Using maintenance options to maximize the benefits of prognostics for wind farms
ABSTRACT Many engineering systems incorporate prognostics and health management (PHM), which consists of technologies and methods to assess the reliability of a product in its actual life‐cycle conditions to determine the advent of failure and mitigate system risks. Wind turbines are among the syste...
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| Veröffentlicht in: | Wind energy (Chichester, England) England), 2014-05, Vol.17 (5), p.775-791 |
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| container_title | Wind energy (Chichester, England) |
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| creator | Haddad, G. Sandborn, P. A. Pecht, M. G. |
| description | ABSTRACT
Many engineering systems incorporate prognostics and health management (PHM), which consists of technologies and methods to assess the reliability of a product in its actual life‐cycle conditions to determine the advent of failure and mitigate system risks. Wind turbines are among the systems that incorporate PHM to reduce life‐cycle costs and increase availability. Although cost–benefit models that quantify the value of implementing prognostics within systems exist for wind energy systems, they do not specifically quantify the value of decisions after a prognostic indication. This paper introduces maintenance options as a means to quantify the value of decisions after a prognostic indication. A case study on a US land‐based wind farm is discussed. An analysis of wind turbine maintenance data is presented, and the maintenance options methodology is then demonstrated to establish the value of the wait‐to‐maintain option. The value of waiting after a prognostic indication is determined using a model that quantifies the benefit that results from a PHM implementation that allows the decision maker to delay maintenance actions, thereby using the remaining life of the system components rather than throwing it away. Copyright © 2013 John Wiley & Sons, Ltd. |
| doi_str_mv | 10.1002/we.1610 |
| format | Article |
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Many engineering systems incorporate prognostics and health management (PHM), which consists of technologies and methods to assess the reliability of a product in its actual life‐cycle conditions to determine the advent of failure and mitigate system risks. Wind turbines are among the systems that incorporate PHM to reduce life‐cycle costs and increase availability. Although cost–benefit models that quantify the value of implementing prognostics within systems exist for wind energy systems, they do not specifically quantify the value of decisions after a prognostic indication. This paper introduces maintenance options as a means to quantify the value of decisions after a prognostic indication. A case study on a US land‐based wind farm is discussed. An analysis of wind turbine maintenance data is presented, and the maintenance options methodology is then demonstrated to establish the value of the wait‐to‐maintain option. The value of waiting after a prognostic indication is determined using a model that quantifies the benefit that results from a PHM implementation that allows the decision maker to delay maintenance actions, thereby using the remaining life of the system components rather than throwing it away. Copyright © 2013 John Wiley & Sons, Ltd.</description><identifier>ISSN: 1095-4244</identifier><identifier>EISSN: 1099-1824</identifier><identifier>DOI: 10.1002/we.1610</identifier><language>eng</language><publisher>Bognor Regis: Blackwell Publishing Ltd</publisher><subject>condition-based maintenance ; decision support ; life-cycle cost ; maintenance options ; operation and maintenance ; prognostics and health management ; real options ; wind farms</subject><ispartof>Wind energy (Chichester, England), 2014-05, Vol.17 (5), p.775-791</ispartof><rights>Copyright © 2013 John Wiley & Sons, Ltd.</rights><rights>Copyright © 2014 John Wiley & Sons, Ltd.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4010-da18f3f463a310c944c3658db6acd5ab3e2158125cdae2f0618c2fc0e778b8bd3</citedby><cites>FETCH-LOGICAL-c4010-da18f3f463a310c944c3658db6acd5ab3e2158125cdae2f0618c2fc0e778b8bd3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fwe.1610$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fwe.1610$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,27901,27902,45550,45551</link.rule.ids></links><search><creatorcontrib>Haddad, G.</creatorcontrib><creatorcontrib>Sandborn, P. A.</creatorcontrib><creatorcontrib>Pecht, M. G.</creatorcontrib><title>Using maintenance options to maximize the benefits of prognostics for wind farms</title><title>Wind energy (Chichester, England)</title><addtitle>Wind Energ</addtitle><description>ABSTRACT
Many engineering systems incorporate prognostics and health management (PHM), which consists of technologies and methods to assess the reliability of a product in its actual life‐cycle conditions to determine the advent of failure and mitigate system risks. Wind turbines are among the systems that incorporate PHM to reduce life‐cycle costs and increase availability. Although cost–benefit models that quantify the value of implementing prognostics within systems exist for wind energy systems, they do not specifically quantify the value of decisions after a prognostic indication. This paper introduces maintenance options as a means to quantify the value of decisions after a prognostic indication. A case study on a US land‐based wind farm is discussed. An analysis of wind turbine maintenance data is presented, and the maintenance options methodology is then demonstrated to establish the value of the wait‐to‐maintain option. The value of waiting after a prognostic indication is determined using a model that quantifies the benefit that results from a PHM implementation that allows the decision maker to delay maintenance actions, thereby using the remaining life of the system components rather than throwing it away. Copyright © 2013 John Wiley & Sons, Ltd.</description><subject>condition-based maintenance</subject><subject>decision support</subject><subject>life-cycle cost</subject><subject>maintenance options</subject><subject>operation and maintenance</subject><subject>prognostics and health management</subject><subject>real options</subject><subject>wind farms</subject><issn>1095-4244</issn><issn>1099-1824</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><recordid>eNp10FlLAzEQAOBFFKwH_oWADwqyNbP3PkqtB9QTpb6FbHai0d2kJlva-uuNrvgg-DTD8DFXEOwBHQKl0fECh5ABXQsGQMsyhCJK1r_zNEyiJNkMtpx7pRQoQDEIbh-d0s-k5Up3qLkWSMysU0Y70hlfXqpWfSDpXpBUqFGqzhEjycyaZ21cp4Qj0liyULomktvW7QQbkjcOd3_idvB4Nn4YXYSTm_PL0ckkFImfHdYcChnLJIt5DFSUSSLiLC3qKuOiTnkVYwRpAVEqao6RpBkUIpKCYp4XVVHV8XZw2Pf1q7zP0XWsVU5g03CNZu4YpP5YSssMPN3_Q1_N3Gq_nVcAeeZV6dVBr4Q1zlmUbGZVy-2KAWVfn2ULZF-f9fKolwvV4Oo_xqbjHx32WrkOl7-a2zeW5XGesun1Obt7oqd0dDVi9_EnAsCHlw</recordid><startdate>201405</startdate><enddate>201405</enddate><creator>Haddad, G.</creator><creator>Sandborn, P. A.</creator><creator>Pecht, M. G.</creator><general>Blackwell Publishing Ltd</general><general>John Wiley & Sons, Inc</general><scope>BSCLL</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7ST</scope><scope>C1K</scope><scope>SOI</scope><scope>7U1</scope><scope>7U2</scope><scope>7U6</scope></search><sort><creationdate>201405</creationdate><title>Using maintenance options to maximize the benefits of prognostics for wind farms</title><author>Haddad, G. ; Sandborn, P. A. ; Pecht, M. G.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4010-da18f3f463a310c944c3658db6acd5ab3e2158125cdae2f0618c2fc0e778b8bd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>condition-based maintenance</topic><topic>decision support</topic><topic>life-cycle cost</topic><topic>maintenance options</topic><topic>operation and maintenance</topic><topic>prognostics and health management</topic><topic>real options</topic><topic>wind farms</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Haddad, G.</creatorcontrib><creatorcontrib>Sandborn, P. A.</creatorcontrib><creatorcontrib>Pecht, M. G.</creatorcontrib><collection>Istex</collection><collection>CrossRef</collection><collection>Environment Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Environment Abstracts</collection><collection>Risk Abstracts</collection><collection>Safety Science and Risk</collection><collection>Sustainability Science Abstracts</collection><jtitle>Wind energy (Chichester, England)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Haddad, G.</au><au>Sandborn, P. A.</au><au>Pecht, M. G.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Using maintenance options to maximize the benefits of prognostics for wind farms</atitle><jtitle>Wind energy (Chichester, England)</jtitle><addtitle>Wind Energ</addtitle><date>2014-05</date><risdate>2014</risdate><volume>17</volume><issue>5</issue><spage>775</spage><epage>791</epage><pages>775-791</pages><issn>1095-4244</issn><eissn>1099-1824</eissn><abstract>ABSTRACT
Many engineering systems incorporate prognostics and health management (PHM), which consists of technologies and methods to assess the reliability of a product in its actual life‐cycle conditions to determine the advent of failure and mitigate system risks. Wind turbines are among the systems that incorporate PHM to reduce life‐cycle costs and increase availability. Although cost–benefit models that quantify the value of implementing prognostics within systems exist for wind energy systems, they do not specifically quantify the value of decisions after a prognostic indication. This paper introduces maintenance options as a means to quantify the value of decisions after a prognostic indication. A case study on a US land‐based wind farm is discussed. An analysis of wind turbine maintenance data is presented, and the maintenance options methodology is then demonstrated to establish the value of the wait‐to‐maintain option. The value of waiting after a prognostic indication is determined using a model that quantifies the benefit that results from a PHM implementation that allows the decision maker to delay maintenance actions, thereby using the remaining life of the system components rather than throwing it away. Copyright © 2013 John Wiley & Sons, Ltd.</abstract><cop>Bognor Regis</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1002/we.1610</doi><tpages>17</tpages></addata></record> |
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| source | Wiley Online Library Journals Frontfile Complete |
| subjects | condition-based maintenance decision support life-cycle cost maintenance options operation and maintenance prognostics and health management real options wind farms |
| title | Using maintenance options to maximize the benefits of prognostics for wind farms |
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