Probability models for estimating the probabilities of cascading outages in high-voltage transmission network
This paper discusses a number of probability models for multiple transmission line outages in power systems, including generalized Poisson model, negative binomial model, and exponentially accelerated model. These models are applied to the multiple transmission outage data for a 20-year period for N...
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| Veröffentlicht in: | IEEE transactions on power systems 2006-08, Vol.21 (3), p.1423-1431 |
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| container_title | IEEE transactions on power systems |
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| creator | Qiming Chen Chuanwen Jiang Wenzheng Qiu McCalley, J.D. |
| description | This paper discusses a number of probability models for multiple transmission line outages in power systems, including generalized Poisson model, negative binomial model, and exponentially accelerated model. These models are applied to the multiple transmission outage data for a 20-year period for North America. The probabilities of the propagation of transmission cascading outage are calculated. These probability magnitudes can serve as indexes for long-term planning and can also be used in short-term operational defense to such events. Results from our research show that all three models apparently explain the occurrence probability of higher order outages very well. However, the exponentially accelerated model fits the observed data and predicts the acceleration trends best. Strict chi-squared fitness tests were done to compare the fitness among these three models, and the test results are consistent with what we observe |
| doi_str_mv | 10.1109/TPWRS.2006.879249 |
| format | Article |
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These models are applied to the multiple transmission outage data for a 20-year period for North America. The probabilities of the propagation of transmission cascading outage are calculated. These probability magnitudes can serve as indexes for long-term planning and can also be used in short-term operational defense to such events. Results from our research show that all three models apparently explain the occurrence probability of higher order outages very well. However, the exponentially accelerated model fits the observed data and predicts the acceleration trends best. Strict chi-squared fitness tests were done to compare the fitness among these three models, and the test results are consistent with what we observe</description><identifier>ISSN: 0885-8950</identifier><identifier>EISSN: 1558-0679</identifier><identifier>DOI: 10.1109/TPWRS.2006.879249</identifier><identifier>CODEN: ITPSEG</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Acceleration ; Binomials ; Blackouts ; Cascading ; Costs ; exponentially accelerated cascading (EAC) ; Fitness ; generalized Poisson distribution (GPD) ; high-order contingency ; Intelligent networks ; Mathematical models ; multiple transmission outages ; negative binomial distribution ; Networks ; Outages ; power law ; Power system analysis computing ; Power system modeling ; Power system planning ; Power transmission lines ; Predictive models ; Probability ; rare events ; Testing ; Transmission lines ; Trends</subject><ispartof>IEEE transactions on power systems, 2006-08, Vol.21 (3), p.1423-1431</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2006</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c324t-5f18269313a61e6fc8d0206bbe8ef07fe803f5427cffe72205b18225351f869d3</citedby><cites>FETCH-LOGICAL-c324t-5f18269313a61e6fc8d0206bbe8ef07fe803f5427cffe72205b18225351f869d3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/1664980$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27903,27904,54737</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/1664980$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Qiming Chen</creatorcontrib><creatorcontrib>Chuanwen Jiang</creatorcontrib><creatorcontrib>Wenzheng Qiu</creatorcontrib><creatorcontrib>McCalley, J.D.</creatorcontrib><title>Probability models for estimating the probabilities of cascading outages in high-voltage transmission network</title><title>IEEE transactions on power systems</title><addtitle>TPWRS</addtitle><description>This paper discusses a number of probability models for multiple transmission line outages in power systems, including generalized Poisson model, negative binomial model, and exponentially accelerated model. These models are applied to the multiple transmission outage data for a 20-year period for North America. The probabilities of the propagation of transmission cascading outage are calculated. These probability magnitudes can serve as indexes for long-term planning and can also be used in short-term operational defense to such events. Results from our research show that all three models apparently explain the occurrence probability of higher order outages very well. However, the exponentially accelerated model fits the observed data and predicts the acceleration trends best. Strict chi-squared fitness tests were done to compare the fitness among these three models, and the test results are consistent with what we observe</description><subject>Acceleration</subject><subject>Binomials</subject><subject>Blackouts</subject><subject>Cascading</subject><subject>Costs</subject><subject>exponentially accelerated cascading (EAC)</subject><subject>Fitness</subject><subject>generalized Poisson distribution (GPD)</subject><subject>high-order contingency</subject><subject>Intelligent networks</subject><subject>Mathematical models</subject><subject>multiple transmission outages</subject><subject>negative binomial distribution</subject><subject>Networks</subject><subject>Outages</subject><subject>power law</subject><subject>Power system analysis computing</subject><subject>Power system modeling</subject><subject>Power system planning</subject><subject>Power transmission lines</subject><subject>Predictive models</subject><subject>Probability</subject><subject>rare events</subject><subject>Testing</subject><subject>Transmission lines</subject><subject>Trends</subject><issn>0885-8950</issn><issn>1558-0679</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2006</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpdkM1KAzEURoMoWKsPIG6CG1dTk8wkkyyl-AeCRSsuQ2bmpk2dTmoyVfr2plYUXAXuPV_47kHolJIRpURdTievT88jRogYyVKxQu2hAeVcZkSUah8NiJQ8k4qTQ3QU44IkMC0GaDkJvjKVa12_wUvfQBux9QFD7N3S9K6b4X4OePVLOYjYW1ybWJtmu_br3szS0HV47mbz7MO32wHug-ni0sXofIc76D99eDtGB9a0EU5-3iF6ubmeju-yh8fb-_HVQ1bnrOgzbqlkQuU0N4KCsLVsCCOiqkCCJaUFSXLLC1bW1kLJGOFVCjCec2qlUE0-RBe7f1Pv93W6RaciNbSt6cCvo5ZKMFZyShJ5_o9c-HXoUjktBZd5SXORILqD6uBjDGD1KiQ7YaMp0Vv9-lu_3urXO_0pc7bLOAD444UoVGr_BSUIgw4</recordid><startdate>20060801</startdate><enddate>20060801</enddate><creator>Qiming Chen</creator><creator>Chuanwen Jiang</creator><creator>Wenzheng Qiu</creator><creator>McCalley, J.D.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>KR7</scope><scope>L7M</scope><scope>F28</scope></search><sort><creationdate>20060801</creationdate><title>Probability models for estimating the probabilities of cascading outages in high-voltage transmission network</title><author>Qiming Chen ; Chuanwen Jiang ; Wenzheng Qiu ; McCalley, J.D.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c324t-5f18269313a61e6fc8d0206bbe8ef07fe803f5427cffe72205b18225351f869d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2006</creationdate><topic>Acceleration</topic><topic>Binomials</topic><topic>Blackouts</topic><topic>Cascading</topic><topic>Costs</topic><topic>exponentially accelerated cascading (EAC)</topic><topic>Fitness</topic><topic>generalized Poisson distribution (GPD)</topic><topic>high-order contingency</topic><topic>Intelligent networks</topic><topic>Mathematical models</topic><topic>multiple transmission outages</topic><topic>negative binomial distribution</topic><topic>Networks</topic><topic>Outages</topic><topic>power law</topic><topic>Power system analysis computing</topic><topic>Power system modeling</topic><topic>Power system planning</topic><topic>Power transmission lines</topic><topic>Predictive models</topic><topic>Probability</topic><topic>rare events</topic><topic>Testing</topic><topic>Transmission lines</topic><topic>Trends</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Qiming Chen</creatorcontrib><creatorcontrib>Chuanwen Jiang</creatorcontrib><creatorcontrib>Wenzheng Qiu</creatorcontrib><creatorcontrib>McCalley, J.D.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><jtitle>IEEE transactions on power systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Qiming Chen</au><au>Chuanwen Jiang</au><au>Wenzheng Qiu</au><au>McCalley, J.D.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Probability models for estimating the probabilities of cascading outages in high-voltage transmission network</atitle><jtitle>IEEE transactions on power systems</jtitle><stitle>TPWRS</stitle><date>2006-08-01</date><risdate>2006</risdate><volume>21</volume><issue>3</issue><spage>1423</spage><epage>1431</epage><pages>1423-1431</pages><issn>0885-8950</issn><eissn>1558-0679</eissn><coden>ITPSEG</coden><abstract>This paper discusses a number of probability models for multiple transmission line outages in power systems, including generalized Poisson model, negative binomial model, and exponentially accelerated model. These models are applied to the multiple transmission outage data for a 20-year period for North America. The probabilities of the propagation of transmission cascading outage are calculated. These probability magnitudes can serve as indexes for long-term planning and can also be used in short-term operational defense to such events. Results from our research show that all three models apparently explain the occurrence probability of higher order outages very well. However, the exponentially accelerated model fits the observed data and predicts the acceleration trends best. Strict chi-squared fitness tests were done to compare the fitness among these three models, and the test results are consistent with what we observe</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TPWRS.2006.879249</doi><tpages>9</tpages></addata></record> |
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| subjects | Acceleration Binomials Blackouts Cascading Costs exponentially accelerated cascading (EAC) Fitness generalized Poisson distribution (GPD) high-order contingency Intelligent networks Mathematical models multiple transmission outages negative binomial distribution Networks Outages power law Power system analysis computing Power system modeling Power system planning Power transmission lines Predictive models Probability rare events Testing Transmission lines Trends |
| title | Probability models for estimating the probabilities of cascading outages in high-voltage transmission network |
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