power equations. Yet, there is no comprehensive comparison of the different AC-OPF formulations, especially for large-scale networks. This paper presents a detailed comparative evaluation of different formulations of the AC-OPF problem on networks ranging from 9-bus to 25,000 buses. Three different formulations: 1) power balance with polar voltages, 2) power balance with Cartesian voltages, and 3) current balance with Cartesian voltages are discussed in detail by comparing their characteristics, and numerical and computational performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Performant Optimization Strategies for Multifidelity Stochastic Power Grid Models

This talk goes into the algorithmic work done under the Forest project in order to solve expensive power grid models. We explore multiple fidelities of models that balance accuracy and computational expense. We use bundling strategies and progressive hedging in order to parallelize large stochastic programs.

Alfant, Rachael May [Sandia National Laboratories ↗

Smart Contracts for Power Grid Applications Using the Advanced DLT Cyber Grid Guard Testbed

In this study is presented two power system applications with distributed ledger technology (DLT) and smart contracts (SC) that were assessed in a Cyber-Grid-Guard System (CGGS) advanced testbed, with protective relays, power meters, communication devices, DLT devices, synchronized time source, clock displays and real time simulator. This CGGS testbed was set in the Advanced Protection Lab, 252 lab space of the Grid Research Integration and Deployment Center (GRID- C), at Oak Ridge National Laboratory. In power grids, customer-owned distributed energy resources (DERs) are more frequent than in the past, and the numbers of points of interconnection (POI) with customer-owned DERs have increased. Disruptive operation from DERs presents a risk to grid operations, and protective relays located at the POI are used to isolate out-of-tolerance or poorly behaving of DERs. Ensuring the integrity of data from the relays at the POI, and DLT could enhance the security of the power grids. The first application is a SC to define and control the allowable total power factor (TPF) of the DER (wind farm) output, and the terms of the SC are implemented using DLT with a CGGS for a customer-owned DER. The TPF SC was implemented by the CGGS using DLT. The experimental model was performed with a real-time simulator using a CGGS and relay in-the-loop. The data collected from the CGGS were used to execute the TPF SC. The TPF limits were between +0.9 and +1.0, and the breakers’ operation in the POI was controlled by the relay using the SC. The events were collected from the real-time simulator, CGGS, and SEL 700GT relay to validate a successful application of the TPF SC using DLT. The second application is a SC to measure and control the allowable voltage service limits (VSL) by the CGGS using DLT. The tests were performed by using a real-time simulator, CGGS and relay in-the-loop. The data was collected from the CGGS that executed the SC. The main constraints were defined based on ANSI C84.1 service voltage limits, and the operation of the breakers in the POI. The events were collected from the CGGS, and SEL 700GT relay to assess a successful operation of the VSL SC using DLT.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Fidelity Analysis of Complex Large-Scale Simulation Models of PEs (MARS) in Future Power Grids

With the proliferation of power electronic (PE)-based resources in the electric grid, there have been numerous different kinds of simulation models developed and studied to understand their dynamic behavior. Study of PE-based resources using each simulation model has its own distinct advantages and disadvantages. Therefore it is very important to carefully select the appropriate model for the evaluation of the PE-based resources. In this paper, one such effort is made to analyze the different types of models in the case of a multi-port autonomous reconfigurable solar power plant (MARS). The MARS integrates a hybrid photovoltaic (PV)-energy storage system (ESS) plant to high-voltage direct current (HVdc) system and transmission alternating current (ac) grid. The dynamic models are evaluated under different test cases varying the short-circuit ratio (SCR) and control algorithms. Recommendations are provided on the equipment study needs based on the analysis completed.

Marthi, Phani Ratna Vanamali↗

Spatial Impacts of Electric Vehicle Charging on Power Grid Stability: A Downtown Atlanta Case Study

The rapid increase in electric vehicle (EV) charging demand poses a potential risk to power grid stability, particularly as the spatial distribution of this demand remains underexplored. Existing research often focuses on technical optimization models while overlooking the geographic and human dynamics that affect energy consumption. This study addresses this gap by incorporating mobility data to estimate both building energy use and EV charging demand while also considering geographic factors for a better understanding of grid load. Using agent-based simulations and the Open-Source Distribution System Simulator, the study evaluates the effect of various EV penetration scenarios on grid voltage and unbalance. The results show that, although voltage remains within acceptable limits at lower EV penetration rates, significant voltage drop and unbalance occur as EV penetration exceeds 40%, particularly in residential areas with high charging demand. This study offers a framework for integrating spatial analysis and mobility data in power network simulations, providing insights for future EV infrastructure planning.

Pan, Melrose [ORNL] (ORCID:000000031627448X)↗

Quantifying impacts of heat waves on power grid operation

Climate change is projected to cause an increase in the severity and frequency of extreme weather events such as heat waves and droughts. Such changes present planning and operating challenges and risks to many economic sectors. In the electricity sector, statistics of extreme events in the past have been used to help plan for future peak loads, determine associated infrastructure requirements, and evaluate operational risks, but industry-standard planning tools have yet to be coupled with or informed by temperature models to explore the impacts of the "new normal" on planning studies. For example, high ambient temperatures during heat waves reduce the output capacity and efficiency of gas fired combustion turbines just when they are needed most to meet peak demands. This paper describes the development and application of a production cost and unit commitment model coupled to high resolution, hourly temperature data and a temperature dependent load model. The coupled system has the ability to represent the impacts of hourly temperatures on load conditions and available capacity and efficiency of combustion turbines, and therefore capture the potential impacts on system reliability and production cost. Ongoing work expands this capability to address the impacts of water availability and temperature on power grid operation.

Climate change↗

Recent Advances in Precision Clock Synchronization Protocols for Power Grid Control Systems

With the advent of a new Precision Time Protocol specification, new opportunities abound for clock synchronization possibilities within power grid control systems. The third iteration of the Institute of Electrical and Electronics Engineers Standard 1588 specification provides several new features specifically aimed at complex, wide-area deployments in which situational awareness and control require precise time agreement. This paper describes the challenges faced by existing technology, introduces the new time distribution specification, and provides examples to explain how it represents a game-changing innovation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Power Grid Contingency Analysis with Machine Learning: A Brief Survey and Prospects

We briefly review previous applications of machine learning (ML) in power grid analyses and introduce our ongoing effort toward developing a generative-adversarial (GA) model for fast and reliable grid contingency analyses. According to our review, the persisting limitation of traditional ML techniques in grid analyses is the need for an exhaustive amount of training data for model generalization and accurate predictions. GA models overcome this limitation by first learning true data distribution from a small training set, from which new samples assimilating true data are generated with some variations. Subsequently, GA models can transfer learn or super-generalize with increased accuracy, that is, accurately predict n - (k + 2) contingencies from a small n - k training set and generated n - (k + 1) data. The joint effort between Idaho National Lab and Florida State University strives to develop a zero-shot and deep learning-based contingency analysis tool, named Smart Contingency Analysis Neural Network (SCANN), by leveraging the aforementioned advantages of GA models. The basic architecture of SCANN stems from the Latent Encoding of Atypical Perturbations network combined with an adversarial network, and it is designed to generate imbalanced power flow data from learned true data distributions for prediction purposes. Here we also introduce the abstract concept of resilience-chaos plots, a new resilience characterization tool proposed to complement SCANN by aiding in the assessment of large amounts of high-order contingency predictions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Market Opportunities and Challenges for Pumped Hydro in an Evolving Power Grid: Preprint

The paper explores several market opportunities and challenges for pumped storage hydropower (PSH) related to ongoing changes in the electric power grid. Two PSH technologies are investigated - single-speed pump/turbine and variable-speed pump/turbine units - under three variable generation penetration scenarios. The results provide a way to do relative comparisons of the opportunities and challenges that pumped storage hydro faces as the variable generation in a system increases.

13 HYDRO ENERGY↗