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A Simple and Accurate Energy-Detector-Based Transient Waveform Detection for Smart Grids: Real-World Field Data Performance
Integration of distributed energy sources, advanced meshed operation, sensors, automation, and communication networks all contribute to autonomous operations and decision-making processes utilized in the grid. Therefore, smart grid systems require sophisticated supporting structures. Furthermore, rapid detection and identification of disturbances and transients are a necessary first step towards situationally aware smart grid systems. This way, high-level monitoring is achieved and the entire system kept operational. Even though smart grid systems are unavoidably sophisticated, low-complexity algorithms need to be developed for real-time sensing on the edge and online applications to alert stakeholders in the event of an anomaly. In this study, the simplest form of anomaly detection mechanism in the absence of any a priori knowledge, namely, the energy detector (also known as radiometer in the field of wireless communications and signal processing), is investigated as a triggering mechanism, which may include automated alerts and notifications for grid anomalies. In contrast to the mainstream literature, it does not rely on transform domain tools; therefore, utmost design and implementation simplicity are attained. Performance results of the proposed energy detector algorithm are validated by real power system data obtained from the DOE/EPRI National Database of power system events and the Grid Signature Library.
Model-driven Privacy Assessment in the Smart Grid
In a smart grid, data and information are transported, transmitted, stored, and processed with various stakeholders having to cooperate effectively. Furthermore, personal data is the key to many smart grid applications and therefore privacy impacts have to be taken into account. For an effective smart grid, well integrated solutions are crucial and for achieving a high degree of customer acceptance, privacy should already be considered at design time of the system. To assist system engineers in early design phase, frameworks for the automated privacy evaluation of use cases are important. For evaluation, use cases for services and software architectures need to be formally captured in a standardized and commonly understood manner. In order to ensure this common understanding for all kinds of stakeholders, reference models have recently been developed. In this paper we present a model-driven approach for the automated assessment of such services and software architectures in the smart grid that builds on the standardized reference models. The focus of qualitative and quantitative evaluation is on privacy. For evaluation, the framework draws on use cases from the University of Southern California microgrid.
A Game-Theoretic Approach to Modeling Attacks and Defenses of Smart Grids at Three Levels
As optimization, user capabilities, and data-taking abilities are incorporated into next-generation power grids, or smart grids, they face cyber threats. The traditional electrical grid could only be damaged by physical attacks; however thesmart grid can suffer remote/cyber attacks, which have not been studied extensively in the literature. The electrical grid forms the backbone of the modern society and its security has significant implications in military settings. This paper applies game theory to model three-levels (power plants, transmission, and distribution networks) of defenses and attacks in smart grid network security. We characterize both the attacker and the defender (who interact at three network levels: distribution, transmission, and power plants) best responses and equilibrium strategies. We find that the defender's best response is not only a function of direct attacks but also of the spread from connected networks. Sensitivity analyses of the equilibrium strategies show that when success probability of an attack against power plantsreaches a threshold, the defender increases defending efforts for power plants. In contrast, the attack eort at all levels is not affected by this probability. This paper provides some novel insights to modeling and analyzing the emerging threats to the growing smart grid networks.
Artificial Intelligence Techniques in Smart Grid: A Survey
The smart grid is enabling the collection of massive amounts of high-dimensional and multi-type data about the electric power grid operations, by integrating advanced metering infrastructure, control technologies, and communication technologies. However, the traditional modeling, optimization, and control technologies have many limitations in processing the data; thus, the applications of artificial intelligence (AI) techniques in the smart grid are becoming more apparent. This survey presents a structured review of the existing research into some common AI techniques applied to load forecasting, power grid stability assessment, faults detection, and security problems in the smart grid and power systems. It also provides further research challenges for applying AI technologies to realize truly smart grid systems. Finally, this survey presents opportunities of applying AI to smart grid problems. The paper concludes that the applications of AI techniques can enhance and improve the reliability and resilience of smart grid systems.
A Survey on Cybersecurity Challenges, Detection, and Mitigation Techniques for the Smart Grid
The world is transitioning from the conventional grid to the smart grid at a rapid pace. Innovation always comes with some flaws; such is the case with a smart grid. One of the major challenges in the smart grid is to protect it from potential cyberattacks. There are millions of sensors continuously sending and receiving data packets over the network, so managing such a gigantic network is the biggest challenge. Any cyberattack can damage the key elements, confidentiality, integrity, and availability of the smart grid. The overall smart grid network is comprised of customers accessing the network, communication network of the smart devices and sensors, and the people managing the network (decision makers); all three of these levels are vulnerable to cyberattacks. In this survey, we explore various threats and vulnerabilities that can affect the key elements of cybersecurity in the smart grid network and then present the security measures to avert those threats and vulnerabilities at three different levels. In addition to that, we suggest techniques to minimize the chances of cyberattack at all three levels.
Multi-Agent Based Attack-Resilient System Integrity Protection for Smart Grid
Not provided.
Greening the Grid - Advancing Solar, Wind, and Smart Grid Technologies (Spanish Version)
This is the Spanish version of 'Greening the Grid - Advancing Solar, Wind, and Smart Grid Technologies'. Greening the Grid provides technical assistance to energy system planners, regulators, and grid operators to overcome challenges associated with integrating variable renewable energy into the grid.
Benefits Analysis of Smart Grid Projects. White paper, 2014-2016
Smart grids are rolling out internationally, with the United States (U.S.) nearing completion of a significant USD4-plus-billion federal program funded under the American Recovery and Reinvestment Act (ARRA-2009). The emergence of smart grids is widespread across developed countries. Multiple approaches to analyzing the benefits of smart grids have emerged. The goals of this white paper are to review these approaches and analyze examples of each to highlight their differences, advantages, and disadvantages. This work was conducted under the auspices of a joint U.S.-China research effort, the Climate Change Working Group (CCWG) Implementation Plan, Smart Grid. We present comparative benefits assessments (BAs) of smart grid demonstrations in the U.S. and China along with a BA of a pilot project in Europe. In the U.S., we assess projects at two sites: (1) the University of California, Irvine campus (UCI), which consists of two distinct demonstrations: Southern California Edison’s (SCE) Irvine Smart Grid Demonstration Project (ISGD) and the UCI campus itself; and (2) the Navy Yard (TNY) area in Philadelphia, which has been repurposed as a mixed commercial-industrial, and possibly residential, development. In China, we cover several smart-grid aspects of the Sino-Singapore Tianjin Eco-city (TEC) and the Shenzhen Bay Technology and Ecology City (B-TEC). In Europe, we look at a BA of a pilot smart grid project in the Malagrotta area west of Rome, Italy, contributed by the Joint Research Centre (JRC) of the European Commission. The Irvine sub-project BAs use the U.S. Department of Energy (U.S. DOE) Smart Grid Computational Tool (SGCT), which is built on methods developed by the Electric Power Research Institute (EPRI). The TEC sub-project BAs apply Smart Grid Multi-Criteria Analysis (SG-MCA) developed by the State Grid Corporation of China (SGCC) based on the analytic hierarchy process (AHP) with fuzzy logic. The B-TEC and TNY sub-project BAs are evaluated using new approaches developed by those project teams. JRC has adopted an approach similar to EPRI’s but tailored to the Malagrotta distribution grid.
SDN-enabled recovery for Smart Grid teleprotection applications in post-disaster scenarios
Not provided.
OPNET/Simulink Based Testbed for Disturbance Detection in the Smart Grid
The important backbone of the smart grid is the cyber/information infrastructure, which is primarily used to communicate with different grid components. A smart grid is a complex cyber physical system containing a numerous and variety number of sources, devices, controllers and loads. Therefore, the smart grid is vulnerable to grid related disturbances. For such dynamic system, disturbance and intrusion detection is a paramount issue. This paper presents a Simulink and Opnet based co-simulated platform to carry out a cyber-intrusion in cyber network for modern power systems and the smart grid. The IEEE 30 bus power system model is used to demonstrate the effectiveness of the simulated testbed. The experiments were performed by disturbing the circuit breakers reclosing time through a cyber-attack. Different disturbance situations in the considered test system are considered and the results indicate the effectiveness of the proposed co-simulated scheme.
Scalable Real Time Data Management for Smart Grid
This paper presents GridMW, a scalable and reliable data middleware for smart grids. Smart grids promise to improve the efficiency of power grid systems and reduce green house emissions through incorporating power generation from renewable sources and shaping demand to match the supply. As a result, power grid systems will become much more dynamic and require constant adjustments, which requires analysis and decision making applications to improve the efficiency and reliability of smart grid systems.
NREL Smart Grid Projects
Although implementing Smart Grid projects at the distribution level provides many advantages and opportunities for advanced operation and control, a number of significant challenges must be overcome to maintain the high level of safety and reliability that the modern grid must provide. For example, while distributed generation (DG) promises to provide opportunities to increase reliability and efficiency and may provide grid support services such as volt/var control, the presence of DG can impact distribution operation and protection schemes. Additionally, the intermittent nature of many DG energy sources such as photovoltaics (PV) can present a number of challenges to voltage regulation, etc. This presentation provides an overview a number of Smart Grid projects being performed by the National Renewable Energy Laboratory (NREL) along with utility, industry, and academic partners. These projects include modeling and analysis of high penetration PV scenarios (with and without energy storage), development and testing of interconnection and microgrid equipment, as well as the development and implementation of advanced instrumentation and data acquisition used to analyze the impacts of intermittent renewable resources. Additionally, standards development associated with DG interconnection and analysis as well as Smart Grid interoperability will be discussed.
A Framework for Counterfeit Smart Grid Device Detection
The core vision of the smart grid concept is the realization of reliable two-way communications between smart devices (e.g., IEDs, PLCs, PMUs). The benefits of the smart grid also come with tremendous security risks and new challenges in protecting the smart grid systems from cyber threats. Particularly, the use of untrusted counterfeit smart grid devices represents a real problem. Consequences of propagating false or malicious data, as well as stealing valuable user or smart grid state information from counterfeit devices are costly. Hence, early detection of counterfeit devices is critical for protecting smart grid’s components and users. To address these concerns, in this poster, we introduce our initial design of a configurable framework that utilize system call tracing, library interposition, and statistical techniques for monitoring and detection of counterfeit smart grid devices. In our framework, we consider six different counterfeit device scenarios with different smart grid devices and adversarial seZings. Our initial results on a realistic testbed utilizing actual smart-grid GOOSE messages with IEC-61850 communication protocol are very promising. Our framework is showing excellent rates on detection of smart grid counterfeit devices from impostors.
Design and Evaluation of SunSpec-Compliant Smart Grid Controller with an Automated Hardware-in-the-Loop Testbed.
Abstract not provided.
Smart Grid Status and Metrics Report Appendices
A smart grid uses digital power control and communication technology to improve the reliability, security, flexibility, and efficiency of the electric system, from large generation through the delivery systems to electricity consumers and a growing number of distributed generation and storage resources. 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. The Smart Grid Status and Metrics Report defines and examines 21 metrics that collectively provide insight into the grid’s capacity to embody these characteristics. This appendix presents papers covering each of the 21 metrics identified in Section 2.1 of the Smart Grid Status and Metrics Report. These metric papers were prepared in advance of the main body of the report and collectively form its informational backbone.