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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

CIEPAT for Photovoltaic System Resilience

The Cyber-Informed Engineering Photovoltaic Analysis Tool (CIEPAT) was developed in collaboration with the U.S. Department of Energy's Office of Cybersecurity, Energy Security, and Emergency Response (CESER). This tool is an energy source subcomponent integrated into the CIEMAT ecosystem and is developed to enhance the security and resilience of Photovoltaic installations by incorporating Cyber-Informed Engineering (CIE) principles into the deployment of PV systems.

14 SOLAR ENERGY↗
DOE OSTI2023

Cybersecurity for System Operators

SERC's System Operator Conference is an annual education and sustainment training for electric power system operators across the southeastern United States. In recognition of the growing importance of cybersecurity for energy systems, a block of instruction on cybersecurity concepts was included for this year's conferences. This presentation provides an overview of the need for and general approach used in the DOE CESER-sponsored Cybersecurity for the Operational Technology Environment (CyOTE) program, tailored for electric power system operators. NERC's updated Cyber Intrusion Guide for System Operators is reviewed, explaining how it is an operationalization of some of CyOTE's principles and approach.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Opdefender Network Monitoring And Control System

OpDefender is a new system designed to enhance the cyber security of control system networks. It accomplishes this by inspecting each network packet using a novel, patent-pending method that extends software defined networking into the application/ICS protocol layer. OpDefender consists of two key components: 1. Smart, “ICS-aware” network switches that analyze and filter network traffic in real time. 2. A network management human machine interface (HMI) that allows an operator to monitor and control network traffic in real time. The “ICS-aware” switches can serve as a drop-in replacement for typical network switches, or they can be used in conjunction with existing network switches. OpDefender is configured and controlled in real time via a custom-built, web-based HMI designed with the operator in mind.

Johnson, BriamE.↗
DOE OSTI2024

Cy-Phy ADS: Cyber Physical Anomaly Detection Framework for EV Charging Systems

Today’s large-scale Electric Vehicle (EV) infrastructures are heavily dependent on information communication technologies to maintain their operation and to support communication within sub-system components as well as the outside world. These technologies are vulnerable to various cyber and physical threats. Timely identification and mitigation of these threats are critical for improving human safety, avoiding economic losses, and preventing catastrophic system failures. By addressing this, our work presents a ResNet Autoencoder (AE) based Cyber-Physical Anomaly Detection System (Cy-Phy ADS) for detecting anomalies in EV Controller Area Network (CAN) protocol communication. It consists of four main components: Cyber-Physical Feature Extractor, ResNet AE-based Anomaly Detection Framework, Cyber-Physical Health Metric (CPHM), and Visualization Dashboard. The presented framework was trained and tested using CAN data collected from the EV charging system testbed at the Idaho National Laboratory. The presented Cy-Phy ADS compared against six widely used unsupervised anomaly detection algorithms: One Class Support Vector Machine (OCSVM), Variational Autoencoder (VAE), LSTM Autoencoder (LSTM AE), Isolation Forest (IForest), Principle Component Analysis (PCA) and Local Outlier Factor (LOF). Here the presented approach showed the highest accuracy among the compared methods. Further, the proposed approach showed comparable performance in terms of precision, F1, and False positive rate. It also showed the lowest training and inference time compared to the neural network-based baseline algorithms compared against with. Additionally, the Cy-Phy ADS has advantages such as unsupervised training, the ability to provide a holistic metric for system health characterization, and non-linear feature extraction.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Systems and methods for control system security

A resilient security agent determines a cyber and/or physical health of a control system by, inter alia, communicating cyber-physical key data through cyber-physical control paths of the system, and determining error introduced by the communication. The resilient security agent may be further configured to verify the integrity of acquired cyber-physical state information. The cyber health of the control system may be evaluated by comparing the acquired cyber state information to one or more cyber state profiles. The physical health of the control system may be evaluated by comparing the acquired physical state information to one or more physical state profiles.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Application Guide for the Cyber-Resilient Design Framework for Hybrid Systems

As the energy landscape evolves, hybrid power plants—integrating multiple renewable energy sources (e.g., solar, wind, and battery storage) with the bulk power electric system—play a crucial role in meeting growing energy demands. However, with a hybrid power plant’s increased number of components, complex network connectivity and digitization of controls, these systems face growing cybersecurity risks. To help mitigate these risks, Idaho National Laboratory (INL) presents this application guide specifically designed for operators and systems engineers to evaluate the cybersecurity resilience of their hybrid power plant’s design.

14 SOLAR ENERGY↗
DOE OSTI2024

Demystifying Cyberattacks: Potential for Securing Energy Systems With Explainable AI : Preprint

Modernization of energy systems has led to in- creased interactions among multiple critical infrastructures and diverse stakeholders making the challenge of operational decision making more complex and at times beyond cognitive capabilities of human operators. The state-of-the-art machine learning and deep learning approaches show promise of supporting users with complex decision-making challenges, such as those occurring in our rapidly transforming cyber-physical energy systems. However, successful adoption of data-driven decision support technology for critical infrastructure will be dependent on the ability of these technologies to be trustworthy and contextually interpretable. In this paper, we investigate the feasibility of implementing XAI for interpretable detection of cyberattacks in the energy system. Leveraging a proof-of-concept simulation use case of detection of a data falsification attack on a photovoltaic system using XGBoost algorithm, we demonstrate how Local Interpretable Model-Agnostic Explanations (LIME), a flavor XAI approach, can help provide contextual and actionable interpretation of cyberattack detection.

artificial intelligence↗
DOE OSTI2023

Systems and methods for global cyber-attack or fault detection model

An industrial asset may have monitoring nodes that generate current monitoring node values representing a current operation of the industrial asset. An abnormality detection computer may detect when a monitoring node is currently being attacked or experiencing a fault based on a current feature vector, calculated in accordance with current monitoring node values, and a detection model that includes a decision boundary. A model updater (e.g., a continuous learning model updater) may determine an update time-frame (e.g., short-term, mid-term, long-term, etc.) associated with the system based on trigger occurrence detection (e.g., associated with a time-based trigger, a performance-based trigger, an event-based trigger, etc.). The model updater may then update the detection model in accordance with the determined update time-frame (and, in some embodiments, continuous learning).

Xu, Rui↗
DOE OSTI2025

Security of DERs and Grid Edge Technologies [Slides]

Distributed energy resources (DERs) offer significant value for incorporating diverse generation technologies and improving reliability. They also present a new set of cybersecurity challenges. The move of generation to the grid edge can also mean more distributed control systems and expanded communication networks, resulting in an increase in attack surface. This presentation will discuss definitions and essential terms related to DERs; developments and deployment trends for DERs; recent cyber attacks on operational technology and industrial systems; cyber risk arising from distributed grid resources; and ways in which standards may help mitigate some of these risks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
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 OSTI2022

Dynamic, resilient virtual sensing system and shadow controller for cyber-attack neutralization

An industrial asset may have monitoring nodes (e.g., sensor or actuator nodes) that generate current monitoring node values. An abnormality detection and localization computer may receive the series of current monitoring node values and output an indication of at least one abnormal monitoring node that is currently being attacked or experiencing a fault. An actor-critic platform may tune a dynamic, resilient state estimator for a sensor node and output tuning parameters for a controller that improve operation of the industrial asset during the current attack or fault. The actor-critic platform may include, for example, a dynamic, resilient state estimator, an actor model, and a critic model. According to some embodiments, a value function of the critic model is updated for each action of the actor model and each action of the actor model is evaluated by the critic model to update a policy of the actor-critic platform.

Roychowdhury, Subhrajit↗