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DOE OSTI2024

Network Security Challenges and Countermeasures for Software-Defined Smart Grids: A Survey

The rise of grid modernization has been prompted by the escalating demand for power, the deteriorating state of infrastructure, and the growing concern regarding the reliability of electric utilities. The smart grid encompasses recent advancements in electronics, technology, telecommunications, and computer capabilities. Smart grid telecommunication frameworks provide bidirectional communication to facilitate grid operations. Software-defined networking (SDN) is a proposed approach for monitoring and regulating telecommunication networks, which allows for enhanced visibility, control, and security in smart grid systems. Nevertheless, the integration of telecommunications infrastructure exposes smart grid networks to potential cyberattacks. Unauthorized individuals may exploit unauthorized access to intercept communications, introduce fabricated data into system measurements, overwhelm communication channels with false data packets, or attack centralized controllers to disable network control. An ongoing, thorough examination of cyber attacks and protection strategies for smart grid networks is essential due to the ever-changing nature of these threats. Previous surveys on smart grid security lack modern methodologies and, to the best of our knowledge, most, if not all, focus on only one sort of attack or protection. This survey examines the most recent security techniques, simultaneous multi-pronged cyber attacks, and defense utilities in order to address the challenges of future SDN smart grid research. The objective is to identify future research requirements, describe the existing security challenges, and highlight emerging threats and their potential impact on the deployment of software-defined smart grid (SD-SG).

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DOE OSTI2024

Communication Network Layer State Estimation Measurement Model for a Cyber-Secure Smart Grid

Network communication has been proven to be a very important tool and a key factor in the recent development and progress of the power grid operation. It is also considered as the foundation for the smart grid because information and communication are integrated into electricity distribution to achieve reliable and accurate knowledge of the power grid. In previous years, absorbing energy from substations and delivering it to customers was the only type of interaction we knew between utility companies and customers. Presently, the growing connections of small distributed generation units caused by the cost reduction of most of the technologies used in generation and storage of electrical energy, along with the potential benefits of renewable energy have pushed many researchers to look into the improvement of information and communication technologies (ICT) in order to ensure a bidirectional flow of power and data. Moreover, the evolution of information and communication technologies and its applications to smart grid have converted the smart grid into a cyber-physical system where vulnerabilities and additional security challenges such as cyber-threats and cyber-attacks have emerged. Previously, we have demonstrated that using machine learning-based processing on data gathered from communication networks and the power grid was a promising solution for detecting cyber threats by implementing a co-simulation of cyber-security for cross-layer strategy. Since the majority of the challenges observed can only be solved in the network communication layer, we present in this work a physics-based state estimation model of the communication network system towards enhanced cyber-physical security of the smart grid. Information integration with the previously developed machine learning model is developed, providing a enhanced cyber-physical security application for the smart grid. Easy-to-implement model, without hard-to-derive parameters, highlight potential aspects of the model for real-life applications.

Mathieu, Reynold↗
DOE OSTI2015

Smart Grid Demonstration Project (Final Report)

The National Rural Electric Cooperative Association (NRECA) organized the NRECA-U.S. Department of Energy (DOE) Smart Grid Demonstration Project (DE-OE0000222) to install and study a broad range of advanced smart grid technologies in a demonstration that spanned 23 electric cooperatives in 12 states. More than 205,444 pieces of electronic equipment and more than 100,000 minor items (bracket, labels, mounting hardware, fiber optic cable, etc.) were installed to upgrade and enhance the efficiency, reliability, and resiliency of the power networks at the participating co-ops. The objective of this project was to build a path for other electric utilities, and particularly electrical cooperatives, to adopt emerging smart grid technology when it can improve utility operations, thus advancing the co-ops’ familiarity and comfort with such technology. Specifically, the project executed multiple subprojects employing a range of emerging smart grid technologies to test their cost-effectiveness and, where the technology demonstrated value, provided case studies that will enable other electric utilities—particularly electric cooperatives— to use these technologies. NRECA structured the project according to the following three areas: Demonstration of smart grid technology; Advancement of standards to enable the interoperability of components; and Improvement of grid cyber security. We termed these three areas Technology Deployment Study, Interoperability, and Cyber Security. Although the deployment of technology and studying the demonstration projects at coops accounted for the largest portion of the project budget by far, we see our accomplishments in each of the areas as critical to advancing the smart grid. All project deliverables have been published. Technology Deployment Study: The deliverable was a set of 11 single-topic technical reports in areas related to the listed technologies. Each of these reports has already been submitted to DOE, distributed to co-ops, and posted for universal access at www.nreca.coop/smartgrid. This research is available for widespread distribution to both cooperative members and non-members. These reports are listed in Table 1.2. Interoperability: The deliverable in this area was the advancement of the MultiSpeak™ interoperability standard from version 4.0 to version 5.0, and improvement in the MultiSpeak™ documentation to include more than 100 use cases. This deliverable substantially expanded the scope and usability of MultiSpeak™, the most widely deployed utility interoperability standard, now in use by more than 900 utilities. MultiSpeak™ documentation can be accessed only at www.multispeak.org. Cyber Security: NRECA’s starting point was to develop cyber security tools that incorporated succinct guidance on best practices. The deliverables were: cyber security extensions to MultiSpeak™, which allow more security message exchanges; a Guide to Developing a Cyber Security and Risk Mitigation Plan; a Cyber Security Risk Mitigation Checklist; a Cyber Security Plan Template that co-ops can use to create their own cyber security plans; and Security Questions for Smart Grid Vendors.

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DOE OSTI2022

Authentication of smart grid communications using quantum key distribution

Smart grid solutions enable utilities and customers to better monitor and control energy use via information and communications technology. Information technology is intended to improve the future electric grid’s reliability, efficiency, and sustainability by implementing advanced monitoring and control systems. However, leveraging modern communications systems also makes the grid vulnerable to cyberattacks. Here we report the first use of quantum key distribution (QKD) keys in the authentication of smart grid communications. In particular, we make such demonstration on a deployed electric utility fiber network. The developed method was prototyped in a software package to manage and utilize cryptographic keys to authenticate machine-to-machine communications used for supervisory control and data acquisition (SCADA). This demonstration showcases the feasibility of using QKD to improve the security of critical infrastructure, including future distributed energy resources (DERs), such as energy storage.

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DOE OSTI2023

Machine Learning-based Intrusion Detection for Smart Grid Computing: A Survey

Machine learning (ML)-based intrusion detection system (IDS) approaches have been significantly applied and advanced the state-of-the-art system security and defense mechanisms. In smart grid computing environments, security threats have been significantly increased as shared networks are commonly used, along with the associated vulnerabilities. However, compared to other network environments, ML-based IDS research in a smart grid is relatively unexplored, although the smart grid environment is facing serious security threats due to its unique environmental vulnerabilities. In this article, we conducted an extensive survey on ML-based IDS in smart grids based on the following key aspects: (1) The applications of the ML-based IDS in transmission and distribution side power components of a smart power grid by addressing its security vulnerabilities; (2) dataset generation process and its usage in applying ML-based IDSs in the smart grid; (3) a wide range of ML-based IDSs used by the surveyed papers in the smart grid environment; (4) metrics, complexity analysis, and evaluation testbeds of the IDSs applied in the smart grid; and (5) lessons learned, insights, and future research directions.

SCADA↗
DOE OSTI2014

Smart Grid Status and Metrics Report

To convey progress made in achieving the vision of a smart grid, this report uses a set of six characteristics derived from the National Energy Technology Laboratory Modern Grid Strategy. It measures 21 metrics to provide insight into the grid’s capacity to embody these characteristics. This report looks across a spectrum of smart grid concerns to measure the status of smart grid deployment and impacts.

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DOE OSTI2015

Pacific Northwest Smart Grid Demonstration Project Technology Performance Report Volume 1: Technology Performance

The Pacific Northwest Smart Grid Demonstration (PNWSGD), a $179 million project that was co-funded by the U.S. Department of Energy (DOE) in late 2009, was one of the largest and most comprehensive demonstrations of electricity grid modernization ever completed. The project was one of 16 regional smart grid demonstrations funded by the American Recovery and Reinvestment Act. It was the only demonstration that included multiple states and cooperation from multiple electric utilities, including rural electric co-ops, investor-owned, municipal, and other public utilities. No fewer than 55 unique instantiations of distinct smart grid systems were demonstrated at the projects’ sites. The local objectives for these systems included improved reliability, energy conservation, improved efficiency, and demand responsiveness. The demonstration developed and deployed an innovative transactive system, unique in the world, that coordinated many of the project’s distributed energy resources and demand-responsive components. With the transactive system, additional regional objectives were also addressed, including the mitigation of renewable energy intermittency and the flattening of system load. Using the transactive system, the project coordinated a regional response across the 11 utilities. This region-wide connection from the transmission system down to individual premises equipment was one of the major successes of the project. The project showed that this can be done and assets at the end points can respond dynamically on a wide scale. In principle, a transactive system of this type might eventually help coordinate electricity supply, transmission, distribution, and end uses by distributing mostly automated control responsibilities among the many distributed smart grid domain members and their smart devices.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

A Novel Authentication Management for the Data Security of Smart Grid

Bidirectional wireless communication is employed in various smart grid components such as smart meters and control and monitoring applications where security is vital. The Trusted Third Party (TTP) and wireless connectivity between the smart meter and the third party in the key management-based encryption techniques for the smart grid are expected to be totally trustworthy and dependable. In a wired/wireless medium, however, a man-in-the-middle may seek to disrupt, monitor and manipulate the network, or simply execute a replay attack, revealing its vulnerability. Recognizing this, this study presents a novel authentication management (model) comprised of two layer security schema. The first layer implements an efficient novel encryption method for secure data exchange between meters and control center with the help of two partially trusted simple servers (constitutes the TTP). In this setting, one server handles the data encryption between the meter and control center/central database, and the other server administers the random sequence of data transmission. The second layer monitors and verifies exchanged data packets among smart meters. It detects abnormal packets from suspicious sources. To implement this node-to-node authentication, One class support vector machine algorithm is proposed which takes advantages of the location information as well as the data transmission history (node identification, packet size, and data transmission frequency). This schema secures data communication, and imposes a comprehensive privacy throughout the system without considerably extending the complexity of the conventional key management scheme.

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DOE OSTI2015

Role of Smart Grids in Integrating Renewable Energy

This report was prepared for the International Smart Grid Action Network (ISGAN), which periodically publishes briefs and discussion papers on key topics of smart grid development globally. The topic of this report was selected by a multilateral group of national experts participating in ISGAN Annex 4, a working group that aims to produce synthesis insights for decision makers. This report is an update of a 2012 ISGAN Annex 4 report entitled “Smart Grid Contributions to Variable Renewable Resource Integration.” That report and other past publications of ISGAN Annexes can be found at www.iea-isgan.org and at www.cleanenergysolutions.org.

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DOE OSTI2014

NSTAR Smart Grid Pilot

NSTAR Electric & Gas Corporation (“the Company”, or “NSTAR”) developed and implemented a Smart Grid pilot program beginning in 2010 to demonstrate the viability of leveraging existing automated meter reading (“AMR”) deployments to provide much of the Smart Grid functionality of advanced metering infrastructure (“AMI”), but without the large capital investment that AMI rollouts typically entail. In particular, a central objective of the Smart Energy Pilot was to enable residential dynamic pricing (time-of-use “TOU” and critical peak rates and rebates) and two-way direct load control (“DLC”) by continually capturing AMR meter data transmissions and communicating through customer-sited broadband connections in conjunction with a standards-based home area network (“HAN”). The pilot was supported by the U.S. Department of Energy’s (“DOE”) through the Smart Grid Demonstration program. NSTAR was very pleased to not only receive the funding support from DOE, but the guidance and support of the DOE throughout the pilot. NSTAR is also pleased to report to the DOE that it was able to execute and deliver a successful pilot on time and on budget. NSTAR looks for future opportunities to work with the DOE and others in future smart grid projects.

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DOE OSTI2023

Distributed Software-Defined Network Architecture for Smart Grid Resilience to Denial-of-Service Attacks

An important challenge for smart grid security is designing a secure and robust smart grid communications architecture to protect against cyber-threats, such as Denial-of-Service (DoS) attacks, that can adversely impact the operation of the power grid. Researchers have proposed using Software Defined Network frameworks to enhance cybersecurity of the smart grid, but there is a lack of benchmarking and comparative analyses among the many techniques. In this work, a distributed three-controller software-defined networking (D3-SDN) architecture, benchmarking, and comparative analysis with other techniques is presented. The selected distributed flat SDN architecture divides the network horizontally into multiple areas or clusters, where each cluster is handled by a single Open Network Operating System (ONOS) controller. A case study using the IEEE 118-bus system is provided to compare the performance of the presented ONOS-managed D3-SDN, against the POX controller. In addition, the proposed architecture outperforms a single SDN controller framework by a tenfold increase in throughput; a reduction in latency of > 20%; and an increase in throughput of approximately 11% during the DoS attack scenarios.

Agnew Jr., Dennis↗
DOE OSTI2012

Cyber-Physical System Security of Smart Grids

Abstract—This panel presentation will provide perspectives of cyber-physical system security of smart grids. As smart grid technologies are deployed, the interconnected nature of these systems is becoming more prevalent and more complex, and the cyber component of this cyber-physical system is increasing in importance. Studying system behavior in the face of failures (e.g., cyber attacks) allows a characterization of the systems’ response to failure scenarios, loss of communications, and other changes in system environment (such as the need for emergent updates and rapid reconfiguration). The impact of such failures on the availability of the system can be assessed and mitigation strategies considered. Scenarios associated with confidentiality, integrity, and availability are considered. The cyber security implications associated with the American Recovery and Reinvestment Act of 2009 in the United States are discussed.

Dagle, Jeffery E.↗
DOE OSTI2020

Designing a decentralized fault-tolerant software framework for smart grids and its applications

The vision of the ‘Smart Grid’ anticipates a distributed real-time embedded system that implements various monitoring and control functions. As the reliability of the power grid is critical to modern society, the software supporting the grid must support fault tolerance and resilience of the resulting cyber-physical system. This paper describes the fault-tolerance features of a software framework called Resilient Information Architecture Platform for Smart Grid (RIAPS). The framework supports various mechanisms for fault detection and mitigation and works in concert with the applications that implement the grid-specific functions. The paper discusses the design philosophy for and the implementation of the fault tolerance features and presents an application example to show how it can be used to build highly resilient systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Data distribution service-based interoperability framework for smart grid testbed infrastructure

This study presents the design and implementation of a communication and control infrastructure for smart grid operation. The proposed infrastructure enhances the reliability of the measurements and control network. The advantages of utilizing the data-centric over message-centric communication approach are discussed in the context of smart grid applications. The data distribution service (DDS) is used to implement a data-centric common data bus for the smart grid. This common data bus improves the communication reliability, enabling distributed control and smart load management. These enhancements are achieved by avoiding a single point of failure while enabling peer-to-peer communication and an automatic discovery feature for dynamic participating nodes. The infrastructure and ideas presented in this paper were implemented and tested on the smart grid testbed. A toolbox and application programing interface for the testbed infrastructure are developed in order to facilitate interoperability and remote access to the testbed. This interface allows control, monitoring, and performing of experiments remotely. Furthermore, it could be used to integrate multidisciplinary testbeds to study complex cyber-physical systems (CPS).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Recent Development of Frequency Estimation Methods for Future Smart Grid

The frequency estimated by the Phasor Measurement Unit (PMU) is a critical index of power system status and supports many smart grid applications. The future smart grid features high penetration of renewables and more fast-moving power electronics inverters but raises challenges to the reliable frequency estimation. This article presents three methods to address these challenges. First, an enhanced zero-crossing algorithm was developed to track the fast-changing frequency in system dynamics. Second, we propose a technology that can tolerate the system transient and suppress the outliers. Third, an algorithm was developed to export high time-resolution frequency estimations with minimum computational effort. All of the proposed methods are realized in hardware and compared with classical frequency estimation methods. The testing results indicate that the proposed methods have excellent performance. They can be used in future PMUs and provide reliable and high time resolution data for smart grid applications.

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DOE OSTI2012

High-Performance Computing for Advanced Smart Grid Applications

The power grid is becoming far more complex as a result of the grid evolution meeting an information revolution. Due to the penetration of smart grid technologies, the grid is evolving as an unprecedented speed and the information infrastructure is fundamentally improved with a large number of smart meters and sensors that produce several orders of magnitude larger amounts of data. How to pull data in, perform analysis, and put information out in a real-time manner is a fundamental challenge in smart grid operation and planning. The future power grid requires high performance computing to be one of the foundational technologies in developing the algorithms and tools for the significantly increased complexity. New techniques and computational capabilities are required to meet the demands for higher reliability and better asset utilization, including advanced algorithms and computing hardware for large-scale modeling, simulation, and analysis. This chapter summarizes the computational challenges in smart grid and the need for high performance computing, and present examples of how high performance computing might be used for future smart grid operation and planning.

computational challenges↗
DOE OSTI2016

A Literature Review: Smart Grids Impacts on Nuclear Power Plants Task 4: Project Final Report

This report describes the results of a literature review performed to study the current state of electric power industry efforts and research work regarding Smart Grid technologies, renewable energy integration, grid reliability standards, and USNRC electric grid regulations and guidance. The information gathered in the literature review is intended to: (1) Develop a better understanding of the impacts that Smart Grid implementation and the integration of renewable energy sources can have on the availability and reliability of the electric grid as a source of offsite power, (2) Provide an understand of the present grid reliability standards and how they will address the challenges of Smart Grid implementation, (3) Identify electrical system vulnerabilities and failure modes that may result from the implementation of Smart Grid technologies and cybersecurity threats, (4) Provide an understand of the actions being taken by FERC, NERC and others to identify, understand and address potential impacts, (5) Provide an understand of existing NRC regulation and guidance addressing requirements of grid design, operation and reliability supporting NPP design requirements, and (6) Recommend any additional actions or studies that should be undertaken by the NRC to ensure compliance of NPPs to GDC 17 and any other applicable regulations and guidance as the electric grid evolves into the Smart Grid.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Resilient Information Architecture Platform for Smart Grid (RIAPS)

A number of emerging trends will substantially alter the operation and control of the electric grid over the next several decades. These trends include ensuring resiliency under severe weather events, increasing integration of renewable electricity generation, supporting changing electricity demand patterns, and the improving cost effectiveness of distributed energy resources. To address these challenges, the future “Smart Grid” management will need to transition from centralized to coordinated distributed control paradigm. Reliable operation of the Smart Grid depends on distributed intelligence realized through software applications that run on distributed computing devices attached to the power system to collect data and collaboratively manage resources. However, much of the existing software for Smart Grid-enabled devices is either proprietary or developed with custom solutions, which limits interoperability among the heterogeneous devices and hinders the ability to manage system-level reliability, security, and resiliency requirements. Additionally, this approach makes Smart Grid applications hard to maintain, evolve, verify, and replace; resulting in high development and deployment costs. Further development of the Smart Grid requires a reusable software base-layer to move from hard-coded functionality to a plug-and-play architecture capable of managing system-level objectives and constraints in addition to providing consistent common services across heterogeneous devices and applications. Vanderbilt University, in collaboration with North Carolina State University and Washington State University has developed a foundation ‘software platform’ for developing and deploying robust, reliable, effective and secure software applications for the Smart Grid. The Resilient Information Architecture Platform for the Smart Grid (RIAPS) provides core services for building effective and powerful smart grid applications. It offers unique services for real-time data dissemination, fault tolerance, and coordination across apps distributed over the network.

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