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At least 19 records

Cybersecurity Incident Response Guide for Wind

As wind energy systems become increasingly digitized and interconnected, they face a growing array of cyber threats that can disrupt operations, compromise safety, and trigger cascading impacts across the energy ecosystem. The Wind Incident Response Guide provides a structured, wind-specific framework for preparing for, detecting, responding to, and recovering from cyber incidents. Drawing on lessons from field demonstrations, cyber-physical testbeds, and stakeholder engagement across the wind sector, this guide integrates technical, operational, and regulatory considerations to support asset owners, operators, and responders. It outlines key roles and responsibilities, maps incident response phases to wind-specific scenarios, and highlights applicable laws, regulations, standards, and best practices. By tailoring general cybersecurity principles to the unique architectures and operational constraints of wind systems—including remote access, legacy components, and environmental interfaces—this guide aims to enhance resilience, reduce response time, and support coordinated action across public and private stakeholders. It is intended as a practical resource for utilities, developers, regulators, and emergency managers working to secure the future of wind energy.

17 - WIND ENERGY

PAIRS, The GIS-Based Incident Response System for Pennsylvania, and NASA

Over the past several years the Pennsylvania Departments of Environmental Protection (DEP), Health (DOH), and Agriculture (PDA) built the GIs-based Pennsylvania West Nile Surveillance System. That system has become a model for collecting data that has a field component, laboratory component, reporting and mapping component, and a public information component. Given the success of the West Nile Virus System and the events of September 11, 2001, DEP then embarked on the development of the Pennsylvania Incident Response System, or PAIRS. PAIRS is an effective GIs-based approach to providing a system for response to incidents of any kind, including terrorism because it is building upon the existing experience, infrastructure and databases that were successfully developed to respond to the West Nile Virus by DEP, DOH, and PDA. The proposed system can be described as one that supports data acquisition, laboratory forensics, decision making/response, and communications. Decision makers will have tools to view and analyze data from various sources and, at the same time, to communicate with the large numbers of people responding to the same incident. Recent collaborations with NASA partners are creating mechanisms for the PAIRS system to incorporate space-based and other remote sensing geophysical parameters relevant to public health assessment and management, such as surface temperatures, precipitation, land cover/land use change, and humidity. This presentation will describe the PAIRS system and outline the Pennsylvania-NASA collaboration for integration of space-based data into the PAIRS system.

Conrad, Eric

AR4IR (Automated Reasoning for Incident Response) [SWR-24-103]

A basic formal methods tool with the ability to aid and/or automate a utilities’ incidence response and instills confidence that the proposed action satisfies the system’s physical constraints, the organization’s cyber policies, and will not cause violations of technical standards.

Etigowni, Sriharsha [National Renewable Energy Lab

Uncertainty Analysis of Inhalation Dose Coefficients for Nuclear Incident Response

This study addressed the need to characterize variability in inhalation dose coefficients due to uncertainties in respiratory tract deposition, systemic biokinetics, and physiological parameters. A Python-based implementation of the International Commission on Radiological Protection Publication 66 Human Respiratory Tract Model was developed called the Radiological Exposure Dose Calculator (REDCAL) to propagate parameter uncertainty.

61 RADIATION PROTECTION AND DOSIMETRY

NFPA Distributed Energy Resources Safety Training (DERST) For Emergency Responders

The National Fire Protection Association, with support from the Department of Energy, executed a multi-year initiative to develop, enhance, and disseminate Distributed Energy Resources Safety Training (DERST) tools for U.S. emergency responders. As Distributed Energy Resources (DER)—such as solar photovoltaics, battery energy storage systems (ESS), electric vehicles (EVs), and associated infrastructure—become increasingly prevalent, the NFPA identified a critical need for up-to-date standardized, accessible, and effective safety training tailored for the fire service and related public safety professionals. The project delivered a comprehensive suite of educational resources to improve responders’ abilities to safely manage DER-related incidents. This included: • Revised Modular Training Courses: Updated classroom-based DER safety courses, now modular and accessible nationwide through fire academies and the North American Fire Training Directors (NAFTD) network. • Live Burn Testing & Research: A full-scale controlled burn of a DER-equipped residential structure provided real-world data and insights, forming the basis for updated best practices. • A Gamified Simulation Tool – Firefighters Incident Response Simulation Tool (FIRST): A first-of-its-kind, multiplayer, scenario-based simulation using the Unreal Engine 5.0 to train responders in a realistic virtual, multi-DER incident environment. • Field Familiarization Software Tools & Prop Guide: Digital DER field familiarization evolutions software guide and a prop development manual to support field-based DER training exercises, enhancing responders' hands-on familiarity with DER infrastructure and collaboration on virtual incident responses. • National Dissemination Strategy: Strategic partnerships with NAFTD, Vector Solutions, and others enabled wide-scale distribution, with over 5,000 departments accessing resources and 1,100+ departments adopting the simulator in the first seven months. Also provided a web portal for easy access to all training and simulation programs developed under this grant for the U.S. responder community. Key findings from the project—particularly from the burn test—led to paradigm shifts in fire response tactics. For example, traditional approaches to garage fires may be hazardous if DERs are present, due to explosive off gassing and thermal runaway risks. The new training emphasizes scene assessment, stand-off approaches, thermal imaging verification, and careful post-incident cooling of DER components to prevent reignition. This initiative has had a significant national impact, raising awareness, enhancing preparedness, and supporting safer DER incident response practices. Significant engagement from the media, public safety organizations, and PBS coverage has further amplified the reach and adoption of NFPA’s DER safety training, tools, and simulations.

14 SOLAR ENERGY

(abstract) A Mobile Robot for Remote Response to Incidents Involving Hazardous Materials

This paper will report the status of the Emergency Response Robotics project, a teleoperated mobile robot system being developed at JPL for use by the JPL Fire Department/HAZMAT Team. The project, which began in 1991, has been focused on developing a robotic vehicle which can be quickly deployed by HAZMAT Team personnel for first entry into an incident site. The primary goals of the system are to gain access to the site, locate and identify the hazard, and aid in its mitigation. The involvement of JPL Fire Department/HAZMAT Team personnel has been critical in guiding the design and evaluation of the system. A unique feature of the current robot, called HAZBOT III, is its special design for operation in combustible environments. This includes the use of all solid state electronics, brushless motors, and internal pressurization. Demonstration and testing of the system with HAZMAT Team personnel has shown that teleoperated robots, such as HAZBOT III, can successfully gain access to incident sites locating and identifying hazardous material spills. Work is continuing to enable more complex missions through the addition of appropriate sensor technology and enhancement of the operator interface.

robots teleoperator hazardous materials HAZMAT HAZ

Intern Deliverable Poster 2025

An Incident Response Plan (IRP) is a document that is created and maintained by an organization that provides guidance in the event of a cyber incident. The primary objectives of an IRP are to aid in the detection, response, and recovery from incidents, as well as to enhance preparation and preventative measures. An IRP should outline specific procedures at each stage of an incident, with the goal of minimizing asset damage, data leakage, and operational impact. By investing in a well-defined IRP, organizations can better manage and mitigate risks associated with cyber threats, ensuring business continuity and resilience. This poster summarizes incident response guidelines for wind energy, which faces unique cybersecurity and physical challenges.

17 - WIND ENERGY

A Mobile Robot for Remote Response to Incidents Involving Hazardous Materials

This paper will describe a teleoperated mobile robot system being developed at JPL for use by the JPL Fire Department/HAZMAT Team. The project, which began in October 1990, is focused on prototyping a robotic vehicle which can be quickly deployed and easily operated by HAZMAT Team personnel allowing remote entry and exploration of a hazardous material incident site. The close involvement of JPL Fire Department personnel has been critical in establishing system requirements as well as evaluating the system. The current robot, called HAZBOT III, has been especially designed for operation in environments that may contain combustible gases. Testing of the system with the Fire Department has shown that teleoperated robots can successfully gain access to incident sites allowing hazardous material spills to be remotely located and identified. Work is continuing to enable more complex missions through enhancement of the operator interface and by allowing tetherless operation.

robots teleoperator hazardous materials HAZMAT HAZ

Applying Satellite Data to Support Disaster Response and Emergency Management Decision Making

Using the vantage point of space, satellite observations provide information about the Earth that can serve a critical role in building situational awareness and filling in data gaps during disaster response. NASA’s Earth Science Division ( studies the Earth as a system and develops technologies to improve the quality of life here on our home planet. Within NASA ESD, the Disasters Program and its Disasters Response Coordination System (DRCS) aims to advance Earth science data and information to support management decisions that prevent or mitigate the impacts of disasters. Using a whole-of-NASA approach to coordinate and mobilize the Agency’s assets and expertise to provide geospatial information during disasters, this work brings the utility of Earth observation information to emergency management and disaster response and reduces the impacts of disasters on lives and livelihoods .This poster will introduce the utility of satellite and geospatial information to disaster response through examples of recent DRCS incident response activations and highlight the DRCS model that employs a user-centered activation framework beginning with direct requests from responders and ending with after-action assessments that feed lessons learned and process improvements.

Remote Sensing

Optimization of two dimensional gratings for very long wavelength quantum well infrared photodetectors

We have performed a detailed study of two-dimensional grating coupling for quantum well infrared photodetectors in the very long wavelength spectral region lambda is approximately 16 - 17 microns. Using calculations based on the modal expansion method we quantitatively explain the double peaked responsivity spectrum. By optimizing the grating parameters we achieve a normal incidence responsivity and detectivity which are three times larger than the 45 deg angle of incidence geometry.

Sarusi, G.

Advanced Reactor Safeguards & Security Program: Cybersecurity Scenarios

The use of digital control systems and automation in advanced nuclear power systems introduces different types of vulnerabilities compared to legacy (i.e. analog) control systems that cyber adversaries can exploit. These vulnerabilities pose a challenge to reactor operators and cyber operations staff due to the dynamic nature of the event in which a human response or a lack of response can potentially evolve into a worsening plant condition. Using the Department of Homeland Security Cyber and Infrastructure Security Agency’s (CISA) critical infrastructure exercise framework, this document presents several cyber security scenarios typical of digital control systems that could be used in advanced reactor designs. These scenarios can be used in tabletop exercises to evaluate cyber security posture or conduct training on different aspects of cyber security, including detection, threat hunting using indicators of compromise, evaluating incident response, risk mitigation, incident reporting, information sharing and recovery.

22 GENERAL STUDIES OF NUCLEAR REACTORS

Fire Front Detection and Tracking for Autonomous sUAS in STEReO

The Scalable Traffic Management Emergency Response Operations (STEReO) project aims to incorporate unmanned aerial systems (UAS) into wildfire incident response to safely quicken response times, improve operator awareness, and scale-up aircraft operations.Autonomous UAS can be used to relieve human operators of dull, dirty, and dangerous tasks such as checking for re-ignitions and geo-locating fires. To geo-locate fires, the UAS must be able to detect whether a fire is present and also have the necessary information to stamp a location. Furthermore, the UAS should be able to track the fire front to determine the extent of the fire. This study presents a fire front detection and tracking methodology for an autonomous small UAS (sUAS). The methodology is evaluated in simulation.

Autonomous UAV,Wildfire,Detection,Tracking

Validating Protection System Behavior with Machine Learning in a Master State Overseer

As power system protection devices continue the widespread transition from analog to digital, they become increasingly intricate. The internal functions and communication between critical grid components must now be significantly more complex to keep up with the demands of the modern smart grid. This brings increased difficulty in maintenance and monitoring, making it harder to identify potential misoperation, power anomalies, and cyber threats. Such issues are often only pinpointed after an exhaustive and costly post-mortem analysis, when a major outage or damage has already occurred. A solution is needed for validating protection systems as they operate, independently evaluating grid state and confirming whether the protection system is behaving accordingly. As opposed to incident response, this acts as a constant verification mechanism that raises a flag when subtler issues are noticed, catching them earlier and preventing larger incidents. This work presents the implementation of such a system, expanding on the prototype developed by the authors in a previous paper. This is accomplished with a machine learning (ML) system capable of validating the performance of protection systems by classifying anomalous events and characterizing protection system responses based solely on available current and voltage measurements. Additionally, this system is contextualized within a larger, modular Master State awareness Overseer (MSO) framework, responsible for monitoring, analyzing, and managing an electric grid.

24 - POWER TRANSMISSION AND DISTRIBUTION

Machine Learning Framework for Hazard Extraction and Analysis of Trends (HEAT) in Wildfire Response

This research proposes a natural language processing enabled risk analysis framework, named Hazard Extraction andAnalysis of Trends (HEAT), and applies the framework to the ICS-209-PLUS data set of wildfire incident responseforms. The HEAT framework produces safety- and risk- relevant analyses, consisting of: (1) a set of hazards extractedfrom text data, (2) a primary analysis using hazard-relevant metrics, such as rate and severity, to form an FMEA-styletable and risk matrix, (3) a time series analysis of metric trends, and (4) a secondary analysis examining potentialpredictors for hazards. Results from HEAT provide quantitative risk-relevant information for high-level hazards doc-umented in existing-state operations. Because of the generalizability of the steps and limited data requirements, HEATcan be applied to any dataset containing narrative text, thus providing a framework for data-driven machine learning-enabled quantitative risk analysis across a variety of domains. To demonstrate HEAT in a case study, we apply theframework to the ICS-209-PLUS dataset of wildland fire incident response forms. Hazards identified in wildfire re-sponse arise from environmental conditions, the mission, and the wildland urban interface. The resulting risk matrixidentifies evacuations as high-risk hazards, while all other identified hazards are medium or serious risk.

natural language processing