SmartGridComm will include 5 tutorials.
All the tutorials will be delivered virtually on Monday, 25 October 2021.
9:00-11:00 CET
TUT-01: A Unified Control Framework for Real-Time Power System Operation
11:00-13:00 CET
TUT-02: Moving Target Defence Against Stealthy Attacks in Power Grids
13:00-15:00 CET
TUT-03: Malware Analysis and Detection
15:00-17:00 CET
TUT-04: Optimization of DERs for Grid Services in Active Power Distribution Systems
17:00-19:00 CET
TUT-05: Cybersecurity Vulnerabilities in the Power Grid: AI-Enabled Analysis and Decision Making
TUT-01: A Unified Control Framework for Real-Time Power System Operation
Date: Monday, 25 October 2021
Time: 9:00-11:00 CET
Organizer: Lukas Ortmann, ETH
With the increase in solar and wind generation and the deployment of more electric vehicles, the electric power system is going through an unprecedented transformation which render today’s real-time control architecture ineffective. This transition calls for more elaborated real-time control strategies for voltage regulation, line congestion control, and power curtailment. We propose a unified control framework that enables autonomous grid control beyond the state-of-the-art. The key idea is to turn iterative optimization algorithms into robust output-feedback controllers. These controllers, instead of tracking a given reference, drive the system to the optimum of a user-defined optimization problem. Furthermore, these controllers can naturally deal with input and output constraints and are proven to be robust against model mismatch, both in theory and in experiments.
In this tutorial, we will present the theoretical foundation of this framework and present the results of a three year collaboration with the French transmission grid operator, including numerical simulations on a real part of the French subtransmission grid. Furthermore, we will present an experimental demonstration of the controller on a distribution feeder. The attendees will be given access to benchmarks and code to repeat our numerical experiments and compare their own solutions to the proposed approach.
TUT-02: Moving Target Defence Against Stealthy Attacks in Power Grids
Date: Monday, 25 October 2021
Time: 11:00-13:00 CET
Organizer: Subhash Lakshminarayana, U. Warwick
The power grid state estimation (SE) has been known to be vulnerable to False data injection (FDI) attacks that are crafted using the detailed knowledge of the system model. Securing the power grid against such stealthy attacks has been a long-standing problem. Recently, a novel defence strategy, namely, moving target defense (MTD), as an active defence strategy, has been shown to be effective in thwarting such attacks. The key idea behind MTD is to introduce periodic/event-triggered controlled changes to the power grid's SCADA network/ physical plant, thereby invalidating the knowledge attackers use for crafting their attacks. Thus, attacks crafted using outdated system knowledge can be detected. MTD can be implemented as a standalone defence strategy or integrated with other defence strategies (such as date-driven detectors) to form a layered-protection against FDI attacks. Similar idea can also be applied in other cyber-physical systems (CPS).
The tutorial will present a comprehensive overview of MTD in power grids. It will specifically focus on MTD based on active perturbation of power grid's transmission line reactances using distributed flexible AC transmission devices (D-FACTS). The fundamental problem of optimal design of MTD, in combination with other defence strategies, to balance the cost and effectiveness will be thoroughly discussed. Future development of MTD in power grid and other CPS will be identified. We aim to cover the following aspects in this context. (i) Design of MTD perturbation that effectively invalidate the attacker's knowledge. (ii)Assess the impact of MTD perturbations on the power grid's operational cost. (iii) Cost-bene t analysis and deployment questions of MTD in power grids. (iv) Design and implementation of stealth MTD under machine learning-based FDI (v) Development of event-triggered MTD, as a layter protection, to balance the effectiveness and cost.
TUT-03: Malware Analysis and Detection
Date: Monday, 25 October 2021
Time: 13:00-15:00 CET
Organizer: Ashu Sharma, WatchGuard
Often computer/mobile users call everything that disturbs/corrupts their system a VIRUS without being aware of what it means or accomplishes. This tutorial systematically introduces the different varieties of samples under the broad umbrella known as malware, their distinctive properties, different methods of analyzing the malware, and their detection techniques.
The tutorial will cover fundamental techniques, limitations, open research problems and future directions in the field of malware analysis and detection. Following are the three specific learning outcomes:
- Audiences will get familiarity with different types of malware and their detection techniques.
- Applications of classification and clustering based frameworks, tools and techniques for malware detection.
- Overview of significant research problems in the area of malware analysis and detection, results and conclusions from the recent research papers.
TUT-04: Optimization of DERs for Grid Services in Active Power Distribution Systems
Date: Monday, 25 October 2021
Time: 15:00-17:00 CET
Organizer: Anamika Dubey, WSU
With the integration of numerous actionable agents, distributed generation resources, and sensing devices, the electric power distribution system is rapidly evolving into an autonomous and intelligent system. For example, behind-the-meter photovoltaic (PV) output has reached 71.3 GW in the US power grid, with over 2.5 million PV panels installed. Likewise, a recent study shows California’s fleet of light-duty plug-in EVs could double the total transportation electricity demand, from under 5,000 GWh in 2019 to over 10,000 GWh by 2030. Simultaneously, the grid is also getting overwhelmed with extreme weather events that are happening at a higher frequency and causing greater damages. Recent fire-related damages and fatalities caused by high-voltage transmission lines coupled with dry weather are costing billions of dollars annually, with the only practical solution being de-energizing the lines and disrupting the power supply to millions of customers. The recent advances in the distribution grid, including the integration of distributed energy resources (DERs) and microgrids, provide potential means to improve the grid’s operational resilience. However, an advanced decision-support system is needed to plan and manage grid operations by proactively managing the grid’s variable, uncertain, and distributed resources. Consequently, resilient operational solutions for power distribution grids have drawn significant attention. These applications range from using the recent advances in smart grid technology that include remote control capabilities and integration of DERs to enable advanced grid services such as frequency and voltage support for the bulk grid and resilient operations via intentional islanding to support the critical services during disruptions.
The need for advanced grid support functionality from a large number of DERs has led to a growing interest in academia and industry alike on optimization methods for the large-scale unbalanced power distribution systems for improved operational efficiency and resilience. The resulting optimization problems prompt unique challenges requiring extremely fast decision-making to resist the system collapse and consideration to high-impact, low-probability events requiring scalable solutions for risk-averse optimization problems. This tutorial aims to introduce the state-of-the-art optimization methods applied to unbalanced power distribution systems for the provisioning of grid services for resilient grid operations. We will begin by highlighting the unique requirements for the optimization problems to solve these problems and discuss the implications of communication and computing challenges. Then, we describe two specific grid service application cases: (1) Grid service provision via flexible DERs and (2) resilient distribution operations during an extreme event. We will discuss real-world use-cases for both applications and describe the practical challenges of implementing such solutions for large-scale systems.
TUT-05: Cybersecurity Vulnerabilities in the Power Grid: AI-Enabled Analysis and Decision Making
Date: Monday, 25 October 2021
Time: 17:00-19:00 CET
Organizer: Qinghua Li, UARK
The power grid runs upon many intelligent devices for sensing, control, communications, and computation. The trustworthy operation of these devices is crucial, but unfortunately the recent years has seen many cybersecurity vulnerabilities with computing and control devices. Such vulnerabilities are flaws in device firmware and software that could be exploited by adversaries to compromise and take control over devices. They caused real-world incidents such as the 2015/2016 Ukraine Power Grid Attacks, Stuxnet, and the more recent SolarWinds Hack. Thus, it is critical to address cybersecurity vulnerabilities effectively and timely.
Software/firmware vulnerabilities are usually addressed by patching. However, vulnerability and patch management (VPM) faces many challenges. First, patches are not always available. For example, the device vendor might have run out of business and hence is not able to provide patches. Second, patching is not always desirable even when patch is available. This is because patching causes system rebooting and downtime, which needs much effort to coordinate and schedule. Thus, many vulnerabilities are mitigated with other actions before patching can be done. Third, there is a large number of vulnerabilities to deal with. An electric utility company might need to deal with hundreds and even thousands of vulnerabilities in a month. Last but not least, currently vulnerability management (e.g., risk assessment and remediation/mitigation decision making) is usually manually done, which suffers from high cost and low effectiveness. Therefore, new technologies are crucially needed to address vulnerabilities.
While being well recognized in the industry, this problem has not received sufficient attention from the research community, and needs more efforts from the community to tackle. In this tutorial, we will provide a concise but systematic introduction to cybersecurity vulnerability management in power grids, present promising technologies based on recent advances in artificial intelligence (AI), and discuss open challenges in this domain. In particular, the tutorial is planned to be organized around the following topics:
- Introduction to the current VPM practice in the electric sector.
- Challenges, available resources, and the state of the art.
- AI-based risk prediction. This part will present an AI-based technology for automatically predicting when a vulnerability might be weaponized by adversaries [1]. Such prediction provides strong decision support for prioritizing vulnerabilities to minimize cybersecurity risks.
- AI-based risk-aware, context-aware remediation decision making. This part will present an AIbased technology for automatically predicting how vulnerabilities should be remediated considering an organization’s operation context [2].
- AI-based mitigation strategy identification. This part will present an AI-based technology to automatically identify mitigation strategies from online resources for vulnerabilities that need to be mitigated before being patched [3].
- Future research directions.
