Katrina SGER: Data collection following Katrina: Interdependencies across time, space, and subsystems characterizing bulk energy transportation
Katrina SGER: Data collection following Katrina: Interdependencies across time, space, and subsystems characterizing bulk energy transportation
批准号:
0553979
负责人:
James McCalley
金额:
$0.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2005
资助国家:
美国
项目状态:
已结题
起止时间:
2005-10-01 至 2006-08-31
中文摘要
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英文摘要
Catastrophic events like hurricane Katrina in the Gulf-Coast area encompass not only a dramatic cost in terms of human lives, but also a devastating effect in critical national infrastructure. The energy infrastructure located in the affected zones has fundamental importance in terms of the operation and performance of the U.S. energy system, which comprises the production, transportation, storage, and conversion of electricity, water, coal, and gas.After the destructive effects of hurricane Katrina were revealed, there was an almost immediate nationwide increase in energy prices and an instant sense of uncertainty in the energy industry about energy availability and prices for the forthcoming months. Because of the enormous complexity of the U.S. energy system, because of the existence of complex interdependencies and interactions between the different infrastructures, and because of the complex sequence of human decision-making associated with bulk energy production, transportation, conversion (generation), and delivery in the integrated energy industry, it is certainly not clear at this point how the hurricane Katrina will really affect the energy supply in terms of economic efficiency and energy availability.The U.S. energy system is composed of many interrelated energy subsystems. Three major subsystems for raw energy (coal, gas, and water) share with electricity the common characteristic that they can be moved in bulk quantities via a transportation network from the source of their production to the site of their use. These different transportation networks are highly coupled, and it is mainly through the electricity subsystem that these couplings take place.System interdependencies are hard to notice under normal operating conditions. When a major perturbation strikes the system, these interdependencies are likely to be revealed. The collection of data of such events and its posterior analysis is of high utility to adequately model the interdependencies and dynamics of the energy system and so to recognize the essential infrastructure that, if disrupted, may adversely affect the performance of other infrastructures. Stressed operating conditions of a highly interconnected and interdependent system will result in a change in the normal behavior of the decision-making processes. The study of the decision-making processes under extreme operating conditions will help to gain better understandings of the social and structural factors affecting the decision-making processes of system participants.Data collection from energy industries operating in the affected zone is of extreme importance in order to obtain a better understanding of the impact of catastrophic events in the energy system, to appreciate how events propagate geographically and in time, and to study infrastructure interdependencies. Acquiring such knowledge will be also very helpful in order to help prevent the most harmful effects, raise awareness about infrastructure vulnerabilities, and to improve the government and industry reaction capacity in the aftermath of catastrophic events. Furthermore, details about interdependent failure modes (cascading, escalating, and common cause failures), and also about the information flows among the decision makers, are data that by their own nature may be perishable. Therefore, it is very important to collect all this vital information while the information is still available.The objective of the project for which we request funds through this proposal is data collection in two complementary fronts, infrastructure interdependence failure data and decision-making processes under extreme conditions. An important portion of the data that this research project intends to gather is perishable data, therefore there is need to collect it before long from the field.
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