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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 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

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↗
DOE OSTI2021

Review of Power System Support Functions for Inverter-Based Distributed Energy Resources - Standards, Control Algorithms, and Trends

Penetration of renewable energy in power systems has been increasing in the past decades in response to increased global electricity demand and concerns for the environment. Distributed energy resources (DERs) based on renewables have experienced rapid growth thanks to the incentive programs and broad-based participation. With the growing prevalence of DERs, the risk of grid instability and vulnerability increases due to the intermittent nature of renewable energy. At the same time, the voltage and frequency deviation problems emerge more often when the reverse power flow occurs under supply-demand imbalance in distributed power systems. Standards and grid codes have been issued for DER inverters to interconnect with the distribution grid. The updated standard and grid codes expect DERs to provide a variety of power system support functions in order to incorporate higher DER penetration and to maximize DER value to the grid. This paper provides an overview of the power system support functions from renewable DER inverters, which are categorized as: voltage regulation by active/reactive power control, frequency regulation by active power control, voltage ride-through, and frequency ride-through. The benefits and drawbacks of each algorithm are presented and compared with its predecessor, manifesting the logic in the evolution of the algorithms.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Failure Mode and Effects Analysis (FMEA) for Photovoltaic Inverter

Photovoltaic (PV) inverters are critical yet vulnerable components in modern energy systems, often acting as reliability bottlenecks that increase the levelized cost of energy (LCOE). To address this, this paper presents a comprehensive Failure Mode and Effects Analysis (FMEA) tailored for PV inverters. Leveraging field data and literature, we identify failure-prone components, such as capacitors,, and relays, and prioritize their risks based on quantitative Risk Priority Numbers (RPNs). The analysis reveals that surge-induced MOV short circuits, capacitor degradation, and environmental cooling fan failures dominate the risk profile. These findings provide a targeted framework for reliability improvement, guiding future efforts in predictive diagnostics, design optimization, and accelerated life testing strategies.

14 SOLAR ENERGY↗
DOE OSTI2021

Hardware-in-the-Loop Testbed for Cyber-Physical Security of Photovoltaic Farms

In the last decades, modem grids with distributed energy resources, such as photovoltaic (PV) farms, are increasingly vulnerable to cyber-attacks that seriously affect the stability and performance of the power system. While cyber-physical security of smart grids is extensively studied, most of the existing work focuses on the grid level and neglects the modeling and features of device-level power electronics converters (PECs). Furthermore, establishing a high-fidelity simulation testbed that can simulate harmonic frequencies of the PV farm is in urgent need. In this paper, a high-fidelity and real-time hardware-in- the-loop testbed is built to simulate the harmonics of power electronics converters for cyber-physical security of PEC-enabled PV farms. Based on this testbed, the impact of typical cyber-attacks and physical faults on the PV converter can be analyzed, thus providing a foundation for cyber-attack detection, root cause diagnosis, and resilient control to mitigate the adverse effects of cyber-attacks.

14 SOLAR ENERGY↗
DOE OSTI2025

Pulsar Movement Animation and its Corresponding Signal Visualization for Timing Source

The global positioning system, widely used for synchronization in energy systems, faces vulnerabilities, while Pulsars—natural cosmic clocks—offer long-term stability as potential backup timing sources. Existing research lacks sufficient exploration of Pulsar signal animation under astrophysical factors, limiting practical applications. This study establishes a mathematical model based on the rotation dynamics of dual-beam Pulsars and implements dynamic signal visualization through MATLAB. The model dynamically illustrates the relative motion between Pulsar beams and observers via timeline calculations, beam intensity modeling, and rotation matrix derivation. A case study on the millisecond Pulsar J1939+2134 reveals that observer angles influence signal peak timing, while beam widths determine signal duration, highlighting the critical role of parameter calibration for timing accuracy. Open-source code and animation results are publicly shared, providing tools for interdisciplinary research. This study validates the feasibility of Pulsar-based timing in energy systems, offering new insights to enhance synchronization robustness.

Wu, Ori [ORNL] (ORCID:0000000326723410)↗
DOE OSTI2020

A Review of Machine Learning Applications in Power System Resilience

The integration of power electronics enabled devices and the high penetration of renewable energy drastically increase the complexity of power system operation and control. Power systems are still vulnerable to large-scale blackouts caused by extreme natural events or man-made attacks. With the recent development in artificial intelligence technique, machine learning has shown a processing ability in computational, perceptual and cognitive intelligence. It is an urgent challenge to integrate the advanced machine learning technology and large amount of real-time data from wide area measurement systems and intelligent electronic devices, in order to effectively enhance power system resilience and ensure the reliable and secure operation of power systems. Therefore, this paper aims to systematically review the existing application of machine learning methods on power system resilience enhancement, to expand the interest of researchers and scholars in this topic, and to jointly promote the application of artificial intelligence in the field of power systems.

Deep Learning↗
DOE OSTI2021

Cyber-Physical Event Emulation-Based Transmission-and-Distribution Co-Simulation for Situational Awareness of Grid Anomalies (SAGA)

Energy management of transmission and distribution networks (T&D) is becoming more challenging with the accelerated adoption of distributed energy resources (DERs)-such as distributed photovoltaic generation and battery energy storage systems (BESS)-on the electric grid. To better analyze the impacts of DERs on both transmission and distribution systems, a comprehensive T&D co-simulation platform is developed. Further, with DERs more actively participating in system operation-e.g., by providing real-time grid services-their cyber vulnerability needs to be better understood to maintain system reliability. This paper discusses a cyber-physical events emulation-based T&D co-simulation platform to perform comprehensive cyber events emulations, physical simulation, and analysis of interdependent impacts. Results from the case studies-which show how cyber events on a synthetic distribution network can impact operations on the transmission and distribution network-validate that the proposed T&D cosimulation platform can perform cyber-physical events emulation and produce response in near realtime; therefore, with extensive simulation using the proposed co-simulation platform, the system operators can accumulate adequate training data for system situational awareness of grid anomalies.

anomalies detection↗
DOE OSTI2024

ByzSec — A Multi-layered Byzantine Resilient Architecture for Bulk Power System Protective Relays

Reliability, selectivity, and sensitivity are the fundamental attributes of any protection system, acting as the main drivers in the selection of schemes, and equipment. In high-voltage systems, microprocessor-based relays represent the industry’s preferred solution, providing engineers with a vast array of benefits. However, they remain vulnerable to cybersecurity events that may compromise their functionality. To help mitigate against potential cybersecurity risks, this paper presents a fault-tolerant, Byzantine Resilient (BR) architecture that significantly increases the cybersecurity attributes of a protection system while minimizing the amount of performance impacts and integration overheads introduced. The solution relies on an array of independent relays that utilize robust consensus methods (based on Spire [1], [2]) to ensure correct system behavior is achieved even when a relay has been compromised. Furthermore, the solution has been complemented with a custom-built Situational Awareness engine that can be used to detect and identify potential threats. The implemented solution has been developed in consultation with three hardware vendors and has been tested to comply with the performance requirements of a 345kV differential protection scheme (87T). The results indicate that the proposed architecture is a comprehensive solution that: supports the strict correctness and performance requirements of the bulk power grid while providing a cost-effective alternative that offers a seamless, long-term solution.

byzantine security, Fault Tolerant Application Sof↗
DOE OSTI2023

Towards Smart Grids Enhanced Situation Awareness: A Bi-Level Quasi-Static State Estimation Model

Smart Grid situational awareness is provided by Energy Management Systems. A core process of these systems is State Estimation. The great majority of state estimators model the Smart Grid through a set of nonlinear algebraic equations, named the measurement model. Problem formulation considers the Gauss solution. Several model improvements have been presented regarding the Gauss solution, aiming between others to provide measurement noise robustness to the state estimation process. While considerable effort has been focused on such developments, state estimation is still constrained by the implicit modelling error, and thus inevitably vulnerable to cyber-threats. In this work, a state estimation bi-level formal model is presented towards Smart Grids enhanced situational awareness considering the concepts of synthetic measurements and innovation. Comparative test results with the state-of-the-art on the IEEE 14-bus system are presented highlighting improved situational awareness to bad data. Easy-to-implement model, without hard-to-derive parameters, built-on the classic weighted least squares solution, highlight potential aspects for real-life implementation.

cyber security↗
DOE OSTI2023

Wildfire Risk Evaluation Framework for Grid Operations and Planning

The United States (US) environmental protection agency's (EPA's) climate change indicators for wildfires show a long-term trend of increased annual wildfire activity, larger wildfire size, and more variable dynamics in wildfire behavior. This has caused more frequent preemptive public safety power shutoff (PSPS) events in the regions with recognized high wildfire risk. These preemptive power shutoffs attempt to prevent the ignition of a wildfire but it nonetheless renders the transmission line non-operational, which often sheds load of downstream communities. As wildfires and PSPS events become more frequent, it is crucial to find the communities most at risk of load shedding. To that end, this paper proposes the wildfire risk evaluation of the system (WiRES) framework, which is a performance-based framework that translates extreme weather-related and PSPS event probabilities into a cumulative probability of a non-operational transmission line. This study also provides a geospatial visualization tool that breaks down the entire western electrical coordinating council (WECC) region into 50 km grid cells which can be used to 1) filter out transmission lines with higher than a threshold outage probability, and 2) graphically discover the affected regions and their biophysical and socioeconomic metrics. %such as the social vulnerability index, population density, gross domestic product, etc. Lastly, an impact assessment study is conducted which connects the results of the proposed framework to python and powerworld-based contingency analysis to highlight the applicability of the framework.

Wildfire, Resilience, Extreme Events, Grid Reslien↗
DOE OSTI2026

SDN-Based Smart Cyber Switching (SCS) for Cyber Restoration of a Digital Substation

In recent years, critical infrastructure and power grids have increasingly been targets of cyber-attacks, causing widespread and extended blackouts. Digital substations are particularly vulnerable to such cyber incursions, jeopardizing grid stability. This paper addresses these risks by proposing a cybersecurity framework that leverages software-defined networking (SDN) to bolster the resilience of substations based on the IEC- 61850 standard. The research introduces a strategy involving smart cyber switching (SCS) for mitigation and concurrent intelligent electronic device (CIED) for restoration, ensuring ongoing operational integrity and cybersecurity within a substation. The SCS framework improves the physical network’s behavior (i.e., leveraging commercial SDN capabilities) by incorporating an adaptive port controller (APC) module for dynamic port management and an intrusion detection system (IDS) to detect and counteract malicious IEC-61850-based sampled value (SV) and generic object-oriented system event (GOOSE) messages within the substation’s communication network. The framework’s effectiveness is validated through comprehensive simulations and a hardware-in-the-loop (HIL) testbed, demonstrating its ability to sustain substation operations during cyber-attacks and significantly improve the overall resilience of the power grid.

Liu, Chen-Ching (ORCID:0000000289417958)↗
DOE OSTI2021

BACKFLIP: Identification of Materials and Changes Upon Aging of Emerging Fluoropolymer-Free and Industry-Benchmark PV Backsheets

Extending lifetimes of photovoltaic (PV) modules and decreasing manufacturing and decommissioning costs are motivating research of novel PV module backsheet materials. Backsheet integrity is critical to the safety and performance of a PV module, however, the polymeric materials are often vulnerable to environmental degradation. The long-term durability of emerging polyolefin (PO) materials is being examined to inform regarding the possible replacement of laminated backsheets containing polyethylene terephthalate (PET) cores and fluoropolymer protective inner/outer layers. This study compares traditional PET-based backsheets with novel, co-extruded, and recyclable PO-based backsheets after being subjected to hygrometric and UV photolytic accelerated weathering. A large set of characterization methods will compare physical, chemical, structural, mechanical, and insulating properties of these backsheets and the resulting mini-module (MiMo) PV performances. The study of chemical composition, glass- and phase-transition temperatures, degree of crystallinity, and crystalline structure are described here.

mini-module↗
DOE OSTI2020

Impact of Aggregated PV on Subsynchronous Torsional Interaction: Preprint

This paper investigates induced oscillation (specifically subsynchronous torsional interactions) in power systems arising from photovoltaic (PV) power modulation. Time domain simulations of a modified IEEE first-benchmark system are presented and analyzed. In the IEEE benchmark system, a PV generator was added at the same bus where the synchronous generator is connected. The impact of different parameters of the PV inverters volt-volt-ampere reactive (volt-var) curve on SSTI is examined. The most severe impact found arises from the time response of the inverters reactive power change. A second-order time response with natural frequency matching the rotor speed deviation oscillation frequency and low-damping ratio quickly drives the system to an unstable region. Although it is highly unlikely that conditions necessary for distributed energy resource-induced oscillations would occur in the field, with knowledge of this vulnerability in mind, inverters' control parameters can be designed to avoid it.

aggregated↗
DOE OSTI2020

Quantitative Prediction of Perovskite Stability Using Accelerated Testing and Machine Learning

PV technologies based on hybrid perovskites offer the potential for reducing solar cell costs, but they are particularly vulnerable to degradation by environmental factors such as moisture, oxygen, and illumination. Commercialization will require not only stable materials and device architectures but also accelerated testing protocols and models that can predict degradation from the accelerated testing data. Here, we report results from in situ photoluminescence (PL) and photoconductivity (PC) measurements during perovskite degradation with simultaneous optical transmittance (Tr) measurements or reflected dark field (DF) imaging. From PL, PC, Tr, and DF, we determine (respectively) the steady-state quasi-Fermi level splitting, the mean effective carrier diffusion length, the extent of conversion of perovskite to higher bandgap degradation products, and the extent of scattering from domains with different orientation or composition, all as a function of time during degradation. Simultaneous measurement of PL-PC-Tr or PL-PC-DF on perovskite absorbers in an environmental chamber over a wide range of humidity, oxygen, temperature, and illumination levels yields a rich data set. We use machine learning to develop a model that accurately predicts (within 10%) the time for the diffusion length to decrease to 85% of its initial value. The model takes the environmental conditions and the first few measurements from the PL-PC-Tr or PL-PC-DF experiment as input. Thus, the model provides a framework to interpret the results of accelerated testing of absorber materials. One of the dominant features in the model of degradation for CH 3 NH 3 PbI 3 is the initial rate at which transmittance increase. For devices with opaque contacts, the pixel-averaged rate of change of the intensity in dark-field images can be used in place of transmittance. Results are also presented on full PV devices with in-situ current-voltage (JV) measurements. Here, the data from simultaneous PL-DF-JV under environmental stresses reveal intimate connection between degradation and shunts and provide a framework to extend accelerated testing to devices. Further, the presentation reveals underlying universal behavior in degradation pathways over a broad range of environmental stresses and perovskite compositions.

14 SOLAR ENERGY↗
DOE OSTI2019

Development of a Host-Based Intrusion Detection and Control Device for Industrial Field Control Devices

Industrial control systems contain a multitude of devices deployed into the field to observe and control a physical process. Currently, most of these devices lack common host-based cybersecurity features, which can lead them to be seen as vulnerable targets. The Cymbiote device was developed to address this problem by examining multiple streams of data to determine what might indicate a potential threat, and to evaluate and execute appropriate response actions. This paper discusses the evolution of the Cymbiote device in response to evaluation and testing done on real-world hardware. Experimental results are discussed, as are the new developments that have been made to the device in response to the findings. In addition, we describe future research directions for this approach along with the experimental setup changes in response to the requirements for statistical rigor.

Rice, Theora R.↗
DOE OSTI2019

Demonstration of the Cybersecurity Framework through Real-world Cyber Attack

The Cybersecurity Framework (CSF) developed by the National Institute of Standards and Technology Cybersecurity, provides five concurrent and continuous functions to Identify, Protect, Detect, Respond, and Recover from cyber threats and vulnerabilities to buildings. Based on the core architecture and security best practices defined in the CSF guidelines, we developed the CSF webtools. The CSF webtools provide actionable functions that can be easily adopted by a facility operator to enhance their critical infrastructure security. The essence is captured in a set of “how-to” instructions for the facility operators to adopt, adapt, and apply to their critical infrastructure facilities. When considered together, these functions provide a high-level, strategic view of the lifecycle of an organization’s cybersecurity risk management. The CSF webtools provide an easy to follow set of cybersecurity best practices, policies, and procedures to improve the cybersecurity posture of our nation’s buildings and other critical infrastructures. The CSF webtools are also designed to facilitate communication of cybersecurity activities and outcomes across the organization from the executive to operations levels. Finally, the CSF webtools allow the critical infrastructure operators to assess the overall cybersecurity maturity and posture. The goal of this paper is to demonstrate the capabilities of the CSF webtools through an illustrative cyber-attack based on a real-world scenario.

cybersecurity framework, maturity model, critical ↗
DOE OSTI2020

Recommended Functionalities for Improving Cybersecurity of Distributed Energy Resources

The current electric grid is transitioning through increasing penetration of distributed energy resources (DERs), which include intermittent renewable generation resources on the distribution side. Both the monitoring and control of DERs require extensive data-exchange and communication networks. These networks lead to cyber vulnerabilities and risks of new kinds of cyberattacks that may be extremely destructive for power system operations. Although current standards, such as IEEE Std. 1547-2018, do not discuss cybersecurity measures for DERs, cybersecurity controls should be developed for securing DER systems at the device level, communications level, and applications level. This paper discusses the current industry's best practices related to DER cybersecurity and proposes recommended functionalities for improving the cybersecurity posture of DERs, specifically at the device/distribution level. These practical recommendations have been discussed and verified with the industry through a DER cybersecurity working group.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

On the Limits of EM Based Detection of Control Logic Injection Attacks In Noisy Environments

The difficulty in applying traditional security mechanisms in Industrial Control System (ICS) environments makes a large portion of these mission-critical assets vulnerable to cyber attacks. Therefore, there is a dire need for the development of novel security mechanisms specifically designed to protect such critical systems. Recently a lot of attention has been given to mechanisms that exploit the EM emanations of devices for defense purposes. Such practices may lead to the development of robust external and non-intrusive anomaly detection systems. Nevertheless, the majority of current work in the area neglects to consider the implications of real-life environments, particularly environmental noise. In this work, we explore the limits of EM-based anomaly detection towards identifying injection attacks in control logic software in noisy environments. Our study conducted upon both synthetically generated and real signals identified that indeed environmental noise might significantly degrade the accuracy of the anomaly detection process. Experiments done upon synthetic data indicated that assuming that signals are captured with high sampling rates, even minor code injections can be detected with above-90% accuracy in noisy environments where SNR is up to -2dB. This is true even if naive detection methods are considered. Moreover, experiments done using a real-life testbed attest that even single-instruction injections can be detected with near-perfect accuracy in relatively clean environments. Finally, noise-elimination techniques can drastically improve the reliability of the detection mechanism even in noisy environments.

97 MATHEMATICS AND COMPUTING↗