Bulk power risk analysis : ranking infrastructure elements according to their risk significance
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Nuclear Science and Engineering, 2006. === Includes bibliographical references (p. 50-52). === Disruptions in the bulk power grid can result in very diverse consequences that include economic, social, physical, and psychological impacts....
Main Author: | |
---|---|
Other Authors: | |
Format: | Others |
Language: | English |
Published: |
Massachusetts Institute of Technology
2008
|
Subjects: | |
Online Access: | http://hdl.handle.net/1721.1/41272 |
id |
ndltd-MIT-oai-dspace.mit.edu-1721.1-41272 |
---|---|
record_format |
oai_dc |
spelling |
ndltd-MIT-oai-dspace.mit.edu-1721.1-412722019-05-02T16:22:39Z Bulk power risk analysis : ranking infrastructure elements according to their risk significance Koonce, Anthony M George E. Apostolakis. Massachusetts Institute of Technology. Dept. of Nuclear Science and Engineering. Massachusetts Institute of Technology. Dept. of Nuclear Science and Engineering. Nuclear Science and Engineering. Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Nuclear Science and Engineering, 2006. Includes bibliographical references (p. 50-52). Disruptions in the bulk power grid can result in very diverse consequences that include economic, social, physical, and psychological impacts. In addition, power outages do not affect all end-users of the system in the same manner. For these reasons, a risk analysis of bulk power systems requires more than determining the likelihood and magnitude of power outages; it must also include the diverse impacts power outages have on the users of the system. We propose a methodology for performing a risk analysis on the bulk power system. A power flow simulation model is used to determine the likelihood and extent of power outages when components within the system fail to perform their designed function. The consequences associated with these failures are determined by looking at the type and number of customers affected. Stakeholder input is used to evaluate the relative importance of these consequences. The methodology culminates with a ranking of each system component by its risk significance to the stakeholders. The analysis is performed for failures of infrastructure elements due to both random causes and malevolent acts. by Anthony M. Koonce. S.M. 2008-04-23T14:38:04Z 2008-04-23T14:38:04Z 2006 2006 Thesis http://hdl.handle.net/1721.1/41272 213435813 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 77 p. application/pdf Massachusetts Institute of Technology |
collection |
NDLTD |
language |
English |
format |
Others
|
sources |
NDLTD |
topic |
Nuclear Science and Engineering. |
spellingShingle |
Nuclear Science and Engineering. Koonce, Anthony M Bulk power risk analysis : ranking infrastructure elements according to their risk significance |
description |
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Nuclear Science and Engineering, 2006. === Includes bibliographical references (p. 50-52). === Disruptions in the bulk power grid can result in very diverse consequences that include economic, social, physical, and psychological impacts. In addition, power outages do not affect all end-users of the system in the same manner. For these reasons, a risk analysis of bulk power systems requires more than determining the likelihood and magnitude of power outages; it must also include the diverse impacts power outages have on the users of the system. We propose a methodology for performing a risk analysis on the bulk power system. A power flow simulation model is used to determine the likelihood and extent of power outages when components within the system fail to perform their designed function. The consequences associated with these failures are determined by looking at the type and number of customers affected. Stakeholder input is used to evaluate the relative importance of these consequences. The methodology culminates with a ranking of each system component by its risk significance to the stakeholders. The analysis is performed for failures of infrastructure elements due to both random causes and malevolent acts. === by Anthony M. Koonce. === S.M. |
author2 |
George E. Apostolakis. |
author_facet |
George E. Apostolakis. Koonce, Anthony M |
author |
Koonce, Anthony M |
author_sort |
Koonce, Anthony M |
title |
Bulk power risk analysis : ranking infrastructure elements according to their risk significance |
title_short |
Bulk power risk analysis : ranking infrastructure elements according to their risk significance |
title_full |
Bulk power risk analysis : ranking infrastructure elements according to their risk significance |
title_fullStr |
Bulk power risk analysis : ranking infrastructure elements according to their risk significance |
title_full_unstemmed |
Bulk power risk analysis : ranking infrastructure elements according to their risk significance |
title_sort |
bulk power risk analysis : ranking infrastructure elements according to their risk significance |
publisher |
Massachusetts Institute of Technology |
publishDate |
2008 |
url |
http://hdl.handle.net/1721.1/41272 |
work_keys_str_mv |
AT koonceanthonym bulkpowerriskanalysisrankinginfrastructureelementsaccordingtotheirrisksignificance |
_version_ |
1719039388833284096 |