Kevin L. Stamber

Evaluating the effect of resource constraints on resilience of bulk power system with an electric power restoration model

Although reliability standards for electric power systems are well accepted, methods and metrics are not established for evaluating the effects of large-scale disruptions that exceed N – 1 criteria for bulk power systems. This paper introduces a model for simulating restoration of bulk power systems following such disruptions. The model allows analysts to simulate disruption of a bulk power system by designating system components as damaged or non-functional. The analyst further defines recovery resource availability and restoration priorities. The model then compares resource requirements to constraints to calculate the timeline of repair completion and the dynamic restoration of power across the network. Resilience metrics quantify the impacts and costs of the disruption to the utility. These quantities enable the analyst to evaluate how proposed system improvements affect restoration and resilience of the bulk power system. The paper concludes with an illustrative case study on a simplified seven-bus system.

Comparative analysis of the transportation of select petrochemicals

Large volumes of hazardous cargo move across US roadways daily. Field counts are conducted on sections of roadway that provide aggregated volumes. A high level of interest exists in acquiring the capability to replicate these periodic field counts through a computer-simulated programme. Base data and computer simulation models were identified, which could be coordinated with field counts. The corridor traversing the core of Houston’s petrochemical industry served as the study area. Simulation data on producers and chemicals within the area were analysed, and alternate means of transportation were identified, to select chemicals most likely to be transported to the geographic area by truck. The likely frequency of shipments was calculated and compared to the field data. The study outcome reflected a good fit between the simulation and the field counts, providing positive conditions for application of the model to other corridors and showing strong potential for its predictive value.

A mission resilience assessment methodology for infrastructure disruptions

Resilience has recently emerged as a security priority, but the development of mission resilience analysis techniques for military systems has lagged behind those for other systems. This paper identifies gaps for mission resilience assessment in current vulnerability assessment approaches used at military facilities. Additionally, the paper describes ongoing research to develop a set of mission resilience models that addresses those gaps and could be used to evaluate mission resilience to electric power outages.

Earthquake warning system for infrastructures : a scoping analysis.

This report provides the results of a scoping study evaluating the potential risk reduction value of a hypothetical, earthquake early-warning system. The study was based on an analysis of the actions that could be taken to reduce risks to population and infrastructures, how much time would be required to take each action and the potential consequences of false alarms given the nature of the action. The results of the scoping analysis indicate that risks could be reduced through improving existing event notification systems and individual responses to the notification; and production and utilization of more detailed risk maps for local planning. Detailed maps and training programs, based on existing knowledge of geologic conditions and processes, would reduce uncertainty in the consequence portion of the risk analysis. Uncertainties in the timing, magnitude and location of earthquakes and the potential impacts of false alarms will present major challenges to the value of an early-warning system.

Executive Summary for Assessing the Near-Term Risk of Climate Uncertainty: Interdependencies among the U.S. States

Policy makers will most likely need to make decisions about climate policy before climate scientists have resolved all relevant uncertainties about the impacts of climate change. This study demonstrates a risk-assessment methodology for evaluating uncertain future climatic conditions. We estimate the impacts of climate change on U.S. state- and national-level economic activity from 2010 to 2050. To understand the implications of uncertainty on risk and to provide a near-term rationale for policy interventions to mitigate the course of climate change, we focus on precipitation, one of the most uncertain aspects of future climate change. We use results of the climate-model ensemble from the Intergovernmental Panel on Climate Changes (IPCC) Fourth Assessment Report 4 (AR4) as a proxy for representing climate uncertainty over the next 40 years, map the simulated weather from the climate models hydrologically to the county level to determine the physical consequences on economic activity at the state level, and perform a detailed 70-industry analysis of economic impacts among the interacting lower-48 states. We determine the industry-level contribution to the gross domestic product and employment impacts at the state level, as well as interstate population migration, effects on personal income, and consequences for the U.S. trade balance. We show that the mean or average risk of damage to the U.S. economy from climate change, at the national level, is on the order of

The effects of residential real-time pricing contracts on transco loads, pricing, and profitability : Simulations using the N-ABLE™ agent-based model

1 trillion over the next 40 years, with losses in employment equivalent to nearly 7 million full-time jobs.