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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Studying impacts of communication system performance on dynamic stability of networked microgrid

The development of smart grid technologies has resulted in increased interdependence between power and communication systems. Many of the operations in the existing power system rely on a stable and secured communication system. For electrically weak systems and time‐critical applications, this reliance can be even greater, where a small degradation in communication performance can degrade system stability. However, despite inter‐dependencies between power and communication systems, only a few studies have investigated the impacts of communication system performance on power system dynamics. This study investigates the dependencies of power system dynamics operations on a communication system performance. First, a detailed, dynamic networked microgrid model is developed in the GridLAB‐D simulation environment, along with a representative multi‐traffic, multi‐channel, multi‐protocol communication system model, developed in the network simulator (ns‐3). Second, a hierarchical engine for large‐scale infrastructure co‐simulation framework is developed to co‐simulate microgrid dynamics, its communication system, and a microgrid control system. The impact of communication system delays on the dynamic stability of networked microgrids is evaluated for the loss of generation using three use‐cases. While the example use‐cases examine microgrid applications and the impact to resiliency, the framework can be applied to all levels of power system operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Detecting False Data Injection Attacks Against Power System State Estimation With Fast Go-Decomposition Approach

State estimation is a fundamental function in modern energy management system, but its results may be vulnerable to false data injection attacks (FDIAs). FDIA is able to change the estimation results without being detected by the traditional bad data detection algorithms. In this paper, we propose an accurate and computational attractive approach for FDIA detection. In this work, we first rely on the low rank characteristic of the measurement matrix and the sparsity of the attack matrix to reformulate the FDIA detection as a matrix separation problem. Then, four algorithms that solve this problem are presented and compared, including the traditional augmented Lagrange multipliers (ALMs), double-noise-dual-problem (DNDP) ALM, the low rank matrix factorization, and the proposed new “Go Decomposition (GoDec).” Numerical simulation results show that our GoDec algorithm outperforms the other three alternatives and demonstrates a much higher computational efficiency. Furthermore, GoDec is shown to be able to handle measurement noise and applicable for large-scale attacks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

A Review of Edge Computing Technology and Its Applications in Power Systems

Recent advancements in network-connected devices have led to a rapid increase in the deployment of smart devices and enhanced grid connectivity, resulting in a surge in data generation and expanded deployment to the edge of systems. Classic cloud computing infrastructures are increasingly challenged by the demands for large bandwidth, low latency, fast response speed, and strong security. Therefore, edge computing has emerged as a critical technology to address these challenges, gaining widespread adoption across various sectors. This paper introduces the advent and capabilities of edge computing, reviews its state-of-the-art architectural advancements, and explores its communication techniques. A comprehensive analysis of edge computing technologies is also presented. Furthermore, this paper highlights the transformative role of edge computing in various areas, particularly emphasizing its role in power systems. It summarizes edge computing applications in power systems that are oriented from the architectures, such as power system monitoring, smart meter management, data collection and analysis, resource management, etc. Additionally, the paper discusses the future opportunities of edge computing in enhancing power system applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Leveraging graph clustering techniques for cyber‐physical system analysis to enhance disturbance characterisation

Abstract Cyber‐physical systems have behaviour that crosses domain boundaries during events such as planned operational changes and malicious disturbances. Traditionally, the cyber and physical systems are monitored separately and use very different toolsets and analysis paradigms. The security and privacy of these cyber‐physical systems requires improved understanding of the combined cyber‐physical system behaviour and methods for holistic analysis. Therefore, the authors propose leveraging clustering techniques on cyber‐physical data from smart grid systems to analyse differences and similarities in behaviour during cyber‐, physical‐, and cyber‐physical disturbances. Since clustering methods are commonly used in data science to examine statistical similarities in order to sort large datasets, these algorithms can assist in identifying useful relationships in cyber‐physical systems. Through this analysis, deeper insights can be shared with decision‐makers on what cyber and physical components are strongly or weakly linked, what cyber‐physical pathways are most traversed, and the criticality of certain cyber‐physical nodes or edges. This paper presents several types of clustering methods for cyber‐physical graphs of smart grid systems and their application in assessing different types of disturbances for informing cyber‐physical situational awareness. The collection of these clustering techniques provide a foundational basis for cyber‐physical graph interdependency analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Intelligent Buildings of the Future: Cyberaware, Deep Learning Powered, and Human Interacting

This study discuss, intelligent buildings are quickly becoming cohesive and integral entities of cyber-physical ecosystems. Modern buildings adapt to internal and external elements and thrive on ever increasing data sources such as ubiquitous smart devices and sensors while mimicking various approaches previously known in software, hardware, and bio inspired systems. This article provides an overview of intelligent buildings of the future from a range of perspectives. First, a brief overview of prospects of U.S. and world energy consumption, concepts of smart buildings as integral entities of smart grids is presented. This is followed by a discussion of the role of connectivity and interoperability as well as current issues and solutions in the areas of security, resilience, and humans in realm of intelligent buildings. The article dives into detail about the intelligence aspect of intelligent buildings of the future. The learning and predictive Artificial Intelligence (AI) techniques behind many of the concepts of intelligent buildings are reviewed, including the latest techniques such as deep learning. As a concrete application of AI in the realm of intelligent buildings, prediction of energy consumption/load/demand, which is a much researched application of AI in the realm of intelligent buildings, is elaborated. The discussion is focused on most recent advancements of AI based demand prediction and the overview consists of existing research and a case study conducted by the authors for deep learning based demand prediction. Then, the article discusses the role of humans in intelligent buildings. Different types of human-building interactions are identified. Further, the article presents how each type of human-building interaction can benefit the overall control of intelligent buildings. The section is concluded by elaborating a case study conducted by the authors to achieve effective and efficient human-building interaction. The article is concluded with compilation of future insights based on latest technological advancements in U.S. industry and government.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

The IEC 61850 Sampled Measured Values Protocol: Analysis, Threat Identification, and Feasibility of Using NN Forecasters to Detect Spoofed Packets

The operation of the smart grid is anticipated to rely profoundly on distributed microprocessor-based control. Therefore, interoperability standards are needed to address the heterogeneous nature of the smart grid data. Since the IEC 61850 emerged as a wide-spread interoperability standard widely accepted by the industry, the Sampled Measured Values method has been used to communicate digitized voltage and current measurements. Realizing that current and voltage measurements (i.e., feedback measurements) are necessary for reliable and secure noperation of the power grid, firstly, this manuscript provides a detailed analysis of the Sampled Measured Values protocol emphasizing its advantages, then, it identifies vulnerabilities in this protocol and explains the cyber threats associated to these vulnerabilities. Secondly, current efforts to mitigate these vulnerabilities are outlined and the feasibility of using neural network forecasters to detect spoofed sampled values is investigated. It was shown that although such forecasters have high spoofed data detection accuracy, they are prone to the accumulation of forecasting error. Accordingly, this paper also proposes an algorithm to detect the accumulation of the forecasting error based on lightweight statistical indicators. The effectiveness of the proposed methods is experimentally verified in a laboratory-scale smart grid testbed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Cyber‐Resilient Distributed Energy Resource Control Algorithms for Smart Distribution Grids

ABSTRACT This paper focuses on the development of cyber‐resilient gradient‐based optimisation algorithms and theoretical proof for grid‐interactive distributed energy resource (DER) control to enable two grid services of virtual power plants (VPPs) dispatch and grid voltage regulation, considering the communication and security impacts. Firstly, the combined DER dispatch and voltage regulation as a real‐time gradient‐based optimisation problem is recapped. Thereafter, we consider a probabilistic traffic model to characterise packet delays and loss in a communication network, and study how the delays enter the process of information exchange among the grid measurement units, local DER controllers and the grid control centre that execute this control algorithm in a coordinated manner. Then, a strategy combining delay thresholds and message update rules is proposed to immunity the asynchrony resulting from the communications traffic and it avoids possible numerical instabilities and sensitivities of the power tracking and voltage regulation capabilities, resulting as cyber‐resilient DER control algorithms. Additionally, their convergence is theoretically proved. Effectiveness of proposed cyber‐resilient algorithms has been validated on the IEEE 37‐bus system in terms of convergence, VPP tracking and voltage regulation performance for smart distribution systems with high penetration of DERs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Blockchain cybersecurity audit platform

A cybersecurity distributed ledger is provided herein for managing, tracking, auditing, and securing assets in a power infrastructure. The cybersecurity distributed ledger may include a blockchain, and may combine with smart contract or smart negotiation technology, such as in a permissioned proof of authority blockchain. The cybersecurity distributed ledger may manage the complete life cycle of a grid asset, from asset requirement and specification, through production, testing, deployment, maintenance, and retirement. The cybersecurity distributed ledger may create an immutable record of the grid asset, which may be audited for regulatory compliance or build or development compliance. Further, the cybersecurity distributed ledger may store unique identifying information for a grid asset, which may be used to detect a security breach or other tampering with a grid asset. The cybersecurity distributed ledger may also track control or ownership of the grid asset, as well as changes or updates to the grid asset.

Mylrea, Michael E.↗
DOE OSTI2014

TRAJECTORY SENSITIVITY ANALYSIS FOR DYNAMIC SECURITY ASSESSMENT AND OTHER APPLICATIONS IN POWER SYSTEMS

Real time stability evaluation and preventive scheduling in power systems offer many challenges in a stressed power system. Trajectory sensitivity analysis (TSA) is a useful tool for this and other applications in the emerging smart grid area. In this chapter we outline the basic approach of TSA, to extract suitable information from the data and develop reliable metrics or indices to evaluate proximity of the system to an unstable condition. Trajectory sensitivities can be used to compute critical parameters such as clearing time of circuit breakers, tie line flow, etc. in a power system by developing suitable norms for ease of interpretation. The TSA technique has the advantage that model complexity is not a limitation, and the sensitivities can be computed numerically. Suitable metrics are developed from these sensitivities. The TSA technique can be extended to do preventive rescheduling. A brief discussion of other applications of TSA in placement of distributed generation is indicated.

critical parameter computation↗
DOE OSTI2017

Hiding Critical Targets in Smart Grid Networks

With the integration of advanced communication technologies, the power grid is expected to greatly enhance efficiency and reliability of future power systems. However, since most electrical devices in power grid substations are connected via communication networks, cyber security of these communication networks becomes a critical issue. Real-World incidents such as Stuxnet have shown the feasibility of compromising a device in the power grid network to further launch more sophisticated attacks. To deal with security attacks of this spirit, this paper aims to hide critical targets from compromised internal nodes and hence protect them from further attacks launched by those compromised nodes. In particular, we consider substation networks and propose to add carefully-controlled dummy traffic to a substation network to make critical target nodes indistinguishable from other nodes in network traffic patterns. This paper describes the design and evaluation of such a scheme. Evaluations show that the scheme can effectively protect critical nodes with acceptable communication cost.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

A High Performance Computational Framework for Dynamic Security Assessment under Uncertainty

Dynamic security assessment (DSA) is a critical function to evaluate power grids’ capability to survive the transition caused by a set of disturbances to an acceptable steady-state condition. Its computational burden is heavy. With the challenges brought by renewable energy and new smart grid technologies, DSA under uncertainty has to be considered to study the impact of forecast errors on DSA simulation, which further increases the computational burden. To address this challenge, this paper presents a high performance computational framework to support DSA simulation user uncertainty. The computational framework aims to provide a seamless workflow that links data from high performance computing, statistical analysis, to visualization so that a problem can be easily expressed in a way compatible with different functions. It also enables software compatibility such that application development can be more efficient. Case study results of the ESCA60 system and a western U.S. size system show the advantages and efficiency of the computational framework.

dynamic security assessment, high performance comp↗
DOE OSTI2020

Attack-resilient algorithms and testbed federation for wide-area protection and control in smart grid

Today’s energy infrastructure is undergoing a massive transformation across all generation, transmission, and distribution systems to provide reliability, efficiency, and sustainability to the power system network. During the past 10 years, there has been a remarkable enhancement in developing close-loop wide-area protection and control (WAPAC) applications, such as automatic generation control (AGC), wide-area protection scheme (WAPS), synchrophasor-based wide-area voltage control system (WAVCS), etc., in the energy management system (EMS) to provide an adequate situational awareness to control center operators during physical disturbances and natural events. The rapid digitalization, unencrypted communication, and numerous data-sharing devices have increased digital access points that have exposed the grid network to countless cyberattacks pertinent to the WAPAC cybersecurity. Given the amount of complex grid network coupled with legacy infrastructures, it is untrustworthy to completely rely on information technology (IT)-based conventional security measures to defend against evolving cyberattacks. Hence, there is a compelling need to go beyond the traditional paradigm of ‘security by obscurity’ and ‘bolt-on’ security measures, and develop a suite of innovative security solutions at multiple layers to transform the current “fault-resilient” grid into “fault and attack-resilient” grid of the future. This dissertation specifically focuses on developing application-specific attack-resilient solutions for critical WAPAC applications in the smart grid. The first part of the study, Attack-Resilient Wide-Area Protection Scheme, presents a cyber-physical attack-resilient system (CPARS) for WAPS, where two anomaly detection methods are proposed to detect multi-level cyberattacks followed by the rules-based intrusion mitigation system (RIMS) to initiate effective mitigation strategies, tailored to these attacks, to restore the normal grid operation after disturbances. The first anomaly detection component, Machine learning-based Anomaly Detection for Centralized WAPS, discusses a novel architecture and methodology for developing a machine-learning-based anomaly detection system (ADS) for the centralized wide-area protection system (CWAPS) by applying the variational mode decomposition (VMD) technique and decision tree (DT) algorithms using cyber logs and synchrophasor measurements. The second component, Multi-Agent-based Anomaly Detection for Decentralized WAPS, presents a two-level hierarchical multi-agent-based decentralized WAPS against the system-aware stealthy cyber-attacks. Finally, for the RIMS, the state transition diagram-based mitigation measures are defined based on the grid operation states and experimental testing and evaluation are presented in a cyber-physical testbed environment. The second part of the study, Attack-Resilient Wide-Area Voltage Control System, addresses the existing vulnerabilities in the wide-area voltage control system (WAVCS), presents the methodology for performing an impact analysis during data integrity attacks, and proposes a data-driven attackresilient system (DARS) by incorporating machine learning-based ADS and rules-based anomaly mitigation system (RAMS) to detect these attacks and provide necessary mitigation actions to maintain the transient voltage stability after disturbances. Finally, the third part, Networked Federation Testbed (NEFTSec) for Smart Grid Cybersecurity, focuses on developing an interconnected federated testbed through a common network like the internet, describes its conceptual architectures, and also presents its design components for experimental testing, validation, and evaluation. Further, it presents the co-simulation interface algorithm (CIA) to facilitate the geographically-dispersed real-time distributed simulation (GD-RTDS) during the cyber-physical federation. In general, this dissertation presents innovative attack-resilient solutions for WAPAC applications that are experimentally tested and evaluated using the PowerCyber testbed and NEFTSec platform to accelerate the transition of state-of-the-art research works to the real-field deployments.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Cybersecurity Considerations and Research Pathways for Grid-Interactive Efficient Buildings

Federal facilities serve critical missions and functions that require safe, reliable, and efficient operations. Digitization of several facility operations has increased the cost-effectiveness of energy usage and optimization of energy system performance. As the building controls landscape shifts to become more connected and smarter, building operators now face unique opportunities and challenges to adopt smart enabled devices that can lower energy usage while also optimizing building system performance. The grid-interactive efficient buildings (GEB) initiative aims to make buildings cleaner and more flexible through these smart devices. Smart enabled devices allow greater connectivity and control through remote operations and provide crucial data for analytics and increased efficiency. GEBs enable demand flexibility that has the potential to reduce electrical costs and transform the grid edge where buildings connect to power grids. This operation of interconnected systems, if not designed with cybersecurity practices, causes security gaps and introduces potential attack paths by adversarial and non-adversarial entities leading to disruption of operations.

building controls↗
DOE OSTI2022

Cyber-Physical Security and Resiliency Analysis Testbed for Critical Microgrids with IEEE 2030.5: Preprint

IEEE 2030.5, also known as the Common Smart Inverter Standard (CSIP) is a protocol that specifies the interface between the end user and the smart grid. This standard was proposed recently, and provides many functions which if implemented incorrectly might lead to vulnerabilities. This paper proposes a cyber-physical microgrid testbed using OpenDSS and IEEE 2030.5 that can be used to study the performance of the CSIP protocol various scenarios. For critical microgrid installations, it is essential that the critical loads are served in spite of multiple contingencies. A resiliency analysis is performed for a military microgrid to study its performance and the results are analyzed.

CVSS↗
DOE OSTI2019

Recommended Functionalities for Improving Cybersecurity of Distributed Energy Resources: Preprint

The legacy electric grid is transitioning into a 'present' modern grid due to increasing penetration of intermittent renewable generation at the distribution side, also known as distributed energy resources (DERs). Monitoring and control of such DERs requires extensive data-exchange and bidirectional communication networks. This bidirectional communication paves the way to cyber vulnerabilities and risks for new kinds of cyber-attacks that may have destructive impacts on power system operations. Since IEEE Std. 1547-2018 does not discuss cybersecurity measures for DERs, cybersecurity controls should be developed for securing DER systems at all three levels: 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. These practical recommended functionalities have been discussed and verified with the industry through a DER cybersecurity working group and are meant to improve the device level security of DERs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2013

Large-Scale Data Challenges in Future Power Grids

This paper describes technical challenges in supporting large-scale real-time data analysis for future power grid systems and discusses various design options to address these challenges. Even though the existing U.S. power grid has served the nation remarkably well over the last 120 years, big changes are in the horizon. The widespread deployment of renewable generation, smart grid controls, energy storage, plug-in hybrids, and new conducting materials will require fundamental changes in the operational concepts and principal components. The whole system becomes highly dynamic and needs constant adjustments based on real time data. Even though millions of sensors such as phase measurement units (PMUs) and smart meters are being widely deployed, a data layer that can support this amount of data in real time is needed. Unlike the data fabric in cloud services, the data layer for smart grids must address some unique challenges. This layer must be scalable to support millions of sensors and a large number of diverse applications and still provide real time guarantees. Moreover, the system needs to be highly reliable and highly secure because the power grid is a critical piece of infrastructure. No existing systems can satisfy all the requirements at the same time. We examine various design options. In particular, we explore the special characteristics of power grid data to meet both scalability and quality of service requirements. Our initial prototype can improve performance by orders of magnitude over existing general-purpose systems. The prototype was demonstrated with several use cases from PNNL’s FPGI and was shown to be able to integrate huge amount of data from a large number of sensors and a diverse set of applications.

Smart Grid, Real Time, Commercial Products, Big Da↗