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This presentation by Erfan Ibrahim was prepared for NREL's 2017 Cybersecurity and Reslience Workshop on distributed energy resource (DER) best practices. The presentation provides an overview of NREL's Cyber-Physical Systems Security and Resilience R&D Center, the Center's approach to cybersecurity, and disruptive ideas for power grid security and resilience with DER.
Barriers to the participation of distributed energy resources (DERs) in wholesale electricity markets have limited the use of DERs for power system security and resilience. In September 2020, the Federal Energy Regulatory Commission (FERC) approved an order to reduce these barriers. FERC Order No. 2222 enables the participation of DER aggregators in wholesale electricity markets. DERs include renewable generation and technologies that support the integration of renewable generation by increasing grid flexibility and resilience. Requiring wholesale energy markets to allow DER aggregator participation provides a path for DERs to become competitive in these markets. As the contribution from aggregated DERs continues to increase, the aggregator's role in supporting grid security and resilience will become more critical. This paper reviews work that demonstrates how DER aggregators can provide resilience support through technical capabilities, operational strategies, and secure communication architectures. Socioeconomic influences and impacts of aggregators, including implications for social resilience, are presented. In surveying the current state-of-the-art across different but interconnected topics, we illustrate how aggregators can be power system participants that enhance grid security. There is no one-size-fits-all approach to enhancing resilience in a power grid that includes a growing cohort of DER aggregators, but there are many options for aggregators to contribute to a more resilient and secure power grid.
Cyber security and resiliency of Wide-Area Monitoring, Protection and Control (WAMPAC) applications is critically important to ensure secure, reliable, and economic operation of the bulk power system. WAMPAC relies heavily on the security of measurements and control commands transmitted over wide-area communication networks for real-time operational, protection, and control functions. Also, the current “N-1 security criteria” for grid operation is inadequate to address malicious cyber events and therefore it is important to fundamentally redesign WAMPAC and to enhance Energy Management System (EMS) applications to make them attack-resilient. In this paper, we propose an end-to-end defense-in-depth architecture for attack-resilient WAMPAC that addresses resilience at both the infrastructure layer and the application layers. Also, we propose an attack-resilient cyber-physical security framework that encompasses the entire security life cycle including risk assessment, attack prevention, attack detection, attack mitigation, and attack resilience. The overarching objective of this paper is to provide a broad scope that comprehensively describes most of the major research issues and potential solutions in the context of cyber-physical security of WAMPAC for the power grid.
Barriers to the participation of distributed energy resources (DERs) in wholesale electricity markets have limited the use of DERs for power system security and resilience. In September 2020, the Federal Energy Regulatory Commission (FERC) approved an order to reduce these barriers. FERC Order No. 2222 enables the participation of DER aggregators in wholesale electricity markets. DERs include renewable generation and technologies that support the integration of renewable generation by increasing grid flexibility and resilience. Requiring wholesale energy markets to allow DER aggregator participation provides a path for DERs to become competitive in these markets. As the contribution from aggregated DERs continues to increase, the aggregator's role in supporting grid security and resilience will become more critical. This paper reviews work that demonstrates how DER aggregators can provide resilience support through technical capabilities, operational strategies, and secure communication architectures. Socioeconomic influences and impacts of aggregators, including implications for social resilience, are presented. There is no one-size-fits-all approach to enhancing resilience in a power grid that includes a growing cohort of DER aggregators, but there are many options for aggregators to contribute to a more resilient and secure power grid.
Power grid is one of the critical national infrastructures with social, economics, and national security impacts. Particularly, power distribution systems represent part of the infrastructure between power distribution substations and customers such as residential, commercial, and industrial. To address various grid modernization challenges, state-of-the-art algorithms and methodologies have been developed to deploy, operate, and expand a secure and resilient power grid. At the same time, there is a need to develop capabilities to assist power grid stakeholders to quickly get insight into the design and structure of the grid. Data visualization is a key approach to comprehend and understand complex systems such as the power grid. We present GLIMPSE Grid Layout Interface for Model Preview and System Exploration), a graph-based semantic-aware application to visualize and update distribution power grid models. The GLIMPSE can be used with standard IEEE models to search and highlight power grid objects such as generators, loads, overhead lines, etc. Additionally, it supports updating attributes and model export to integrate with GridLAB-D simulations.
This report takes stock of the research NREL conducted on behalf of DOE’s Wind Energy Technologies Office (WETO), other funding and research partners, and the people of the United States during the first half of FY21 (between Oct. 1, 2020 and March 30, 2021). While diverse, all of these efforts shared a common goal to accelerate the deployment of wind energy technologies by helping to improve wind power performance, lower costs, and reduce market barriers to create a more sustainable, secure, and resilient power grid and a cleaner energy future.
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Natural and man-made hazardous events resulting in loss of grid infrastructure assets challenge the electric power grid’s security and resilience. However, the planning and allocation of appropriate contingency resources for such events requires an understanding of their likelihood and the extent of their potential impact. Where these events are of low likelihood, a risk-informed perspective on planning can be problematic as there exists an insufficient statistical basis to directly estimate the probabilities and consequences of their occurrence. Since risk-informed decisions rely on such knowledge, a basis for modeling the risk associated with high-impact low frequency events (HILFs) is essential. Insights from such a model can inform where resources are most rationally and effectively expended. The present effort is focused on development of a HILF risk assessment framework. Such a framework is intended to provide the conceptual and overarching technical basis for the development of HILF risk models that can inform decision makers across numerous stakeholder sectors. The North American Electric Reliability Corporation (NERC) 2014 Standard TPL-001-4 considers severe events for transmission reliability planning, but does not address events of such severity that they have the potential to fail a substantial fraction of grid assets over a region, such as geomagnetic disturbances (GMD), extreme seismic events, and coordinated cyber-physical attacks. These are beyond current planning guidelines. As noted, the risks associated with such events cannot be statistically estimated based on historic experience; however, there does exist a stable of risk modeling techniques for rare events that have proven of value across a wide range of engineering application domains. There is an active and growing interest in evaluating the value of risk management techniques in the State transmission planning and emergency response communities, some of this interest in the context of grid modernization activities. The availability of a grid HILF risk model, integrated across multi-hazard domains which, when interrogated, can support transparent, defensible and effective decisions, is an attractive prospect among these communities. In this report, we document an integrated HILF risk framework intended to inform the development of risk models. These models would be based on the systematic and comprehensive (to within scope) characterization of hazards to the level of detail required for modeling risk, identification of the stressors associated with the hazards (i.e., the means of impacting grid and supporting infrastructure), characterization of the vulnerability of assets to these stressors and the probabilities of asset compromise, the grid’s dynamic response to the asset failures, and assessment of subsequent severities of consequence with respect to selected impact metrics, such as power outage duration and geographic reach. Specifically, the current framework is being developed to;1. Provide the conceptual and overarching technical paradigms for the development of risk models; 2. Identify the classes of models required to implement the framework - providing examples of existing models, and also identifying where modeling gaps exist; 3. Identify the types of data required, addressing circumstances under which data are sparse and the formal elicitation of informed judgment might be required; and 4. Identify means by which the resultant risk models might be interrogated to form the necessary basis for risk management.
Extremely fast charging (XFC) has the potential to reduce the charging time of battery electric vehicles (BEV) to be equivalent to the filling time of internal combustion engine vehicles (ICEV), thus eliminating one of the few advantages ICEV still poses for light- and heavy-duty vehicles. Enabling XFC will, however, require coordination and cooperation between the grid, charging stations, and the vehicles themselves, which leads to an inevitable increase in the attack surface for all systems combined. In securing the overall system, we must not only embrace traditional cybersecurity, which is chiefly concerned with communications and the operation of digital systems, but also cyber-physical systems security as the proper operation of XFC is critically dependent on systems’ abilities to know about (sense) and interact with (actuate) the physical world. The project team consists of academic and industry researchers with backgrounds in cybersecurity, cyber-physical systems security, learning in adversarial environments, transportation security, grid security and resilience, wireless power transfer, converter design, and battery management systems.
The United States' power infrastructure is aging, underfunded, and vulnerable to cyber attack. Emerging smart grid technologies may take some of the burden off of existing systems and make the grid as a whole more efficient, reliable, and secure. The Pacific Northwest National Laboratory (PNNL) is funding research into several aspects of smart grid technology and grid security, creating a software simulation tool that will allow researchers to test power infrastructure control and distribution paradigms by utilizing different smart grid technologies to determine how the grid and these technologies react under different circumstances. Understanding how these systems behave in real-world conditions will lead to new ways to make our power infrastructure more resilient and secure. Demonstrating security in embedded systems is another research area PNNL is tackling. Many of the systems controlling the U.S. critical infrastructure, such as the power grid, lack integrated security and the aging networks protecting them are becoming easier to attack.
The electric power grid is changing. For many decades, the synchronous generator - an electromechanical device invented in 1887 - has been the workhorse and backbone of power grids across the globe. Our entire infrastructure is built around it. But times change, and so does the power grid. Since the early 21st century, we have seen a gradual shift in modern power grids away from synchronous generators to ones dominated by power electronic inverter-based resources (IBRs). Sources such as photovoltaics, wind turbines, battery storage, fuel cells, and other technologies like high-voltage DC transmission interconnections all rely on an inverter to connect and interface with the grid. They are increasingly being installed on the grid to augment, or even replace, traditional energy sources. This change is a fundamental shift that brings tremendous technical challenges and questions: Can a power grid remain stable with many more inverter-based resources? How do we avoid more blackouts on the grid? How do we keep the grid secure and resilient during disturbances? After all, power electronic inverters are nothing like the big, rotating, iron-and-copper machines that the grid heavily relies on. Many of these questions can be answered by using grid-forming (GFM) inverters, yet many research challenges remain. This document explores GFM inverters and how they can help stabilize the future grid, especially during disturbances and contingencies. It summarizes a two-year research and development fellowship program at NREL. We point interested readers to more detailed works developed during the project along the way. Let's dive in
Persistently available power transmission can be disrupted by weather causing power outages with economic and social consequences. This research investigated the effects on the national power grid from a specific weather event, Hurricane Irene, that caused approximately 5.7 million customer power outages along the Eastern Seaboard in August of 2011. The objective was to describe the geographic differences in the grid s vulnerability to these events. Individual factors, such as wind speed or precipitation, were correlated with the number of outages to determine the greatest mechanism of power failure in hopes of strengthening the future power grid. The resulting fragility maps not only depicted 18 counties that were less robust than the design-standard robustness model and three counties that were more robust, but also drew new damage contours with correlated wind speeds and county features.
This presentation on Modernizing and Securing the Grid brought together regional and NREL cybersecurity expertise for USAID's Caribbean Energy Sector Cybersecurity Forum. The presentation's overall purpose was to provide a deep dive into the changes underway in the electric grid, including the greater integration of renewables and distributed energy resources. The presentation also reviewed best practices for building cybersecurity into modern energy systems, including in the areas of vendor assessment and supply chain cybersecurity.
On September 20, 2017, Hurricane Maria made landfall in Puerto Rico, incapacitating the central power system and leaving the entire island without power. To ensure the long-term recovery of Puerto Rico's electric power grid in the most secure and resilient way, the U.S. Department of Energy funded research to develop recommendations for a cohesive new framework of interconnection standards for utility-scale renewable electrical generation and energy storage that ensure cross-technology compatibility and enable high deployment levels without compromising grid reliably, safety, or security. This paper provides a summary of work conducted by the National Renewable Energy Laboratory to analyze and address many shortcomings and areas of improvement to help the Puerto Rico Electric Power Authority (PREPA) establish minimum technical requirements for interconnecting single-technology and hybrid renewable generation because of their importance for PREPA system security and impacts on future integrated resource planning scenarios. Results and findings presented in this paper are important for any island power system.
Phasor measurement units (PMUs) enable better system monitoring and security enhancement in smart grids. In order to enhance power system resilience against outages and blackouts caused by extreme weather events or man-made attacks, it remains a major challenge to determine the optimal number and location of PMUs. In this paper, a multi-objective resilient PMU placement (MORPP) problem is formulated, and solved by a modified Teaching-Learning-Based optimization (MO-TLBO) algorithm. Three objectives are considered in the MORPP problem, minimizing the number of PMUs, maximizing the system observability, and minimizing the voltage stability index. The effectiveness of the proposed method is validated through testing on IEEE 14-bus, 30-bus, and 118-bus test systems. The advantage of the MO-TLBO-based MORPP is demonstrated through the comparison with other methods in the literature, in terms of iteration number, optimality and time of convergence.
Reliable and secure time synchronization underpins the monitoring and control functions of modern power grids. As GPS-based timing infrastructures grow more susceptible to spoofing and jamming, their vulnerabilities pose escalating risks to grid stability. This work investigates a secure, resilient timing framework that can serve as an alternative or redundant source for power grids, with a particular focus on synchrophasorbased applications. A candidate timing system architecture is evaluated to guarantee trustworthy time dissemination, even in degraded conditions. A network hardware-in-the-loop testing of two synchrophasors validates the concepts, demonstrating enhanced timing integrity, improved detection of timing anomalies, and sustained observability during adverse timing events.
In recent years, bulk energy storage has been applied to electric power systems as an auxiliary device for the support of grid reliability via grid services. This approach is useful but only extracts value from storage on a marginal basis because grid services involve only a tiny fraction of the power flowing in a grid. While storage is flexible enough to perform many services, assessing its value on a stacked-services basis obscures its real value: storage is a buffer for electric energy flows. All of its capabilities stem from this one fundamental property. Limiting storage to use as an ancillary services device leaves this primary value untapped. The real value of storage is as a means to provide a key characteristic missing from power grids: the ability to absorb stresses with little or no loss of performance – the essence of resilience. Storage applied systematically throughout the grid can provide the missing “shock absorber” springiness that the grid is missing. To provide this value, storage must be incorporated into the grid as core infrastructure and must be deeply integrated into grid operations. Doing so will provide far-reaching benefits to users of electricity at all levels, including vastly increased system resilience, expanded system operational flexibility, support for critical lifeline functions during critical events, and even improved cyber security.
The paradigm shift in the electric power grid necessitates a revisit of existing control methods to ensure the grid’s security and resilience. In particular, the increased uncertainties and rapidly changing operational conditions in power systems have revealed outstanding issues in terms of either speed, adaptiveness, or scalability of the existing control methods for power systems. On the other hand, the availability of massive real-time data can provide a clearer picture of what is happening in the grid. Recently, deep reinforcement learning (RL) has been regarded and adopted as a promising approach leveraging massive data for fast and adaptive grid control. However, like most existing machine learning (ML)- based control techniques, RL control usually cannot guarantee the safety of the power systems. In this paper, we introduce a novel method for safe RL-based load shedding of power systems that can enhance the safe voltage recovery of the electric power grid after experiencing faults. Numerical simulation on the IEEE 39-bus testcase is performed to demonstrate the effectiveness of the proposed safe RL emergency control, as well as its adaptive capability to faults not seen in the training.