Results for “smart grid security” — Page 7

DOE OSTI2020

Chapter Nine - Automated Optimal Control in Energy Systems: The Reinforcement Learning Approach

With the development of smart grid technologies an increasing number of new devices and participants have joined modern energy systems and are inevitably making them more complicated and interdependent than ever. Optimally controlling such a complex energy system and maintaining its operation in a high-efficient, secure, and resilient manner are challenging tasks to the system operators. Fortunately, the revolution in deep learning and artificial intelligence (AI), both from hardware and algorithms perspectives, has provided new ideas and solutions to many previously intractable problems. As a result, this advance in computer science also sparked great research interests in utilizing AI in solving engineering problems related to the modern energy systems. Among many AI techniques, deep reinforcement learning (DRL) has demonstrated great potential for solving sequential optimization problems, which are very common in the engineering domains. Its ability to handle nonlinearity and stochasticity in controlled systems has out-competed many traditional optimal control algorithms. Therefore in this chapter, we focus on the state-of-the-art of DRL concepts and related algorithms, compare their pros and cons with traditional optimal control approaches and discuss the typical workflow for leveraging RL in solving complex problems in modern energy systems.

artificial intelligence↗

DOE OSTI2020

An intelligent energy router for managing behind-the-meter resources and assets

With increase in distributed energy resources (DERs) and smart loads, each energy resource and load need a separate power conversion system leading to complex coordination and interaction, reduced energy conversion efficiency, coordinating compliance to grid standards (IEEE 1547) from multiple sources, reduced security. Also, multiple vendors with legacy system designs and proprietary communications interfaces result in redundancy and increase in cost of power electronics systems. This paper presents an energy router concept for buildings applications which provides autonomous power flow between sources and loads with a novel agent-based software interface.

Chinthavali, Madhu Sudhan↗

DOE OSTI2022

Systems and methods for authentication and key agreement in a smart grid

Systems and methods for authentication and key agreement are provided and can utilize a scheme that uses dynamic key generation to achieve replay-attack resistance in zero round trip time (0-RTT). The hash-chain concept can be integrated with the Diffie-Hellman (DH) key exchange scheme. With this scheme, a device can securely determine the new shared key immediately (i.e., in 0-RTT) and start using it.

Akkaya, Kemal↗

DOE OSTI2020

Autonomous Tools for Attack Surface Reduction

The electric power grid is a complex critical infrastructure that forms the lifeline of modern society, and its secure and reliable operation is of paramount importance to national security and economic well being. However, recent findings documented in authoritative sources indicate the threat of cyber-based attacks growing in numbers and sophistication. However, securing the grid against stealthy cyber attacks is a challenging task due to legacy nature of the infrastructure coupled with dynamic nature of threat landscape and ever growing sophistication of the adversaries. Additionally, the grid’s attack surface continues to grow with the increased dependence on digital communications and control that now extends to each consumer through smart meters and distributed energy resources. Unfortunately, this expansive surface increases the grid’s vulnerability and further exposes critical control systems in both substations and control centers. To respond to this emerging need, we had successfully assembled an interdisciplinary team with academic- industry partnership to successfully conduct research, development, evaluation, demonstration, and commercialization of attack surface reduction tools, whose goal is to significantly reduce the cyber attack surface in the North American power grid. Our proposed project was a synergistic collaborative effort leveraging the synergistic expertise of the team members across power systems, cyber security and CPS security, testbeds, field deployments and demonstration, and successful commercialization. The team consisted of leading experts from two major universities – Iowa State University, Washington State University – complemented by reputed researchers from two DOE national laboratories – Pacific Northwest National Lab, and Argonne National Lab, one major utility vendor GE Global Research, and one utility partner – Cedar Falls Utilities (CFU). The team members have proven track record of successful academic-industry collaboration in interdisciplinary R&D projects, and bring onboard some of the best state-of-the-art testbed resources, industry-grade SCADA/EMS/DMS environment for experimentation and field demonstration.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Autonomous Tools for Attack Surface Reduction (Final Report)

The electric power grid is a complex critical infrastructure that forms the lifeline of modern society, and its secure and reliable operation is of paramount importance to national security and economic wellbeing. However, recent findings documented in authoritative sources indicate the threat of cyber-based attacks growing in numbers and sophistication. However, securing the grid against stealthy cyberattacks is a challenging task due to legacy nature of the infrastructure coupled with dynamic nature of threat landscape and ever-growing sophistication of the adversaries. Additionally, the grid’s attack surface continues to grow with the increased dependence on digital communications and control that now extends to each consumer through smart meters and distributed energy resources. Unfortunately, this expansive surface increases the grid’s vulnerability and further exposes critical control systems in both substations and control centers. To respond to this emerging need, we had successfully assembled an interdisciplinary team with academic- industry partnership to successfully conduct research, development, evaluation, demonstration, and commercialization of attack surface reduction tools, whose goal was to significantly reduce the cyber attack surface in the North American power grid. Our proposed project was a synergistic collaborative effort leveraging the synergistic expertise of the team members across power systems, cyber security and CPS security, testbeds, field deployments and demonstration, and successful commercialization. The following are the specific tasks that have been successfully completed two phases (2016-2020). Phase I: Task 1: Developed and implemented a robust Project Management and Data Management Plan, coupled with a well thought out Risk Mitigation Plan. Task 2.1: Developed a comprehensive framework that continually assesses and autonomously reduces the attack surface for the power grid control environment spanning across substations, control center and the SCADA network to significantly reduce the risks of cyber attacks. Task 2.2: Developed attack surface analysis techniques, metrics, and tools that assess the attack surface at multiple levels including the control center, substations, and the SCADA network. Task 2.3: Developed attack surface reduction techniques and tools that dynamically reduce attack surface and hence increase attacker’s cost without interfering in the critical functions of the system. Task 2.4: Prototyped, implemented, and quantitatively evaluated/validated the techniques and tools on a realistic industrial CPS security testbed environment by leveraging the unique resources of the team. Task 3: Developed Commercialization plan to transition the developed tools into power system industry stakeholders for a broader adoption by leveraging the expertise of our industrial members. Phase II: Task 4: Successfully completed field demonstration, verification, and evaluation of the effectiveness of the attack surface analysis and reduction techniques on a realistic utility testbed environment. This also involved the development of realistic scenarios, sound metrics, data sets, evaluation criteria, and documentation. Technology integration & Field demonstration: The project had significantly advanced the state-of-the-art research and practice in improving the cybersecurity of our nation’s power grid infrastructure against cyber threats. In particular, the proposed, designed, and deployed attack surface analysis and reduction algorithms and tools have contributed to significantly reducing the exposure and risk of the devices, substations, and the integrated SCADA/EMS/ DMS grid environment to cyber threat. Strong demonstration and evaluation techniques have verified the feasibility of the developed techniques on realistic cyber-physical testbeds and utility partner's real grid environment, and collaborative research and evaluation of attack surface reduction techniques (for wide-are monitoring and control) within a vendor (GE) EMS platform. The Attack Host Analyzer (AHA) tool that was developed through this project was made available through GitHub.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Smart Grid Cyber-Physical Attack and Defense: A Review

Not Available

42 ENGINEERING↗

DOE OSTI2022

A Survey of Cyber-Physical Power System Modeling Methods for Future Energy Systems

Not Available

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Cybersecurity for the Operational Technology Environment (CyOTE) (Final Technical Report)

Electric grids have historically been susceptible to both physical attacks and environmental hazards but the implementation of smart grids, remote management, and self-healing networks, has now made the grid vulnerable to cyber attacks. To address risks introduced by routable connectivity, utilities must establish dynamic solutions to identify, protect, detect, respond to, and recover from cyber security threats and vulnerabilities. In response to the evolving threat landscape U.S. Department of Energy-Office of Cybersecurity, Energy Security, and Emergency Response (DOE CESER) initiated the Cybersecurity for the OT Environment (CyOTE) pilot program, a U.S. Department of Energy (DOE) effort designed to leverage U.S. intelligence capabilities to prevent, detect, or mitigate a cyber attack on utility operational technology (OT) networks. As part of the CyOTE pilot, The Southern Company (Southern Company or Southern) researched, evaluated and deployed emerging Commercial off the Shelf (COTS) technologies and cyber security monitoring architectures to provide previously unrealized network visibility and situational awareness through deep packet inspection and data analytics. This Final Scientific/Technical Report documents the objectives, methodology, lessons learned, and results of Southern Company’s participation in the CyOTE pilot from December 2018 to September 2023.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Incentivizing Distributed Energy Resource Participation in Grid Services

The bulk power system is experiencing a dramatic shift as renewable generation growth continues to accelerate. Large-scale renewables adoption will help societies transition to a low-carbon, low-cost, and environmentally friendly electrical power system. However, the transition from a paradigm of generation following load to one where load follows generation will require large-scale interconnection and coordinated operation of Distributed Energy Resources (DERs), supported by open communication protocols. In this future grid scenario, DER aggregations will provide critical grid services that enable high penetration levels of renewable generation. This position paper presents an Energy Service Interface (ESI) that defines scope for ensuring secure, trustworthy information exchange between grid service providers and DERs. The goal of the ESI is to encourage large-scale participation of DERs in order to provide grid services through dispatch of DER aggregations. This position paper also presents an open smart energy communications protocol that allows DERs to advertise their characteristics and participate in grid services, within constraints established by the ESI. The paper presents several monetization incentives that grid service providers could use to encourage large-scale DER participation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2019

Blockchain Smart Contracts for Transactive Energy Systems

This report demonstrates the impact of blockchain technology underlying a transactive energy system and articulates details and principle components of each of five stages in a transactive energy system. This report depicts the engineering requirements of a sample market system, blockchain features, and the relationship between those requirements and features (Section 2.2). Clear value propositions of blockchain features for transactive energy systems are: identity management, security of data, resiliency, decentralization and smart contract trustworthiness, performance, integrity in a trustless environment and access control. Due to the immutability afforded by blockchain architecture, increased data fidelity could potentially help detect targeted cyber-attacks and increase resiliency of grid integration. A distributed system can be more fault tolerant and enable transactive energy by supporting machine-to-machine transactions that can be integrated directly into complex grid operations without the need of trust in a third party. Energy auctions, and potentially registration processes, can be carried out according to transparent rules implemented as smart contracts (Section 4.0). In this current experiment, we ran a use-case/table-top exercise that imitated a real-time 5-min double auction market. The objective of this demonstration is to investigate the applicability of blockchain with transactive energy systems (Section 3.0).

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2011

Smart Grid Development Issues for Terrestrial and Space Applications

The development of the so called Smart Grid has as many definitions as individuals working in the area. Based on the technology or technologies that are of interest, be it high speed communication, renewable generation, smart meters, energy storage, advanced sensors, etc. they can become the individual defining characteristic of the Smart Grid. In reality the smart grid encompasses all of these items and quite at bit more. This discussion attempts to look at what the needs are for the grid of the future, such as the issues of increased power flow capability, use of renewable energy, increased security and efficiency and common power and data standards. It also shows how many of these issues are common with the needs of NASA for future exploration programs. A common theme to address both terrestrial and space exploration issues is to develop micro-grids that advertise the ability to enable the load leveling of large power generation facilities. However, for microgrids to realize their promise there needs to a holistic systems approach to their development and integration. The overall system integration issues are presented along with potential solution methodologies.

Soeder, James F.↗

NASA NTRS2014

Smart Grid Development Issues for Terrestrial and Space Applications

The development of the so called Smart Grid has as many definitions as individuals working in the area. Based on the technology or technologies that are of interest, be it high speed communication, renewable generation, smart meters, energy storage, advanced sensors, etc. they can become the individual defining characteristic of the Smart Grid. In reality the smart grid encompasses all of these items and quite at bit more. This discussion attempts to look at what the needs are for the grid of the future, such as the issues of increased power flow capability, use of renewable energy, increased security and efficiency and common power and data standards. It also shows how many of these issues are common with the needs of NASA for future exploration programs. A common theme to address both terrestrial and space exploration issues is to develop micro-grids that advertise the ability to enable the load leveling of large power generation facilities. However, for microgrids to realize their promise there needs to a holistic systems approach to their development and integration. The overall system integration issues are presented along with potential solution methodologies.

Power Systems↗

DOE OSTI2020

Data-Centric Communication Framework for Multicast IEC 61850 Routable GOOSE Messages over the WAN in Modern Power Systems

In this paper, a data-centric communication framework is proposed for multicast routable generic object-oriented substation event (GOOSE) messages (MRGM) over the wide area network (WAN) for effective substation-to-substation (SS2SS) and substation to control center (SS2CC) communications. In this structure, the IEC 61850 GOOSE message is transmitted over the WAN using the data distribution service (DDS) as a fast, reliable, and secure data-centric communication middleware. The main feature of this framework is its multicast capability, where several authorized subscribers can receive a published message simultaneously. This can significantly improve the system monitoring and control of the protection systems in modern smart grids, where intelligent schemes can be applied. The effectiveness of the proposed platform, in terms of total end-to-end delay between participants, is evaluated through experimental results obtained from the actual hardware-based test setup developed at the Florida International University (FIU) smart grid testbed. The results demonstrate that the latency between sending and receiving a GOOSE message among participants is within its maximum time span defined by the IEC 61850-90-5 working group for communications over the WAN.

42 ENGINEERING↗

DOE OSTI2020

Modeling and Detection of Future Cyber-Enabled DSM Data Attacks

Demand-Side Management (DSM) is an essential tool to ensure power system reliability and stability. In future smart grids, certain portions of a customer’s load usage could be under the automatic control of a cyber-enabled DSM program, which selectively schedules loads as a function of electricity prices to improve power balance and grid stability. In this scenario, the security of DSM cyberinfrastructure will be critical as advanced metering infrastructure and communication systems are susceptible to cyber-attacks. Such attacks, in the form of false data injections, can manipulate customer load profiles and cause metering chaos and energy losses in the grid. The feedback mechanism between load management on the consumer side and dynamic price schemes employed by independent system operators can further exacerbate attacks. To study how this feedback mechanism may worsen attacks in future cyber-enabled DSM programs, we propose a novel mathematical framework for (i) modeling the nonlinear relationship between load management and real-time pricing, (ii) simulating residential load data and prices, (iii) creating cyber-attacks, and (iv) detecting said attacks. In this framework, we first develop time-series forecasts to model load demand and use them as inputs to an elasticity model for the price-demand relationship in the DSM loop. This work then investigates the behavior of such a feedback loop under intentional cyber-attacks. We simulate and examine load-price data under different DSM-participation levels with three types of random additive attacks: ramp, sudden, and point attacks. We conduct two investigations for the detection of DSM attacks. The first studies a supervised learning approach, with various classification models, and the second studies the performance of parametric and nonparametric change point detectors. Results conclude that higher amounts of DSM participation can exacerbate ramp and sudden attacks leading to better detection of such attacks, especially with supervised learning classifiers. We also find that nonparametric detection outperforms parametric for smaller user pools, and random point attacks are the hardest to detect with any method.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Cyber–Physical System Security of Distribution Systems

The Information and Communications Technology (ICT) for control and monitoring of power systems is a layer on top of the physical power system infrastructure. The cyber system and physical power system components form a tightly coupled Cyber–Physical System (CPS). Sources of vulnerabilities arise from the computing and communication systems of the cyber–power grid. Cyber intrusions targeting the power grid are serious threats to the reliability of electricity supply that is critical to society and the economy. In a typical Information Technology environment, numerous attack scenarios have shown how unauthorized users can access and manipulate protected information from a network domain. The need for cyber security has led to industry standards that power grids must meet to ensure that the monitoring, operation, and control functions are not disrupted by cyber intrusions. Cyber security technologies such as encryption and authentication have been deployed on the CPS. Intrusion or anomaly detection and mitigation tools developed for power grids are emerging. Furthermore, this survey paper provides the basic concepts of cyber vulnerabilities of distribution systems and CPS security. The important ICT subjects for distribution systems covered in this paper include Supervisory Control And Data Acquisition, Distributed Energy Resources, including renewable energy and smart meters.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Achieving Cyber-Resilience for Power Systems using a Learning, Model-Assisted Blockchain Framework

The secure integration and management of distributed energy resources (DER) and power aggregators in the electric grid requires secure communications and a physics-aware Command and Control (C2) strategy. A Blockchain (BC)-based overlay network was developed to provide a security layer for the existing power grid network that mitigates risks in current and legacy network and C2 protocols. By integrating a Model-Assisted Machine Learning (MAML) framework with a Secure Blockchain Overlay Network (SBON) a defense-in-depth strategy was achieved. In our approach, the MAML framework leveraged a smart contract framework to gather network data and learn the dynamics of DER to develop detection strategies for attacks targeting sensors and actuators used by DER. The MAML framework learned dynamical systems models for individual DERs to detect sensor attacks. For DER we utilized a Digital Twin (DT) to accelerate the learning process for a model resistant to stealthy attacks. The project created DT for PV inverters and BESS. The DTs were coupled with a model-assisted, data-driven learning of DER behavior. Specifically, we evaluated architectures for model-based learning with model-free fine-tuning. Additionally, differential privacy techniques were used to obfuscate data, while still allowing the computation of attack detection results based on obfuscated data. The SBON developed leverages a private permissioned blockchain network orchestrated with the Hyperledger Fabric framework. To connect the cyber world, which orchestrates the blockchain fabric, and the physical world where the power network resides, we developed a system implementation to enable the secure interaction of the physical world and the abstracted blockchain.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Blockchain-Based Smart Contracts Use for Photovoltaic Energy Trade Transactions

In recent decades, interest in renewable energy via solar energy has increased, especially in California and Nevada. In a region that can produce enough solar power for self-use, prosumers must use or sell surplus energy. Solar energy self-consumption is essential in modern energy transactions in the grid. This paper proposes an approach towards grid services that includes photovoltaic hardware to store the excess energy in battery storage. Such energy can then be sold to power companies while the transaction is handled using blockchain. Software, security architecture and data flow requirements based on the Ethereum Blockchain are included. Furthermore, this solution protects the private information of seller and buyer and secures transactions.

14 SOLAR ENERGY↗

DOE OSTI2020

Detection of DoS Attacks Using ARFIMA Modeling of GOOSE Communication in IEC 61850 Substations

Integration of Information and Communication Technology (ICT) in modern smart grids (SGs) offers many advantages including the use of renewables and an effective way to protect, control and monitor the energy transmission and distribution. To reach an optimal operation of future energy systems, availability, integrity and confidentiality of data should be guaranteed. Research on the cyber-physical security of electrical substations based on IEC 61850 is still at an early stage. In the present work, we first model the network traffic data in electrical substations, then, we present a statistical Anomaly Detection (AD) method to detect Denial of Service (DoS) attacks against the Generic Object Oriented Substation Event (GOOSE) network communication. According to interpretations on the self-similarity and the Long-Range Dependency (LRD) of the data, an Auto-Regressive Fractionally Integrated Moving Average (ARFIMA) model was shown to describe well the GOOSE communication in the substation process network. Based on this ARFIMA-model and in view of cyber-physical security, an effective model-based AD method is developed and analyzed. Two variants of the statistical AD considering statistical hypothesis testing based on the Generalized Likelihood Ratio Test (GLRT) and the cumulative sum (CUSUM) are presented to detect flooding attacks that might affect the availability of the data. Our work presents a novel AD method, with two different variants, tailored to the specific features of the GOOSE traffic in IEC 61850 substations. The statistical AD is capable of detecting anomalies at unknown change times under the realistic assumption of unknown model parameters. The performance of both variants of the AD method is validated and assessed using data collected from a simulation case study. We perform several Monte-Carlo simulations under different noise variances. The detection delay is provided for each detector and it represents the number of discrete time samples after which an anomaly is detected. In fact, our statistical AD method with both variants (CUSUM and GLRT) has around half the false positive rate and a smaller detection delay when compared with two of the closest works found in the literature. Our AD approach based on the GLRT detector has the smallest false positive rate among all considered approaches. Whereas, our AD approach based on the CUSUM test has the lowest false negative rate thus the best detection rate. Depending on the requirements as well as the costs of false alarms or missed anomalies, both variants of our statistical detection method can be used and are further analyzed using composite detection metrics.

IEC 61850 electrical substations↗