Generating near-extreme Summer Reference Years for building performance simulation
At present, there is no universally accepted method for deriving near-extreme summer weather data for building performance simulation. Existing data sets such as the Design Summer Years (DSY) used in the UK to estimate summer discomfort in naturally ventilated and free running buildings have been cr...
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Veröffentlicht in: | Building services engineering research & technology 2015-11, Vol.36 (6), p.701-727 |
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description | At present, there is no universally accepted method for deriving near-extreme summer weather data for building performance simulation. Existing data sets such as the Design Summer Years (DSY) used in the UK to estimate summer discomfort in naturally ventilated and free running buildings have been criticised for being inconsistent with the corresponding Test Reference Years (TRY). This paper proposes a method for generating Summer Reference Years (SRY) by adjusting the TRY of a given site with meteorological data in order to represent near-extreme conditions. It takes as the starting point that the TRY is robust, being determined on a monthly basis from the most typical months. Initial simulations for the 14 UK TRY locations show promising results for determining building overheating with the SRY.
Practical application: The proposed method for deriving near-extreme summer years from multi-year data and the corresponding ‘typical’ weather year (TRY) of a given site is applicable to locations worldwide and facilitates summer overheating assessment of naturally ventilated and free running buildings. The method helps to overcome the previous shortcomings of near-extreme summer year selection procedures by providing a clear relationship to the underlying TRY. |
doi_str_mv | 10.1177/0143624415587476 |
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Practical application: The proposed method for deriving near-extreme summer years from multi-year data and the corresponding ‘typical’ weather year (TRY) of a given site is applicable to locations worldwide and facilitates summer overheating assessment of naturally ventilated and free running buildings. The method helps to overcome the previous shortcomings of near-extreme summer year selection procedures by providing a clear relationship to the underlying TRY.</description><identifier>ISSN: 0143-6244</identifier><identifier>EISSN: 1477-0849</identifier><identifier>DOI: 10.1177/0143624415587476</identifier><language>eng</language><publisher>London, England: SAGE Publications</publisher><subject>Building services industry ; Buildings ; Civil engineering ; Data analysis ; Datasets ; Humidity ; Meteorology ; Methods ; Simulation ; Statistical analysis ; Summer ; Temperature ; Weather</subject><ispartof>Building services engineering research & technology, 2015-11, Vol.36 (6), p.701-727</ispartof><rights>The Chartered Institution of Building Services Engineers 2015</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c411t-b7769d36cd7b18910bb3b889c03e04d84e7944953e8c50de55ef68562a7b3353</citedby><cites>FETCH-LOGICAL-c411t-b7769d36cd7b18910bb3b889c03e04d84e7944953e8c50de55ef68562a7b3353</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://journals.sagepub.com/doi/pdf/10.1177/0143624415587476$$EPDF$$P50$$Gsage$$H</linktopdf><linktohtml>$$Uhttps://journals.sagepub.com/doi/10.1177/0143624415587476$$EHTML$$P50$$Gsage$$H</linktohtml><link.rule.ids>314,780,784,21819,27924,27925,43621,43622</link.rule.ids></links><search><creatorcontrib>Jentsch, Mark F</creatorcontrib><creatorcontrib>Eames, Matt E</creatorcontrib><creatorcontrib>Levermore, Geoff J</creatorcontrib><title>Generating near-extreme Summer Reference Years for building performance simulation</title><title>Building services engineering research & technology</title><description>At present, there is no universally accepted method for deriving near-extreme summer weather data for building performance simulation. Existing data sets such as the Design Summer Years (DSY) used in the UK to estimate summer discomfort in naturally ventilated and free running buildings have been criticised for being inconsistent with the corresponding Test Reference Years (TRY). This paper proposes a method for generating Summer Reference Years (SRY) by adjusting the TRY of a given site with meteorological data in order to represent near-extreme conditions. It takes as the starting point that the TRY is robust, being determined on a monthly basis from the most typical months. Initial simulations for the 14 UK TRY locations show promising results for determining building overheating with the SRY.
Practical application: The proposed method for deriving near-extreme summer years from multi-year data and the corresponding ‘typical’ weather year (TRY) of a given site is applicable to locations worldwide and facilitates summer overheating assessment of naturally ventilated and free running buildings. The method helps to overcome the previous shortcomings of near-extreme summer year selection procedures by providing a clear relationship to the underlying TRY.</description><subject>Building services industry</subject><subject>Buildings</subject><subject>Civil engineering</subject><subject>Data analysis</subject><subject>Datasets</subject><subject>Humidity</subject><subject>Meteorology</subject><subject>Methods</subject><subject>Simulation</subject><subject>Statistical analysis</subject><subject>Summer</subject><subject>Temperature</subject><subject>Weather</subject><issn>0143-6244</issn><issn>1477-0849</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp1kM1Lw0AQxRdRsFbvHgOeV3e6H7N7lOIXFITai6ewm0xKSpPU3QT0vzehHkTwNDx-772Bx9g1iFsAxDsBSpqFUqC1RYXmhM1AIXJhlTtlswnziZ-zi5R2QgBKIWZs_UQtRd_X7TZryUdOn32khrK3oWkoZmuqKFJbUPY-0pRVXczCUO_LKXCgOOrGTzjVzbAfe7r2kp1Vfp_o6ufO2ebxYbN85qvXp5fl_YoXCqDnAdG4UpqixADWgQhBBmtdISQJVVpF6JRyWpIttChJa6qM1WbhMUip5ZzdHGsPsfsYKPX5rhtiO37MARdOOzAaRpc4uorYpRSpyg-xbnz8ykHk03D53-HGCD9Gkt_Sr9L__N9bdGzn</recordid><startdate>20151101</startdate><enddate>20151101</enddate><creator>Jentsch, Mark F</creator><creator>Eames, Matt E</creator><creator>Levermore, Geoff J</creator><general>SAGE Publications</general><general>Sage Publications Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7RQ</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>88I</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8FL</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FRNLG</scope><scope>F~G</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K60</scope><scope>K6~</scope><scope>L.-</scope><scope>L6V</scope><scope>M0C</scope><scope>M2P</scope><scope>M7S</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>Q9U</scope><scope>U9A</scope></search><sort><creationdate>20151101</creationdate><title>Generating near-extreme Summer Reference Years for building performance simulation</title><author>Jentsch, Mark F ; Eames, Matt E ; Levermore, Geoff J</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c411t-b7769d36cd7b18910bb3b889c03e04d84e7944953e8c50de55ef68562a7b3353</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Building services industry</topic><topic>Buildings</topic><topic>Civil engineering</topic><topic>Data analysis</topic><topic>Datasets</topic><topic>Humidity</topic><topic>Meteorology</topic><topic>Methods</topic><topic>Simulation</topic><topic>Statistical analysis</topic><topic>Summer</topic><topic>Temperature</topic><topic>Weather</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Jentsch, Mark F</creatorcontrib><creatorcontrib>Eames, Matt E</creatorcontrib><creatorcontrib>Levermore, Geoff J</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Career & Technical Education Database</collection><collection>Access via ABI/INFORM (ProQuest)</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Business Premium Collection (Alumni)</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ProQuest Engineering Collection</collection><collection>ABI/INFORM Global</collection><collection>Science Database</collection><collection>Engineering Database</collection><collection>ProQuest One Business</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>ProQuest Central Basic</collection><jtitle>Building services engineering research & technology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Jentsch, Mark F</au><au>Eames, Matt E</au><au>Levermore, Geoff J</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Generating near-extreme Summer Reference Years for building performance simulation</atitle><jtitle>Building services engineering research & technology</jtitle><date>2015-11-01</date><risdate>2015</risdate><volume>36</volume><issue>6</issue><spage>701</spage><epage>727</epage><pages>701-727</pages><issn>0143-6244</issn><eissn>1477-0849</eissn><abstract>At present, there is no universally accepted method for deriving near-extreme summer weather data for building performance simulation. Existing data sets such as the Design Summer Years (DSY) used in the UK to estimate summer discomfort in naturally ventilated and free running buildings have been criticised for being inconsistent with the corresponding Test Reference Years (TRY). This paper proposes a method for generating Summer Reference Years (SRY) by adjusting the TRY of a given site with meteorological data in order to represent near-extreme conditions. It takes as the starting point that the TRY is robust, being determined on a monthly basis from the most typical months. Initial simulations for the 14 UK TRY locations show promising results for determining building overheating with the SRY.
Practical application: The proposed method for deriving near-extreme summer years from multi-year data and the corresponding ‘typical’ weather year (TRY) of a given site is applicable to locations worldwide and facilitates summer overheating assessment of naturally ventilated and free running buildings. The method helps to overcome the previous shortcomings of near-extreme summer year selection procedures by providing a clear relationship to the underlying TRY.</abstract><cop>London, England</cop><pub>SAGE Publications</pub><doi>10.1177/0143624415587476</doi><tpages>27</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Building services industry Buildings Civil engineering Data analysis Datasets Humidity Meteorology Methods Simulation Statistical analysis Summer Temperature Weather |
title | Generating near-extreme Summer Reference Years for building performance simulation |
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