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Ogle, James P.

Publications and source records attributed to Ogle, James P..

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Enabling DER visibility using a distributed dissemination network

The electrical grid is currently undergoing a series of rapid transformational changes that have resulted in the introduction of new actors and operational schemes that have fragmented the data and control planes. To help address the issue, this paper describes the implementation of a sensor-oriented, distributed data dissemination network that seeks to eliminate data silos. The implementation is based on the DGSS architecture previously described in [1]. The developed product seeks to facilitate the seamless integration of multi-operator, multi-origin, multi-domain sensor data by using a distributed systems approach. The proposed solution decouples the sensor’s data streams from the application-specific infrastructure and migrates them into a software-defined databus that can be configured to suit the end application’s demands. To further validate DGSS capabilities, a DER oriented use case has been developed.

Sensor Dissemination Networks, Enhanced DER visibi↗
DOE OSTI2024

5G Energy FRAME Report on 5G for Grid Use Case (Year 3 Final Report)

This report provides an extensive overview of the interrelationships among energy, communication, and computing—especially in the context of decarbonization goals, challenges, and opportunities. Technical examples enabled by 5G technologies and their performance are presented, discussed, based on the experiment performed at Pacific Northwest National Laboratory. This is the first use case focused on using 5G for the U.S. power grid and will be referred to as the 5G for Grid Use Case from here on. Specifically, this use case looks at the workflow, which integrates the performance data of a real-world 5G communication testbed and a grid transmission and distribution co-simulation platform. The cross-domain information flow and logic design are illustrated with a combination of power grid contingencies and events. Lastly, a summary of the project achievement and outcome is provided, along with a technology roadmap envisioned by the project team.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

A Scalable Transmission and Distribution Co-simulation Platform for IBR-heavy Power Systems

The integration of Inverter-Based Resources (IBRs) into power systems, including both transmission and distribution networks, poses challenges for studying grid dynamic behaviours under various operating conditions and system events. This paper addresses the urgent need to investigate the influence of IBRs on grid dynamics, and their potential to enhance power system reliability and resilience. We propose a flexible, scalable transmission and distribution co-simulation platform, using opensource tools only for assessing the impact of grid-following (GFL) and grid-forming (GFM) IBRs on dynamic stability at various renewable penetration levels (up to 100%). This platform enables researchers to explore different contingencies at transmission, distribution, or both, providing a comprehensive evaluation of grid status. A series of case studies, including both small and large T&D systems with varying GFL/GFM configurations and contingencies, have been conducted. The results not only robustly validate our co-simulation framework, but also provide invaluable insights for effective IBR management in the power grid.

grid management↗
DOE OSTI2023

Model Agnostic Bayesian Framework for Online Anomaly/Event Detection in PMU Data

Phasor measurement units (PMU) are integral to the modernization and automation plan of the electric power industry. A PMU data signature contains system-level events (e.g., faults, generation/load change, etc.) and any measurement/device-related errors. Therefore, the reliable and resilient operation of power systems is equivalent to the quality of the PMU data and the situation awareness provided by its data signature. Despite recent progress, current state-of-the-art methods are not fool-proof and have certain limitations tracing an error/abnormality to sensor sub-components and grid systems. This is because of technical challenges imposed by the scarcity of the labeled information, loss of data quality, and non-stationarity of data. In this paper, we consider the online PMU data stream as an output of a stochastic process and pose the anomaly/event detection as a changepoint detection problem dealing with detecting parameter changes in the underlying stochastic processes. The proposed model-agnostic framework relies on: (a) feature extraction utilizing the minimum volume enclosing ellipsoids (MVEE) method from raw PMU observations and (b) a Bayesian framework of changepoint detection. The validity of the proposed methodology is discussed through numerical experiments on real-world utility-scale PMU data.

Hossain, Ramij Raja↗
DOE OSTI2023

5G Energy FRAME: The Design and Implementation of Data, Model, and Use Case (Year 2 Report)

This report summarizes the Year 2 work of Pacific Northwest National Laboratory’s (PNNL’s) 5G Fabricated Resource and Asset Management Encompassment for energy infrastructure (Energy FRAME) project funded by the Department of Energy Office of Science’s Advanced Scientific Computing Research (ASCR) Program. In this report, newest 5G equipment testing results are presented, along with two 5G-enabled AI/ML examples for grid applications; in addition, the work flow of grid edge, cloud, and High Performance Computing (HPC) platform is introduced, to support and interface the cross-domain simulation for power system transmission, distribution, and communication networks. Last but not least, the outlook for Year 3 work and the overarching impact of 5G Energy FRAME work to a multitude of stakeholders are provided. Additional 5G performance data now is shared through the publicly available weblink, https://www.pnnl.gov/projects/5g-energy-frame/publications

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Bi-Level Linear Programming Model for Automatic Load Shedding: A Distributed Wide-Area Measurement System-based Solution

Load shedding is currently implemented as a two-step based approach. In the first step, manual load shedding is taken place, were system operators, using estimates, inform distribution utilities of predicted stressful conditions. Information provided include the potential use of energy reserves, as well as load shedding amount. In a second step, automatic load shedding is done. The latter is realized using protection relays. While considering frequency variation, pre-defined values of load to be shed and correspondent number of stages for such to be realized are transformed into relay settings. Under-frequency protection relays use only local measurements towards decision making, thus operate in a decentralized architecture. Decision making is done in milliseconds plus breaker time. While this approach has provided much system reliability, considering the new smart grid paradigm, where system dynamics are much faster due to increasing renewable resources penetration, in some operating conditions it will generate sub-optimal solutions, such as islanding. Phasor measurement units provide a source of information which can be useful for this problem. Centralized architecture-based solutions for automatic load shedding, as present in the state-of-the-art, require though total processing times which are not acceptable for real-life implementation. In this work, considering the above, a bi-level linear programming model is presented. The model is implemented considering a distributed architecture while leveraging phasor measurement units data. The upper-level model estimates the current system state. Results of this model are embedded in a lower-level model, which decision variables are the location and load value to be shed. Easy-to-implement model, built-on the classic weighted least squares solution, highlight potential aspects towards real-life applications.

Bretas, Arturo Suman↗
DOE OSTI2023

A 5G Enabled Adaptive Computing Workflow for Greener Power Grid

5G wireless technology can deliver higher data speeds, ultra low latency, more reliability, massive network capacity, increased availability, and a more uniform user experience to users. It brings additional power to help address the challenges brought by renewable integration and decarbonization. In this paper, a 5G enabled adaptive computing workflow tool has been presented that consists of various computing resources, such as 5G equipment, edge computing, cluster, Graphics processing unit (GPU) and cloud computing, with two examples showing technical feasibility for edge-grid-cloud interaction for real-time monitoring, security assessment, and forecasting. Benefiting from the high data transmission speed and massive connection capability of 5G, the workflow shows its potential to seamlessly integrate various applications at distributed and/or centralized locations to build more complex and powerful functions, with better flexibility.

5G technology, computational workflow, edge comput↗
DOE OSTI2023

Analyzing Distribution Transformer Degradation with Increased Power Electronic Loads

The influx of non-linear power electronic loads into the distribution network has the potential to disrupt the existing distribution transformer operations. They were not designed to mediate the excessive heating losses generated from the harmonics. To have a good understanding of current standing challenges, a knowledge of the generation and load mix as well as the current harmonic estimations are essential for designing transformers and evaluating their performance. In this paper, we investigate a mixture of essential power electronic loads for a household designed in PSCAD/EMTdc and their potential impacts on transformer eddy current losses and derating using harmonic analysis. Our findings reveal that in the presence of high power electronic loads (especially third harmonics), increasing PV generation may worsen transformer degradation. However, with a low amount of power electronic loads, additional PV generation helps to reduce the harmonic content in the current and improve transformer performance.

eddy current, harmonics, PV, THD, power transforme↗
DOE OSTI2023

The Distributed Grid Sensing Services (DGSS) platform: A scalable and decentralized sensor dissemination network

In this paper, a scalable, decentralized sensor-oriented, communication blueprint will be introduced. The proposed architecture has been specifically designed to support the mass deployment of sensors while enabling data consumers to access the underlying data streams using a distributed systems approach. With the proposed approach, sensors and data clients can be decoupled from the physical communication infrastructure and migrated into a modern, software-defined infrastructure ecosystem that can be configured to suit the end application’s demands. In its current iteration, the blueprint defines the interactions, processes, and expected outcomes that each individual component within the architecture must fulfill in order to support the overall ecosystem’s needs. Within this work, such assemble of services is referred the databus, and represents the heart of the Distributed Grid Sensing Services (DGSS) architecture, a multi-year project that aims to design, implement and test a dedicated sensor dissemination network that can support the needs of the extended grid state. It is our expectation, that the proposed blueprint presented in this paper will serve as a future guide to our implementation efforts

Sebastian Cardenas, David J.↗
DOE OSTI2023

Distributed Grid-Sensing Service Layer: A System Architecture Blueprint

In this report, a scalable, decentralized, sensor-oriented communication blueprint is introduced. The proposed architecture has been specifically designed to support the mass deployment of sensors and also enable data consumers to access the underlying data streams using a distributed systems approach. With the proposed approach, sensors and data clients can be decoupled from the physical communication infrastructure and migrated into a modern, software-defined infrastructure ecosystem that can be configured to suit the end application’s requirements. In its current iteration, this blueprint defines the interactions, processes, and expected outcomes that each individual component within the architecture must support the overall ecosystem’s needs. Within this work, such an assembly of services is called the data bus; it represents the heart of the distributed grid sensing services architecture, a multiyear project that aims to design, implement, and test a reference sensor-data dissemination network that can support the needs of the extended grid state. We expect this blueprint to guide our future implementation efforts

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Efficient Topology Assessment for Integrated Transmission and Distribution Network with 10,000+ Inverter-based Resources

The renewable energy proliferation calls upon the grid operators and planners to systematically evaluate the potential impacts of distributed energy resources (DERs). Considering the significant differences between various inverter-based resources (IBRs), especially the different capabilities between grid-forming inverters and grid-following inverters, it is crucial to develop an efficient and effective assessment procedure besides available co-simulation framework with high computation burdens. This paper presents a streamlined graph-based topology assessment for the integrated power system transmission and distribution networks. Graph analyses were performed based on the integrated graph of modified miniWECC grid model and IEEE 8500-node test feeder model, high performance computing platform with 40 nodes and total 2400 CPUs has been utilized to process this integrated graph, which has 100,000+ nodes and 10,000+ IBRs. The node ranking results not only verified the applicability of the proposed method, but also revealed the potential of distributed grid forming (GFM) and grid following (GFL) inverters interacting with the centralized power plants.

Graph Analysis, Topology evaluation, Infrastructur↗
DOE OSTI2022

Data-Driven PMU Noise Emulation Framework using Gradient-Penalty-Based Wasserstein GAN

Availability of phasor measurement unit (PMUs) data has led to research on data-driven algorithms for event monitoring, control and ensuring stability of the grid. Unavailability of infrequent critical event field PMU data with component failures is driving the need to generate realistic synthetic PMU data for research. The synthetic data from power system simulation software often neglect noise profiles of received phasors, thus creating some discrepancies between real PMU data and synthetic ones. To address this issue, this work presents an initial study on the noise characteristics of PMUs, as well as presenting models for recreating their unique noise signatures. The proposed method, utilizing the Wasserstein generative adversarial network with gradient penalty (WGAN-GP) architecture, provides an excellent benchmark for matching the noise distribution. One can use a well-learned GAN model to draw noise signatures from a distribution that seemingly mirrors the real PMU noise distribution, while also being able to be detached from the PMU data once the training is done. Based on the observed results and employed data-driven methodology, it is expected that the proposed methods can be adapted to replicate the behavior of other sensors, providing research and other applications with a tool for data synthesis and sensor characterization.

PMU↗
DOE OSTI2022

Communication System Modeling in Transactive Systems

Transactive energy systems almost always rely on communication systems for proper operation but most analysis of transactive systems do not model the communication system. Often these analysis are performed by those without a communication system modeling or simulation background and the difficulty of implementing such models in the analysis environment is prohibitive. Without this model, an understanding of the communication system requirements to successfully implement a transactive energy system can not be comprehended. This report details a capability of auto-generating communication system models from an electrical distribution system model, discusses the need for such models, discusses the method by which these models were developed in this project, and demonstrates the impact on the performance of a load management system when using such models. This capability has been incorporated into Pacific Northwest National Laboratory’s (PNNL) Transactive Energy Simulation Platform (TESP).

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Technical Characterization and Benefit Evaluation of 5G-Enabled Grid Data Transport and Applications

This report summarizes the Year 1 work of Pacific Northwest National Laboratory’s (PNNL’s) 5G Fabricated Resource and Asset Management Encompassment for energy infrastructure (Energy FRAME) project funded by the Department of Energy Office of Science’s Advanced Scientific Computing Research Program. 5G is a breakthrough technology that enables a fully mobile and connected society, and a 5G-enabled digital continuum will be one of the critical foundations for a clean energy economy and grid modernization. In collaboration with PNNL’s Advanced Wireless Communication team and Center for Advanced Technology Evaluation team, the project team has been evaluating the system performance of 5G testbeds in the PNNL 5G Innovation Studio, and has formulated a co-simulation test case of power system transmission, distribution, and communication (T&D&C) networks considering 5G technology and high penetration of distributed energy resources. The methodology developed in the 5G Energy FRAME project can be customized to fit different future grid scenarios to evaluate multiple (dynamic) configurations (computing, sensing, communication, environment) for different stakeholders. In summary, our main technical highlights in project Year 1 are as follows: 1) Technical characterization of 5G standalone architectures, 2) Formulation of co-simulation test case of T&D&C networks embedded with 5G, 3) Initial benefit evaluation of 5G communication platform for grid use cases, and 4) Additional extended discussions on edge computing, artificial intelligence and machine learning, and high-performance computing and cloud computing adoptions. In addition, a collection of system performance data is shared through the publicly available weblink, https://www.pnnl.gov/projects/5g-energy-frame/publications

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

5G Enabled Transformative Co-design and Co-simulation Framework for Grid Decarbonization and Modernization

5G is a breakthrough technology to enable a fully mobile and connected society, and a 5G-enabled digital continuum will be one of the critical foundations for clean energy economy and grid modernization. The clean energy transformation not only requires innovative manufacturing, algorithm, application, and cross-domain co-simulation, but also a systematic evaluation and comprehensive support on the microelectronic and architectural computing customization to enable and maximize the high renewable penetration in the future power grid. The co-design of decarbonized grid, reliable yet efficient communication, and affordable yet ubiquitous computing will unlock the potential of almost any available tools for the undergoing clean energy transformation. 5G is also an opportunity to rethink the paradigm of infrastructure planning, as computing will be one of the core services for society alongside electricity and communication services.

5G↗
DOE OSTI2022

Model-based interface design for smart field-device integration

Operational complexity is ever-increasing for electric utilities that face challenges including integration of DERs, customer expectation of energy choices, the proliferation of non-utility-owned resources, new business models with energy service providers, and new technology with IT/OT convergence. To maintain and improve the quality of operations, planning, and decision-making in general, utilities need to manage and navigate the complexity. Managing complexity requires a modular, scalable, and flexible solution. Connecting large amounts of DERs and introducing new services requires increased grid control and evolving applications. In this paper, we show an approach utilizing model-based standardized interfaces that simplifies integration and deployment of new algorithms and smart field devices for interoperability across legacy or new systems. A modular design is presented for a reference implementation of widely used DNP3 and IEEE 2030.5 interfaces within an open-source, standards-based data integration platform for integration of smart field devices with independently developed, best-of-breed applications.

Model-driven development, system integration, smar↗