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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Assessment and Commissioning of Electrical Substation Grid Testbed with a Real-Time Simulator and Protective Relays/Power Meters in the Loop

Electrical utility substations are wired with intelligent electronic devices (IEDs), such as protective relays, power meters, and communication switches. Substation engineers commission these IEDs to assess the appropriate measurements for monitoring, control, power system protection, and communication applications. Like real electrical utility substations, complex electrical substation grid testbeds (ESGTs) need to be assessed for measuring current and voltage signals in monitoring, power system protection, control (synchro check), and communication applications that are limited by small measurement percentage errors. In the process of setting an ESGT with real-time simulators and IEDs in the loop, protective relays, power meters, and communication devices must be commissioned before running experiments. In this study, an ESGT with IEDs and distributed ledger technology was developed. The ESGT with a real-time simulator and IEDs in the loop was satisfactorily assessed and commissioned. The commissioning and problem-solving tasks of the testbed are described to define a method with flowcharts to assess possible trouble-shooting in ESGTs. This method was based on comparing the simulations versus IED measurements for the phase current and voltage magnitudes, three-phase phasor diagrams, breaker states, protective relay times with selectivity coordination at electrical faults, communication data points, and time-stamp sources.

Piesciorovsky, Emilio↗
DOE OSTI2023

Latent Neural ODE for Integrating Multi-Timescale Measurements in Smart Distribution Grids

Under a smart grid paradigm, there has been an increase in sensor installations to enhance situational awareness. The measurements from these sensors can be leveraged for real-time monitoring, control, and protection. However, these measurements are typically irregularly sampled. These measure-ments may also be intermittent due to communication bandwidth limitations. To tackle this problem, this paper proposes a novel latent neural ordinary differential equations (LODE) approach to aggregate the unevenly sampled multivariate time-series measurements. The proposed approach is flexible in performing both imputations and predictions while being computationally efficient. Simulation results on IEEE 37 bus test systems illustrate the efficiency of the proposed approach.

multi time-scale measurements↗
DOE OSTI2023

Electrical substation grid testbed for DLT applications of electrical fault detection, power quality monitoring, DERs use cases and cyber-events

Electrical utilities continue to deploy more intelligent electronic devices (IEDs) inside and outside electrical substation, and are associated with customer-owned distributed energy resources (DERs). The integrity and confidentiality of data from these IEDs, like power meters and protective relays, is crucial. Blockchain technology could improve the resilience of microgrids by improving the security of data sharing. The penetration of customer-owned DERs (renewable energy sources) and the increasing deployment of IEDs can lead to integrate power system applications with Distributed Ledger Technology (DLT). In this study, we implemented the electrical faulted phase detection and power quality monitoring algorithms with a Cyber Grid Guard (CGG) system using DLT. In addition, the DERs (wind turbine farms) use case and protective relay cyber-event tests were assessed, by using the CGG system with DLT. In the experimental model, the testbed was created by using a real-time simulator and CGG system with power meters/ protective relays in-the-loop. The data collected from the CGG system and IEDs were compared with the same time stamp source. These results had shown the successful assessment of protection, control and monitoring applications using a CGG system with DLT. In the future, the ESGT with DERs and the CGG system will be used in other power system applications, based on implementing smart contracts between electrical utilities with customer-owned DERs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Electrical Fault and Power Quality Detection Algorithms and Customer-Owned DERs Monitoring with a Cyber Grid Guard System and DLT

In this study, the electrical fault and power quality detection algorithms and customer-owned DERs monitoring use cases were implemented, with a Cyber Grid Guard system and DLT. Electrical utilities continue to deploy more intelligent electronic devices (IEDs) inside and outside electrical substations, and are associated with customer-owned distributed energy resources (DERs). Data from these IEDs, such as power meters and protection relays, must be kept confidential and of high integrity. Blockchain technology has the potential to increase microgrid resilience by enhancing data sharing security. The growing use of IEDs and customer-owned renewable energy sources (DERs) may make it necessary to connect Distributed Ledger Technology (DLT) with power system applications. We implemented the electrical faulted phase detection and power quality monitoring algorithms with a Cyber Grid Guard (CGG) system using DLT. In addition, the DERs (wind turbine farms) use case and protective relay cyber-event tests were assessed, by using the CGG system with DLT. In the experimental model, the testbed was created by using a real-time simulator and CGG system with power meters/ protective relays in the loop. The data collected from the CGG system and IEDs were compared with the same time stamp source. These results showed the successful assessment of protection, control and monitoring applications using a CGG system with DLT. In the future, power system applications for the ESGT with DERs and the CGG system will be based on executing smart contracts between electrical utilities and customer-owned DERs.

Piesciorovsky, Emilio↗
DOE OSTI2024

Online and Offline Identification of False Data Injection Attacks in Battery Sensors Using a Single Particle Model

The cells in battery energy storage systems are monitored, protected, and controlled by battery management systems whose sensors are susceptible to cyberattacks. False data injection attacks (FDIAs) targeting batteries’ voltage sensors affect cell protection functions and the estimation of critical battery states like the state of charge (SoC). Inaccurate SoC estimation could result in battery overcharging and over discharging, which can have disastrous consequences on grid operations. This paper proposes a three-pronged online and offline method to detect, identify, and classify FDIAs corrupting the voltage sensors of a battery stack. To accurately model the dynamics of the series-connected cells a single particle model is used and to estimate the SoC, the unscented Kalman filter is employed. FDIA detection, identification, and classification was accomplished using a tuned cumulative sum (CUSUM) algorithm, which was compared with a baseline method, the chi-squared error detector. Online simulations and offline batch simulations were performed to determine the effectiveness of the proposed approach. Throughout the batch simulations, the CUSUM algorithm detected attacks, with no false positives, in 99.83% of cases, identified the corrupted sensor in 97% of cases, and determined if the attack was positively or negatively biased in 97% of cases.

25 ENERGY STORAGE↗
DOE OSTI2021

Distribution Grid Modeling Using Smart Meter Data

The knowledge of distribution grid models, including topologies and line impedances, is essential for grid monitoring, control and protection. However, such information is often unavailable, incomplete or outdated. The increasing deployment of smart meters (SMs) provides a unique opportunity to tackle this issue. This paper proposes a two-stage framework for distribution grid modeling using SM data. In the first stage, the network topology is identified by reconstructing a weighted Laplacian matrix of distribution networks. In the second stage, a least absolute deviations (LAD) regression model is developed for estimating line impedance of a single branch based on the nonlinear (inverse) power flow model, wherein a conductor library is leveraged to narrow down the solution space. The LAD regression model is originally a mixed-integer nonlinear program whose continuous relaxation is still non-convex. Furthermore, we specially address its convex relaxation and discuss the exactness. The modified regression model is then embedded within a bottom-up sweep algorithm to achieve the identification across the network in a branch-wise manner. Numerical results on the IEEE 13-bus, 37-bus and 69-bus test feeders validate the effectiveness of the proposed methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Cyber-physical cascading failure and resilience of power grid: A comprehensive review

Smart grid technologies are based on the integration of the cyber network and the power grid into a cyber-physical power system (CPPS). The increasing cyber-physical interdependencies bring about tremendous opportunities for the modeling, monitoring, control, and protection of power grids, but also create new types of vulnerabilities and failure mechanisms threatening the reliability and resiliency of system operation. A major concern regarding the interdependent networks is the cascading failure (CF), where a small initial disturbance/failure in the network results in a seemingly unexpected large-scale failure. Although there has been a significant volume of recent work in the CF research of CPPS, a comprehensive review remains unavailable. This article aims to fill the gap by providing a systematic literature survey regarding the modeling, analysis, and mitigation of CF in CPPS. The open research questions for further research are also discussed. This article allows researchers to easily understand the state of the art of CF research in CPPS and fosters future work required towards full resolutions to the remaining questions and challenges.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Time Synchronization Techniques in the Modern Smart Grid: A Comprehensive Survey

In modern smart grids, accurate and synchronized time signals are essential for effective monitoring, protection, and control. Various time synchronization methods exist, each tailored to specific application needs. Widely adopted solutions, such as GPS, however, are vulnerable to challenges such as signal loss and cyber-attacks, underscoring the need for reliable backup or supplementary solutions. This paper examines the timing requirements across different power grid applications and provides a comprehensive review of available time synchronization mechanisms. Through a comparative analysis of timing methods based on accuracy, flexibility, reliability, and security, this study offers insights to guide the selection of optimal solutions for seamless grid integration.

comparison↗
DOE OSTI2022

Non-Parametric Statistical Analysis of Current Waveforms through Power System Sensors

The protection, control, and monitoring of the power grid is not possible without accurate measurement devices. As the percentage of renewable energy sources penetrating the existing grid infrastructure increases, so do uncertainties surrounding their effects on the everyday operation of the power system. Many of these devices are sources of high-frequency transients. These transients may be useful for identifying certain events or behaviors otherwise not seen in traditional analysis techniques. Therefore, the ability of sensors to accurately capture these phenomena is paramount. In this work, two commercial-grade power system distribution sensors are investigated in terms of their ability to replicate high-frequency phenomena by studying their responses to three events: a current inrush, a microgrid “close-in”, and a fault on the terminals of a wind turbine. Kernel density estimation is used to derive the non-parametric probability density functions of these error distributions and their adequateness is quantified utilizing the commonly used root mean square error (RMSE) metric. It is demonstrated that both sensors exhibit characteristics in the high harmonic range that go against the assumption that measurement error is normally distributed.

47 OTHER INSTRUMENTATION↗
NASA NTRS1990

Precise synchronization of phasor measurements in electric power systems

Phasors representing positive sequence voltages and currents in a power network are in the most important parameters in several monitoring, control, and protection functions in interconnected electric power networks. Recent advances in computer relaying have led to very efficient and accurate phasor measurement systems. When the phasors to be measured are separated by hundreds of miles, it becomes necessary to synchronize the measurement processes, so that a consistent description of the state of the power system can be established. Global Positioning System (GPS) transmissions offer an ideal source for synchronization of phasor measurements. The concept and implementation of this technique are described. Several uses of synchronized phasor measurements are also described. Among these are improved state estimation algorithms, state estimator enhancements, dynamic state estimates, improved control techniques, and improved protection concepts.

Phadke, Arun G.↗
NASA NTRS2010

High-Temperature Optical Sensor

A high-temperature optical sensor (see Figure 1) has been developed that can operate at temperatures up to 1,000 C. The sensor development process consists of two parts: packaging of a fiber Bragg grating into a housing that allows a more sturdy thermally stable device, and a technological process to which the device is subjected to in order to meet environmental requirements of several hundred C. This technology uses a newly discovered phenomenon of the formation of thermally stable secondary Bragg gratings in communication-grade fibers at high temperatures to construct robust, optical, high-temperature sensors. Testing and performance evaluation (see Figure 2) of packaged sensors demonstrated operability of the devices at 1,000 C for several hundred hours, and during numerous thermal cycling from 400 to 800 C with different heating rates. The technology significantly extends applicability of optical sensors to high-temperature environments including ground testing of engines, flight propulsion control, thermal protection monitoring of launch vehicles, etc. It may also find applications in such non-aerospace arenas as monitoring of nuclear reactors, furnaces, chemical processes, and other hightemperature environments where other measurement techniques are either unreliable, dangerous, undesirable, or unavailable.

Adamovsky, Grigory↗
NASA NTRS2011

The Invasive Species Forecasting System

The Invasive Species Forecasting System (ISFS) provides computational support for the generic work processes found in many regional-scale ecosystem modeling applications. Decision support tools built using ISFS allow a user to load point occurrence field sample data for a plant species of interest and quickly generate habitat suitability maps for geographic regions of management concern, such as a national park, monument, forest, or refuge. This type of decision product helps resource managers plan invasive species protection, monitoring, and control strategies for the lands they manage. Until now, scientists and resource managers have lacked the data-assembly and computing capabilities to produce these maps quickly and cost efficiently. ISFS focuses on regional-scale habitat suitability modeling for invasive terrestrial plants. ISFS s component architecture emphasizes simplicity and adaptability. Its core services can be easily adapted to produce model-based decision support tools tailored to particular parks, monuments, forests, refuges, and related management units. ISFS can be used to build standalone run-time tools that require no connection to the Internet, as well as fully Internet-based decision support applications. ISFS provides the core data structures, operating system interfaces, network interfaces, and inter-component constraints comprising the canonical workflow for habitat suitability modeling. The predictors, analysis methods, and geographic extents involved in any particular model run are elements of the user space and arbitrarily configurable by the user. ISFS provides small, lightweight, readily hardened core components of general utility. These components can be adapted to unanticipated uses, are tailorable, and require at most a loosely coupled, nonproprietary connection to the Web. Users can invoke capabilities from a command line; programmers can integrate ISFS's core components into more complex systems and services. Taken together, these features enable a degree of decentralization and distributed ownership that have helped other types of scientific information services succeed in recent years.

Schnase, John↗
DOE OSTI2022

Use of Machine Learning on PMU Data for Transmission System Fault Analysis

Synchrophasor technology has been used for monitoring, control, and protection of bulk power system for over 10 years. Deployment of phasor measurement units (PMUs) in the USA power system has surpassed 3000 units installed in the transmission substations as stand-alone intelligent electronic devices (IEDs) or as a software add-on to other devices such as digital protective relays (DPRs) or digital fault recorders (DFRs). By now, thousands of terabytes of PMU data may have been captured and stored by various transmission system operators (TSOs) and independent system operators (ISOs). This creates an opportunity to deploy advanced machine learning (ML) techniques to detect and classify faults recorded by PMUs automatically to be used by the system operators for rapid, critical decision-making when manual analysis of the past or unfolding events is not feasible. In this paper we offer a brief background on how the automated fault analysis may be done using DPR and/or DFR data, and compare some of the legacy approaches to the new ML approaches in the context of the system-wide PMU recordings. We then offer insights from developing practical ML solutions that have been applied on field recordings captured by close to 450 PMUs from all three US interconnections (Western, Eastern and ERCOT) over two years (2016-2017). We identify and illustrate ML challenges we addressed: inaccurate data, data with scarce and temporally imprecise fault labels, data recorded by PMUs sparsely located at substations resulting in the fault records taken afar from the ends of the faulted lines, data containing only positive sequence values, and data taken at different voltage levels. We then illustrate the ML model results for fault analysis under different application scenarios. The novelty of this study is not only in the design, implementation, and performance analysis of the ML algorithms, but also in the use of advanced fault modelling and simulation approaches to improve the training results when developing supervised ML models for fault detection and classification. Extensive simulations of faults were conducted on a 14-bus power system to create a training dataset with over 1400 accurately labelled faults. This dataset was applied to enhance the accuracy of fault detection and classification of machine learning-based models trained with small number of labelled faults in large datasets recorded in the grid interconnections ranging from 5,000 to 70,000 buses.

Synchrophasors, Machine Learning, Fault Analysis, ↗
NASA NTRS1992

Power system monitoring and source control of the Space Station Freedom DC power system testbed

Unlike a terrestrial electric utility which can purchase power from a neighboring utility, the Space Station Freedom (SSF) has strictly limited energy resources; as a result, source control, system monitoring, system protection, and load management are essential to the safe and efficient operation of the SSF Electric Power System (EPS). These functions are being evaluated in the DC Power Management and Distribution (PMAD) Testbed which NASA LeRC has developed at the Power System Facility (PSF) located in Cleveland, Ohio. The testbed is an ideal platform to develop, integrate, and verify power system monitoring and control algorithms. State Estimation (SE) is a monitoring tool used extensively in terrestrial electric utilities to ensure safe power system operation. It uses redundant system information to calculate the actual state of the EPS, to isolate faulty sensors, to determine source operating points, to verify faults detected by subsidiary controllers, and to identify high impedance faults. Source control and monitoring safeguard the power generation and storage subsystems and ensure that the power system operates within safe limits while satisfying user demands with minimal interruptions. System monitoring functions, in coordination with hardware implemented schemes, provide for a complete fault protection system. The objective of this paper is to overview the development and integration of the state estimator and the source control algorithms.

Kimnach, Greg L.↗
NASA NTRS1992

Power system monitoring and source control of the Space Station Freedom dc-power system testbed

Unlike a terrestrial electric utility which can purchase power from a neighboring utility, the Space Station Freedom (SSF) has strictly limited energy resources; as a result, source control, system monitoring, system protection, and load management are essential to the safe and efficient operation of the SSF Electric Power System (EPS). These functions are being evaluated in the dc Power Management and Distribution (PMAD) Testbed which NASA LeRC has developed at the Power System Facility (PSF) located in Cleveland, Ohio. The testbed is an ideal platform to develop, integrate, and verify power system monitoring and control algorithms. State Estimation (SE) is a monitoring tool used extensively in terrestrial electric utilities to ensure safe power system operation. It uses redundant system information to calculate the actual state of the EPS, to isolate faulty sensors, to determine source operating points, to verify faults detected by subsidiary controllers, and to identify high impedance faults. Source control and monitoring safeguard the power generation and storage subsystems and ensure that the power system operates within safe limits while satisfying user demands with minimal interruptions. System monitoring functions, in coordination with hardware implemented schemes, provide for a complete fault protection system. The objective of this paper is to overview the development and integration of the state estimator and the source control algorithms.

Kimnach, Greg L.↗
NASA NTRS1984

Contamination control and cleanliness level integrity for the Space Shuttle Orbiter PLB, payloads and facilities at KSC

The PLB, its cargo, and payload canister must satisfy the cleanliness requirements of visual clean (VC) level 1, 2, 3, or special as stated in NASA document SN-C-0005A. The specific level of cleanliness is chosen by the payload bay customer for their mission. During orbiter turnaround processing at KSC, the payload bay is exposed to the environments of the Orbiter Processing Facility (OPF) and the Payload Changeout Room (PCR). In supportive response to the orbiter payload bay/facility interface, it is necessary that the facility environment be controlled and monitored to protect the cleanliness/environmental integrity of the payload bay and its cargo. Techniques used to meet environmental requirements during orbiter processing are introduced.

Bartelson, D.↗
NASA NTRS1986

BLSS, a European approach to CELSS

Several studies have revealed the benefits of a biological life support system (BLSS) in space stations. Problem areas requiring experimental and analytical investigations necessary for the development of BLSS have been identified. The nature of these problems allows for the classification into near-term (prepilot) and long-term (pilot) studies, and into terrestrial and space research programmes. The knowledge of planned European and U.S. space experiments allows for a coordination with existing Spacelab and Shuttle programmes to avoid duplication of research efforts. The Japanese also plan biological experiments on Spacelab in 1988. Coordinating efforts should provide answers to certain BLSS relevant questions. Major areas which need immediate attention are: micorgravity effects; cosmic radiation effects; use of PAR-radiation and high energy particle radiation protection; and monitoring and control (including sensor technology).

Skoog, A. I.↗
NASA NTRS1990

Servicing capability for the evolutionary Space Station

Since the beginning of the Space Station Freedom (SSF) program the concept of on-orbit servicing of user hardware has been an integral part of the program implementation. The user servicing system architecture has been divided into a baseline and a growth phase. The baseline system consists of the following hardware elements that will support user servicing - flight telerobotic servicer, crew and equipment translation aid, crew intravehicular and extravehicular servicing support, logistics supply system, mobile servicing center, and the special purpose dextrous manipulator. The growth phase incorporates a customer servicing facility (CSF), a station-based orbital maneuvering vehicle and an orbital spacecraft consumables resupply system. The requirements for user servicing were derived from the necessity to service attached payloads, free flyers and coorbiting platforms. These requirements include: orbital replacement units (ORU) and instrument changeout, National Space Transportation System cargo bay loading and unloading, contamination control and monitoring, thermal protection, payload berthing, storage, access to SSF distributed systems, functional checkout, and fluid replenishment. The baseline user servicing capabilities accommodate ORU and instrument changeout. However, this service is limited to attached payloads, either in situ or at a locally adjacent site. The growth phase satisfies all identified user servicing requirements by expanding servicing capabilities to include complex servicing tasks for attached payloads, free-flyers and coorbiting platforms at a dedicated, protected Servicing site. To provide a smooth evolution of user servicing the SSF interfaces that are necessary to accommodate the growth phase have been identified. The interface requirements on SSF have been greatly simplified by accommodating the growth servicing support elements within the CSF. This results in a single SSF interface: SSF to the CSF.

Thomas, Edward F.↗