Since 2017, the Atlantic and Gulf regions of the United States have been pummeled by massive hurricanes Harvey, Irma, Maria, Florence, and Michael. According to the National Hurricane Center and others, economic losses from these five events could total between US$350 and $400 billion. Many of these losses were the result of damages to the power grid, which occurred because of collapsed structures and faulted lines. The time required to resurrect grid operations after the storms was the same time that many residential, commercial, and industrial electricity users were without power, and their losses are counted with the economic losses caused by actual grid repair.
Faculty and students in the Energy Production and Infrastructure Center (EPIC) at the University of North Carolina at Charlotte are working to make the nation’s power grid more resilient. Often by teaming with colleagues at other institutions and in industry, faculty and students are researching topics in areas such as optimized physical strengthening, big data-driven asset management, sensor-driven monitoring for damage mitigation, grid modeling and modernization, milli-grids through decentralized power production, inclusion of renewable energy, and the economics and policies that affect all energy activities. Recent big storm events provide opportunities to apply these resources to evaluate the effects of the storms, project future extreme storm scenarios, and mitigate damages. More specifically, studying details of these events, the nature of the disaster areas, and the sequence of events leading to the disasters provides valuable data to help improve the resiliency of electric power grids.
From these many topics, two examples of current research at EPIC are highlighted in this article. The first relates to one physical component of the grid that is being evaluated to strengthen it and improve its structural performance. The second example is a systemic review of several grids with respect to their performance during recent hurricanes. The goal is to compare grid performances across different parameters, noting trends that can lead to improved resiliency.
For almost five years, and with support from and in collaboration with the Electric Power Research Institute (EPRI), faculty and staff at EPIC have evaluated the physical load-carrying capabilities and failure mechanisms of insulators. Researchers run standard, full-scale, experimental tests on a variety of insulators, in both braced and unbraced configurations. Using the High-Bay Structures Lab at EPIC, insulators are configured, attached, and loaded at full scale just as they would be installed and loaded in the field. Deflection, stress, strain, and failure data are collected during the test, simultaneously in three directions. A critical review of the test data leads to a better understanding of the behavior of insulators under various load combinations to be experienced in the field. The need for this type of experimental work is expanded by new polymer materials being used to manufacture insulators. These materials require a thorough experimental evaluation in order to fully understand their behavior in the grid. For example, as insulator materials and geometries change, so do failure mechanisms, thereby effecting design requirements. Also, improved computational capabilities allow vendors to analyze and customize their insulators in terms of base material, weather sheds, and end fittings. These differences among vendors make it more difficult to establish a standard design protocol across the industry and may lead to more (or less) conservative designs. This on-going research evaluates various insulators, identifies key parameters that alter performance regardless of vendor, and recommends common design requirements that will reduce the risk of damages or failure, optimize the use of materials, and improve grid resiliency.
According to many predictions, more frequent and intense storms, such as recent hurricanes, will cause damages to the grid generating losses to the economy, to operations and productivity, and to the well-being of communities. For example, category 5 Hurricane Maria resulted in the failure of a large percentage of the Puerto Rico’s transmission system, affecting millions of people as they lost power. Damages from wind, rain, and floods will burden utilities and communities for years to come. As a result, engineering organizations, businesses, utilities, regulators, emergency responders, and the public want to know how power production and delivery systems can be more resilient, thereby reducing losses and inconvenience.
An ongoing NSF-sponsored effort among EPIC, the University of Puerto Rico Mayaguez, Duke Energy, and the Puerto Rico Electric Power Authority has gathered a team of experts who are analyzing damages from recent hurricanes in Puerto Rico and South Florida. They are reconciling details of the weather events with characteristics of the power systems. Unique features of each storm and each geography produce different types of damages for each utility. Comparisons across such different locales, systems, and storms will enhance designs so as to mitigate damages, improve resilience of electrical grids, improve asset management, reduce costs to utilities and supporting companies, reduce demands on government offices and emergency responders, and improve the well-being of effected communities.
Through its post-event forensics investigation, this research team is collecting perishable data on damaged power delivery (transmission and distribution) systems (transformers, conductors, generating stations, substations etc.) along with associated civil infrastructure (towers, power poles, buildings, foundations, etc.). Specifically, the team is constructing an “event line” that overlays the time, location, and nature of the hurricanes with the time, location, and nature of grid damages. The intent is to identify the critical elements that ultimately can help the design of a resilient system and help prioritize the management of assets; that is, design a physical backbone system for a milli-grid scenario integrated with advanced embedded smart grid sensing and monitoring and control technologies (S2MG – Strong and Smart Milli-Grid).
Currently, immediate responses to disaster damages often focus on grid hardening, and long term responses often address the inclusion of renewable energy. These approaches are, understandably, often required by costs and by needs to restore power quickly. While both of these approaches are important parts of a disaster-preparedness strategy, a third option being developed in this research project is the design of an optimal, smart, and resilient power system that will allow rapid recovery after extreme weather events. For example, it is not always cost-effective to design entire power transmission and distribution systems for extreme wind forces, so the S2MG design being developed could provide a more effective approach.
Post-hurricane damage data is extensive, difficult to gather, and complex, and currently there is little opportunity to use it to enhance grid resiliency. The data analyzed in this project will be placed on a web site in geospatial-temporal GIS formats allowing the user to reenact the damage history of the power grid. Such geo-referencing will allow details of storm history to be reconciled with local site conditions and grid conditions. Then, any resilient grid system can be modeled and validated using simulations of different historical storm events anywhere in the world. Only approved data with proper anonymization will be shared by the research team to the broader community, including on the website.
For the future, EPIC has proposed to several funding agencies to expand its current post-hurricane forensics team to include other universities and other utilities for data collection from Hurricanes Florence and Michael. If they are funded, these projects will provide additional data to be combined with data from Irma and Maria. Forensics analysis of damage-data in such a comprehensive way will further advance the knowledge base and applications in grid resiliency as they relate to extreme weather events.