James A. Kavicky

Epfast: a model for simulating uncontrolled islanding in large power systems

This paper describes the capabilities, calculation logic, and foundational assumptions of EPfast, a new simulation and impact analysis tool developed by Argonne National Laboratory. The purpose of the model is to explore the tendency of power systems to spiral into uncontrolled islanding triggered by either man-made or natural disturbances. The model generates a report that quantifies the megawatt reductions in all affected substations, as well as the number, size, and spatial location of the formed island grids. The model is linear and is intended to simulate the impacts of high-consequence events on large-scale power systems. The paper describes a recent application of the model to examine the effects of a high-intensity New Madrid seismic event on the U.S. Eastern Interconnection (USEI). The models final upgrade and subsequent application to the USEI were made possible via funding from U.S. Department of Energys Office of Infrastructure Security and Energy Restoration.

Modeling Electric Power and Natural Gas System Interdependencies

AbstractTo promote the resilience and protection of infrastructure assets from an all-hazards perspective, this paper describes the progress of interdependencies modeling and integration efforts to...

Simulation of the september 8, 2011, san diego blackout

The development of predictive tools for emergency management has recently become a subject of major consideration among emergency responders, especially at the federal level. Often the news of an impending high-consequence threat causes significant stress on these agencies because of their inability to apprise management of probable impacts with sufficient certainty. This paper documents Argonne National Laboratorys effort to demonstrate the predictive capability of its newly enhanced tool called EPfast in estimating the impacts of postulated events on our power system. Specifically, the study focuses on EPfasts ability to estimate power outage areas resulting from random system contingencies. The San Diego September 8, 2011, blackout that affected most of southern California was selected for simulation using EPfast. Results showed agreement with actual reported impacts in both spatial and quantitative terms. The method, assumptions, and data used are presented here, and results showing their potential application to emergency planning are discussed.

Simulating the seismic performance of a large-scale electric network in the U.S. midwest

This paper summarizes the methodology and simulation tools used by Argonne National Laboratory to examine the impact that a high-intensity New Madrid seismic event could have on local electric assets and the performance of surrounding regional electric networks. Local impacts are expressed in terms of the number of assets (under various equipment categories) most likely to be damaged. The total megawatt equivalent of damage-prone power plants is assessed, as is an estimate of power flows that could be disrupted. Damage functions and fragility curves are employed to identify specific electric assets that could be affected. The potential of large-scale electric system collapse is explored via a series of network simulations. The methodology employs two models, the FEMA-developed HAZUS MH-MR3 and Argonne-developed EPfast tool for simulating uncontrolled islanding in electric systems. The models are described, and their complementary roles are discussed.

A natural gas modeling framework for conducting infrastructure analysis studies

Increased emphasis on national critical infrastructure protection has accelerated the need to respond to infrastructure assessment requests in a timely manner with reasonable certainty of system consequences following either natural or deliberate system disruptions. Natural gas supply, transmission, and distribution networks provide an important capability to dependent electric power, industrial, commercial, military, and residential customers. This paper describes the natural gas infrastructure analysis and modeling framework (NGtools) at Argonne National Laboratory that directly supports the analysis of the natural gas transmission network given various system disruptions. Infrastructure analysts, given the task to assess the resiliency of the natural gas infrastructure under various disruption scenarios, efficiently respond with increased certainty to various requests by using the in-house-developed analytical suite of tools within NGtools. Analysts use NGtools to identify critical system components and equipment, assess potential network-wide impacts, and suggest measures to mitigate undesirable system responses.

Linear modeling and simulation of low-voltage electric system for single-point vulnerability assessment of military installation

This paper describes the formulation and development of a linear model to support the single-point vulnerability assessment of electric distribution systems at existing and future U.S. Department of Defense (DoD) military sites. The model uses flow sensitivity factors to rank candidates for designation as ¿critical components¿ and uses triggered cascading line outages to confirm the component¿s criticality. The model is written in Java and integrated in a package that employs a user-friendly graphical user interface (GUI) for convenient display of results. This paper describes the process used to formulate the model and presents a sample application.

Simulating the potential impacts of a 10-kiloton nuclear explosion on an electric power system serving a major city

This paper describes the methodology employed by Argonne to simulate the potential impact of a nuclear explosion on an electric system serving a large populated city. The method uses a combined deterministic and heuristics-based approach for the analysis. Initially, deterministic steady-state tools, such as load flow and EPfast, are used to explore the possibility of uncontrolled islanding. Heuristics are then used to estimate additional potential cascading effects, particularly during the transient period. The effects of the electromagnetic pulse are determined on the basis of findings from previous related studies, while the probable system dynamic response is estimated by using heuristics. System resilience is heuristically assessed in several aspects, including partial and full-load rejection capability of participating power plants, power swing allowance based on initial power angle values, and over-frequency relay protection sufficiency against extreme grid events such as sudden loss of a large load. Major findings are presented and discussed.

Impacts of smart grid data on parallel path and contingency analysis efforts

Although a desirable attribute, not all operations models currently make use of real-time data for various reasons. To say the least, the regional scope and comprehensiveness that current data encompasses may be considered limited and incomplete. However, as computational, communication, security, and instrumentation technologies advance, smart grid technology demonstrates the potential to radically change network monitoring and data collection capabilities and advance simulation methods beyond that achievable given the current institutional environment. Because smart grid has the potential to conduct data collection in real time and to improve modeling and simulation results, potential data overload, validation, security, access, and other challenges are leading to new design opportunities. Similarly, we can expect significant impacts on system operation procedures and increased use of enhanced automation applications in operations decision making.