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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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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Validation of Synthetic U.S. Electric Power Distribution System Data Sets

There is a strong need for synthetic yet realistic distribution system test data sets that are as diverse, large, and complex to solve as real systems. Such data sets can facilitate the development of advanced algorithms and the assessment of emerging distributed energy resources while avoiding the need to acquire proprietary critical infrastructure or private data. Such synthetic data sets, however, are useful only if they are realistic enough to look and behave similarly to actual systems. This paper presents a comprehensive framework for validating synthetic distribution data sets using a three-pronged statistical, operational, and expert validation approach. Furthermore, it also presents a set of statistical and operational metric targets for achieving realistic data sets based on detailed characterization of more than 10,000 real U.S. utility feeders. The paper demonstrates the use of the proposed validation approach to validate three large-scale synthetic data sets developed by the authors representing Santa Fe, New Mexico; Greensboro, North Carolina; and the San Francisco Bay Area, California.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

A Simple and Accurate Energy-Detector-Based Transient Waveform Detection for Smart Grids: Real-World Field Data Performance

Integration of distributed energy sources, advanced meshed operation, sensors, automation, and communication networks all contribute to autonomous operations and decision-making processes utilized in the grid. Therefore, smart grid systems require sophisticated supporting structures. Furthermore, rapid detection and identification of disturbances and transients are a necessary first step towards situationally aware smart grid systems. This way, high-level monitoring is achieved and the entire system kept operational. Even though smart grid systems are unavoidably sophisticated, low-complexity algorithms need to be developed for real-time sensing on the edge and online applications to alert stakeholders in the event of an anomaly. In this study, the simplest form of anomaly detection mechanism in the absence of any a priori knowledge, namely, the energy detector (also known as radiometer in the field of wireless communications and signal processing), is investigated as a triggering mechanism, which may include automated alerts and notifications for grid anomalies. In contrast to the mainstream literature, it does not rely on transform domain tools; therefore, utmost design and implementation simplicity are attained. Performance results of the proposed energy detector algorithm are validated by real power system data obtained from the DOE/EPRI National Database of power system events and the Grid Signature Library.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Data Center Power Systems: Architectures, Impact on Grid Reliability, Modeling Considerations, and Megawatt-Scale Hardware Testing [Slides]

This slide deck describes typical power systems of large datacenters along with reliability problems to bulk power systems from large-scale integration of datacenters. The slide deck covers the architecture of datacenter power systems, different power electronic converters used inside datacenters, their operation modes, and R&Dopportunities in maintaining grid stability.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Multifold Insights for Power System Dynamics From Data Assimilation: Meeting Current Challenges

The world’s electric power grids have evolved over the last 120 years from a single power line to today’s large networks. The evolution will continue at an accelerated rate with extensive smart grid development worldwide. Here for example, the U.S. government has set a goal of reaching 100 percent carbon pollution-free electricity by 2035, while the Department of Energy (DOE) shared a goal to deploy 30 GW and 110 GW of offshore wind by 2030 and 2050, respectively. To meet such ambitious goals, in the years to come, a significant percentage of electricity will come from intermittent renewable sources, electric vehicles (EVs), and be supplied to a vast number of loads that will actively respond to grid conditions and incentive signals. This development is largely driven by environmental and economic factors, such as reducing carbon emissions and saving electricity cost for consumers. These energy resources lead to new uncertain behaviors and dynamics which the grid has never seen and were not considered in its design. Operating such a dynamic grid with sufficient reliability and efficiency is a monumental challenge.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Real-time simulator and controller of power system using distributed data streaming server

Systems and methods for simulating and controlling a power system in real time, using a controller, are provided. The controller includes a simulation layer to simulate an operation of the power system, a disturbance generation layer to provide data to the simulation layer to disturb the simulated operation of the power system, an application layer to display the simulated operation of the power system and generate a control signal to control, based on the simulated operation of the power system, at least one element of the power system, and a distributed data streaming server (D2S2) to allow interoperability among the simulation layer, the disturbance layer, and the application layer.

Li, Fangxing↗
DOE OSTI2021

Efficient Contingency Analysis in Power Systems via Network Trigger Nodes

Modeling failure dynamics within a power system is a complex and challenging process due to multiple inter-dependencies and convoluted inter-domain relationships. Subject matter experts (SMEs) are interested in understanding these failure dynamics for reducing the impact from future disasters (i.e., losses or failures of power system components, such as transmission lines). Contingency analysis (CA) tools enable such ’what-if’ scenario analyses to evaluate the impacts on the power system. Analyzing all possible contingencies among N system components can be computationally expensive. An important step for performing CA is identifying a set of k ‘trigger’ components, which when failed initially can significantly impact the overall system by causing multiple failures. Currently SMEs focus on identifying these trigger components by running expensive simulations on all possible subsets, which quickly becomes infeasible. Hence finding a relevant set of trigger components (contingencies) rapidly to enable efficient and useful CA is crucial.In a collaboration between computer scientists and power system experts, we propose an efficient method for performing CA by exploiting network inter-dependencies in power system components. First, we construct a network with multiple electric grid infrastructure components and dependencies as connections among them. We reformulate the problem of finding a set of trigger components as a problem of identifying critical nodes in the network, which can cascade power failures through connected nodes and cause significant damage to the network. To guide the practical CA tools, we develop a network-based model with a probabilistic edge-weights setup using intricate domain rules. Then we conduct an empirical study on real power system data in the US for both regional and national levels. Firstly, we use power system datasets for the US to create a national-scale domain-driven model. Secondly, we demonstrate that network-based model outperforms the outputs from a real CA tool and show on average 25 × improved selection of contingencies, thereby showcasing practical benefits to the power experts.

Tabassum, Anika↗
DOE OSTI2020

Distributed Intrusion Detection System using Semantic-based Rules for SCADA in Smart Grid

Cyber-physical system (CPS) security for the smart grid enables secure communication for the SCADA and wide-area measurement system data. Power utilities world-wide use various SCADA protocols, namely DNP3, Modbus, and IEC 61850, for the data exchanges across substation field devices, remote terminal units (RTUs), and control center applications. Adversaries may exploit compromised SCADA protocols for the reconnaissance, data exfiltration, vulnerability assessment, and injection of stealthy cyberattacks to affect power system operation. In this paper, we propose an efficient algorithm to generate robust rule sets. We integrate the rule sets into an intrusion detection system (IDS), which continuously monitors the DNP3 data traffic at a substation network and detects intrusions and anomalies in real-time. To enable CPS-aware wide-area situational awareness, we integrated the methodology into an open-source distributed-IDS (D-IDS) framework. The D-IDS facilitates central monitoring of the detected anomalies from the geographically distributed substations and to the control center. The proposed algorithm provides an optimal solution to detect network intrusions and abnormal behavior. Different types of IDS rules based on packet payload, packet flow, and time threshold are generated. Further, IDS testing and evaluation is performed with a set of rules in different sequences. The detection time is measured for different IDS rules, and the results are plotted. All the experiments are conducted at Power Cyber Lab, Iowa State University, for multiple power grid models. After successful testing and evaluation, knowledge and implementation are transferred to field deployment.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Outage Cause Classification of Power Distribution Systems with Machine Learning and Real-World Data

Power distribution systems are geographically dispersed by nature. It may be affected by various factors, such as vegetation, weather, animal and human behaviors. Present response procedures to an outage event massively rely on expert experience and thus tend to be time-consuming. Automatic outage event detection and classification will help to reduce the responding and restoration time. However, this issue is less addressed with existing research done in this area. In this applied research, a set of waveform pre-processing techniques are first proposed to prepare the waveform data for being used as inputs to the classification algorithm. Further, a machine learning-based algorithm is proposed to classify the outage events according to their root causes, e.g. tree contact, animal contact, lightning, etc. Available data include three phase current & voltage waveforms and contextual information during the distribution system outages. The proposed machine learning algorithm takes the current and voltage waveforms as direct inputs in search of features that humans are unable to capture. Real data provided by a distribution company in the East Tennessee region is used to test the proposed pre-processing techniques and the classification algorithm.

Sun, Haoyuan↗
NASA NTRS2001

Baseline Testing of the Ultracapacitor Enhanced Photovoltaic Power Station

The NASA John H. Glenn Research Center is developing an advanced ultracapacitor enhanced photovoltaic power station. Goals of this effort include maximizing photovoltaic power generation efficiency and extending the life of photovoltaic energy storage systems. Unique aspects of the power station include the use of a solar tracker, and ultracapacitors for energy storage. The photovoltaic power station is seen as a way to provide electric power in remote locations that would otherwise not have electric power, provide independence form utility systems, reduce pollution, reduce fossil fuel consumption, and reduce operating costs. The work was done under the Hybrid Power Management (HPM) Program, which includes the Hybrid Electric Transit Bus (HETB), and the E-Bike. The power station complements the E-Bike extremely well in that it permits the charging of the vehicle batteries in remote locations. Other applications include scientific research and medical power sources in isolated regions. The power station is an inexpensive approach to advance the state of the art in power technology in a practical application. The project transfers space technology to terrestrial use via nontraditional partners, and provides power system data valuable for future space applications. A description of the ultracapacitor enhanced power station, the results of performance testing and future power station development plans is the subject of this report. The report concludes that the ultracapacitor enhanced power station provides excellent performance, and that the implementation of ultracapacitors in the power system can provide significant performance improvements.

Eichenberg, Dennis J.↗
NASA NTRS2001

Baseline Testing of the EV Global E-Bike with Ultracapacitors

The NASA John H. Glenn Research Center initiated baseline testing of the EV Global E-Bike SX with ultracapacitors as a way to reduce pollution in urban areas, reduce fossil fuel consumption, and reduce operating costs for transportation systems. The E-Bike provides an inexpensive approach to advance the state of art in hybrid technology in a practical application. The project transfers space technology to terrestrial use via nontraditional partners, and provides power system data valuable for future space applications. The work was done under the Hybrid Power Management (HPM) Program, which includes the Hybrid Electric Transit Bus (HETB). The E-Bike is a state of the art, ground up, hybrid electrical bicycle. Unique features of the vehicle's power system include the use of an efficient, 400 W electric hub motor, and a seven-speed derailleur system that permits operation as fully electric, fully pedal, or a combination of the two. Other innovative features, such as regenerative braking through ultracapacitor energy storage, are planned. Regenerative braking recovers much of the kinetic energy of the vehicle during deceleration. A description of the E-bike, the results of performance testing, and future vehicle development plans are given in this report. The report concludes that the E-Bike provides excellent performance, and that the implementation of ultracapacitors in the power system can provide significant performance improvements.

Eichenberg, Dennis J.↗
NASA NTRS2003

Baseline Testing of the Club Car Carryall With Asymmetric Ultracapacitors

The NASA John H. Glenn Research Center initiated baseline testing of the Club Car Carryall with asymmetric ultracapacitors as a way to reduce pollution in industrial settings, reduce fossil fuel consumption, and reduce operating costs for transportation systems. The Club Car Carryall provides an inexpensive approach to advance the state of the art in electric vehicle technology in a practical application. The project transfers space technology to terrestrial use via non-traditional partners, and provides power system data valuable for future space applications. The work was done under the Hybrid Power Management (HPM) Program, which includes the Hybrid Electric Transit Bus (HETB). The Carryall is a state of the art, ground up, electric utility vehicle. A unique aspect of the project was the use of a state of the art, long life ultracapacitor energy storage system. Innovative features, such as regenerative braking through ultracapacitor energy storage, are planned. Regenerative braking recovers much of the kinetic energy of the vehicle during deceleration. The Carryall was tested with the standard lead acid battery energy storage system, as well as with an asymmetric ultracapacitor energy storage system. The report concludes that the Carryall provides excellent performance, and that the implementation of asymmetric ultracapacitors in the power system can provide significant performance improvements.

Eichenberg, Dennis J.↗
DOE OSTI2023

Developing Synthetic Distribution Models Using Open-Source Data Sets

The deployment of distributed generation resources at scale with the distribution side of the power system network over the last two decades has spurred a lot of research interest in distribution networks. Given, the sensitive nature of power system data sets, utilities are still reluctant to open-source distribution networks. Although some open-source data sets are available, they may not cover the region of interest. In this paper, we introduce the Synthetic dIstribution Network Generator (SING), new software that allows users to develop synthetic distribution models, using open-source data sets, in any region of interest within the continental US.

data set↗
NASA NTRS2005

The Fuel Cell Powered Club Car Carryall

The NASA Glenn Research Center initiated development of the Fuel Cell Powered Club Car Carryall as a way to reduce pollution in industrial settings, reduce fossil fuel consumption and reduce operating costs for transportation systems. The Club Car Carryall provides an inexpensive approach to advance the state of the art in electric vehicle technology in a practical application. The project transfers space technology to terrestrial use via non-traditional partners, and provides power system data valuable for future aeronautics and space applications. The work was done under the Hybrid Power Management (HPM) Program. The Carryall is a state of the art, dedicated, electric utility vehicle. Hydrogen powered proton exchange membrane (PEM) fuel cells are the primary power source. Ultracapacitors were used for energy storage as long life, maintenance free operation, and excellent low temperature performance is essential. Metal hydride hydrogen storage was used to store hydrogen in a safe and efficient low-pressure solid form. The report concludes that the Fuel Cell Powered Club Car Carryall can provide excellent performance, and that the implementation of fuel cells in conjunction with ultracapacitors in the power system can provide significant reliability and performance improvements.

Eichenberg, Dennis J.↗
DOE OSTI2026

Grid Operator Analytics and Assessment Tools for Inverter- Based Resources Dominated Grid (GOAAT-IBR) Project Update

This presentation provides an update on the OPTIMA GOAAT project, with emphasis on the cloud-native data platform developed in-house to ingest, manage, and operationalize high-resolution power system data. Since our last NASPI presentation, accessible via OSTI ID #2671437, the project team advanced the design and deployment of a scalable architecture capable of handling both synchronized and non-synchronized streams, including PMU, point-on-wave (POW), COMTRADE, and SCADA data. These materials review the project status, recent progress, and key lessons learned. The core of the presentation examines the architecture and engineering of our cloud-native ingestion and data management platform. We then explain how pipelines were designed to collect, normalize, time-align, store, and serve heterogeneous data at scale. We will discuss design choices such as data models, streaming versus batch ingestion, storage tiers, and interoperability with analytics applications. Practical experiences with cloud-native technologies were shared during the event, including benefits, limitations, and integration challenges in a utility environment, along with methods used to improve performance, reduce latency, and optimize resource usage. The presentation also showcases user interface designs and visualization tools that convert raw measurements and analytics results into intuitive, actionable insights for operators and engineers. During the presentation examples were provided demonstrating how visualization, event views, and summarized analytics enhance situational awareness and support operational decision-making. These use cases illustrate how a well-designed data infrastructure can bridge the gap between high-volume measurements and practical grid operations.

Aminifar, Farrokh↗