Ranking critical assets in interdependent energy transmission networks
•A methodology to identify critical assets in a coupled gas-power grid is proposed.•The feasibility of the geodesic vulnerability index is demonstrated.•Critical nodes are classified by evaluating the performance of 557 networks.•A damage area measure is proposed for the comparison of cascading fail...
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Veröffentlicht in: | Electric power systems research 2019-07, Vol.172, p.242-252 |
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creator | Beyza, Jesus Garcia-Paricio, Eduardo Yusta, Jose M. |
description | •A methodology to identify critical assets in a coupled gas-power grid is proposed.•The feasibility of the geodesic vulnerability index is demonstrated.•Critical nodes are classified by evaluating the performance of 557 networks.•A damage area measure is proposed for the comparison of cascading failures curves.
This article proposes a procedure based on graph theory to identify critical assets in integrated natural gas and electricity infrastructures. In order to validate the results achieved with the graph-based approach, the technique of coupled electricity and gas flows is also used. The criticality level of each node is calculated using the geodesic vulnerability topological index and the classification is determined via a dimensionless measure called damage area. This measure quantifies the performance under cascading failures following the removal of each asset. The methodology is applied to an infrastructure system composed of an IEEE network of 118 buses and a natural gas system of 25 nodes and three compressors, resulting in 557 different case studies. As a conclusion, it is demonstrated that graph theory can be useful and accurate in evaluating and identifying the most critical assets of interdependent electricity and natural gas infrastructures. |
doi_str_mv | 10.1016/j.epsr.2019.03.014 |
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This article proposes a procedure based on graph theory to identify critical assets in integrated natural gas and electricity infrastructures. In order to validate the results achieved with the graph-based approach, the technique of coupled electricity and gas flows is also used. The criticality level of each node is calculated using the geodesic vulnerability topological index and the classification is determined via a dimensionless measure called damage area. This measure quantifies the performance under cascading failures following the removal of each asset. The methodology is applied to an infrastructure system composed of an IEEE network of 118 buses and a natural gas system of 25 nodes and three compressors, resulting in 557 different case studies. As a conclusion, it is demonstrated that graph theory can be useful and accurate in evaluating and identifying the most critical assets of interdependent electricity and natural gas infrastructures.</description><identifier>ISSN: 0378-7796</identifier><identifier>EISSN: 1873-2046</identifier><identifier>DOI: 10.1016/j.epsr.2019.03.014</identifier><language>eng</language><publisher>Amsterdam: Elsevier B.V</publisher><subject>Cascading failures ; Compressors ; Critical assets ; Data buses ; Electricity ; Electricity distribution ; Energy transmission ; Gas flow ; Gas networks ; Graph theory ; Interdependence ; Interdependent infrastructures ; Natural gas ; Natural gas distribution ; Power flow</subject><ispartof>Electric power systems research, 2019-07, Vol.172, p.242-252</ispartof><rights>2019 Elsevier B.V.</rights><rights>Copyright Elsevier Science Ltd. Jul 2019</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c381t-79620cad2094deddfad0eb0d28ebd194706ac685e204066f582de51cd05750513</citedby><cites>FETCH-LOGICAL-c381t-79620cad2094deddfad0eb0d28ebd194706ac685e204066f582de51cd05750513</cites><orcidid>0000-0003-3992-4393 ; 0000-0003-3174-9703</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0378779619301063$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids></links><search><creatorcontrib>Beyza, Jesus</creatorcontrib><creatorcontrib>Garcia-Paricio, Eduardo</creatorcontrib><creatorcontrib>Yusta, Jose M.</creatorcontrib><title>Ranking critical assets in interdependent energy transmission networks</title><title>Electric power systems research</title><description>•A methodology to identify critical assets in a coupled gas-power grid is proposed.•The feasibility of the geodesic vulnerability index is demonstrated.•Critical nodes are classified by evaluating the performance of 557 networks.•A damage area measure is proposed for the comparison of cascading failures curves.
This article proposes a procedure based on graph theory to identify critical assets in integrated natural gas and electricity infrastructures. In order to validate the results achieved with the graph-based approach, the technique of coupled electricity and gas flows is also used. The criticality level of each node is calculated using the geodesic vulnerability topological index and the classification is determined via a dimensionless measure called damage area. This measure quantifies the performance under cascading failures following the removal of each asset. The methodology is applied to an infrastructure system composed of an IEEE network of 118 buses and a natural gas system of 25 nodes and three compressors, resulting in 557 different case studies. As a conclusion, it is demonstrated that graph theory can be useful and accurate in evaluating and identifying the most critical assets of interdependent electricity and natural gas infrastructures.</description><subject>Cascading failures</subject><subject>Compressors</subject><subject>Critical assets</subject><subject>Data buses</subject><subject>Electricity</subject><subject>Electricity distribution</subject><subject>Energy transmission</subject><subject>Gas flow</subject><subject>Gas networks</subject><subject>Graph theory</subject><subject>Interdependence</subject><subject>Interdependent infrastructures</subject><subject>Natural gas</subject><subject>Natural gas distribution</subject><subject>Power flow</subject><issn>0378-7796</issn><issn>1873-2046</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><recordid>eNp9kM9LwzAUx4MoOKf_gKeC59aXpElb8CLDqTAQRM8hS15Hui2dSabsvzdjnoUH7_L9xYeQWwoVBSrvhwp3MVQMaFcBr4DWZ2RC24aXDGp5TibAm7Zsmk5ekqsYBwCQXSMmZP6u_dr5VWGCS87oTaFjxBQL5_MlDBZ36C36VKDHsDoUKWgfty5GN_rCY_oZwzpek4tebyLe_P0p-Zw_fcxeysXb8-vscVEa3tJU5n4GRlsGXW3R2l5bwCVY1uLS0q5uQGojW4F5NUjZi5ZZFNRYEI0AQfmU3J1yd2H82mNMahj3wedKxRgXwICzNqvYSWXCGGPAXu2C2-pwUBTUkZca1JGXOvJSwFXmlU0PJxPm_d8Og4rGoTdoXUCTlB3df_Zf4vl0rQ</recordid><startdate>20190701</startdate><enddate>20190701</enddate><creator>Beyza, Jesus</creator><creator>Garcia-Paricio, Eduardo</creator><creator>Yusta, Jose M.</creator><general>Elsevier B.V</general><general>Elsevier Science Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>8FD</scope><scope>FR3</scope><scope>KR7</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0003-3992-4393</orcidid><orcidid>https://orcid.org/0000-0003-3174-9703</orcidid></search><sort><creationdate>20190701</creationdate><title>Ranking critical assets in interdependent energy transmission networks</title><author>Beyza, Jesus ; Garcia-Paricio, Eduardo ; Yusta, Jose M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c381t-79620cad2094deddfad0eb0d28ebd194706ac685e204066f582de51cd05750513</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Cascading failures</topic><topic>Compressors</topic><topic>Critical assets</topic><topic>Data buses</topic><topic>Electricity</topic><topic>Electricity distribution</topic><topic>Energy transmission</topic><topic>Gas flow</topic><topic>Gas networks</topic><topic>Graph theory</topic><topic>Interdependence</topic><topic>Interdependent infrastructures</topic><topic>Natural gas</topic><topic>Natural gas distribution</topic><topic>Power flow</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Beyza, Jesus</creatorcontrib><creatorcontrib>Garcia-Paricio, Eduardo</creatorcontrib><creatorcontrib>Yusta, Jose M.</creatorcontrib><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Electric power systems research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Beyza, Jesus</au><au>Garcia-Paricio, Eduardo</au><au>Yusta, Jose M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Ranking critical assets in interdependent energy transmission networks</atitle><jtitle>Electric power systems research</jtitle><date>2019-07-01</date><risdate>2019</risdate><volume>172</volume><spage>242</spage><epage>252</epage><pages>242-252</pages><issn>0378-7796</issn><eissn>1873-2046</eissn><abstract>•A methodology to identify critical assets in a coupled gas-power grid is proposed.•The feasibility of the geodesic vulnerability index is demonstrated.•Critical nodes are classified by evaluating the performance of 557 networks.•A damage area measure is proposed for the comparison of cascading failures curves.
This article proposes a procedure based on graph theory to identify critical assets in integrated natural gas and electricity infrastructures. In order to validate the results achieved with the graph-based approach, the technique of coupled electricity and gas flows is also used. The criticality level of each node is calculated using the geodesic vulnerability topological index and the classification is determined via a dimensionless measure called damage area. This measure quantifies the performance under cascading failures following the removal of each asset. The methodology is applied to an infrastructure system composed of an IEEE network of 118 buses and a natural gas system of 25 nodes and three compressors, resulting in 557 different case studies. As a conclusion, it is demonstrated that graph theory can be useful and accurate in evaluating and identifying the most critical assets of interdependent electricity and natural gas infrastructures.</abstract><cop>Amsterdam</cop><pub>Elsevier B.V</pub><doi>10.1016/j.epsr.2019.03.014</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0003-3992-4393</orcidid><orcidid>https://orcid.org/0000-0003-3174-9703</orcidid></addata></record> |
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subjects | Cascading failures Compressors Critical assets Data buses Electricity Electricity distribution Energy transmission Gas flow Gas networks Graph theory Interdependence Interdependent infrastructures Natural gas Natural gas distribution Power flow |
title | Ranking critical assets in interdependent energy transmission networks |
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