Identification of linearised RMS-voltage dip patterns based on clustering in renewable plants
Generation units connected to the grid are currently required to meet low-voltage ride-through (LVRT) requirements. In most developed countries, these requirements also apply to renewable sources, mainly wind power plants and photovoltaic installations connected to the grid. This study proposes an a...
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| Veröffentlicht in: | IET generation, transmission & distribution transmission & distribution, 2018-03, Vol.12 (6), p.1256-1262 |
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| container_title | IET generation, transmission & distribution |
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| creator | García-Sánchez, Tania Gómez-Lázaro, Emilio Muljadi, Edward Kessler, Mathieu Muñoz-Benavente, Irene Molina-García, Angel |
| description | Generation units connected to the grid are currently required to meet low-voltage ride-through (LVRT) requirements. In most developed countries, these requirements also apply to renewable sources, mainly wind power plants and photovoltaic installations connected to the grid. This study proposes an alternative characterisation solution to classify and visualise a large number of collected events in light of current limits and requirements. The authors’ approach is based on linearised root-mean-square-(RMS)-voltage trajectories, taking into account LRVT requirements, and a clustering process to identify the most likely pattern trajectories. The proposed solution gives extensive information on an event's severity by providing a simple but complete visualisation of the linearised RMS-voltage patterns. In addition, these patterns are compared to current LVRT requirements to determine similarities or discrepancies. A large number of collected events can then be automatically classified and visualised for comparative purposes. Real disturbances collected from renewable sources in Spain are used to assess the proposed solution. Extensive results and discussions are also included in this study. |
| doi_str_mv | 10.1049/iet-gtd.2017.0474 |
| format | Article |
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(NREL), Golden, CO (United States)</creatorcontrib><description>Generation units connected to the grid are currently required to meet low-voltage ride-through (LVRT) requirements. In most developed countries, these requirements also apply to renewable sources, mainly wind power plants and photovoltaic installations connected to the grid. This study proposes an alternative characterisation solution to classify and visualise a large number of collected events in light of current limits and requirements. The authors’ approach is based on linearised root-mean-square-(RMS)-voltage trajectories, taking into account LRVT requirements, and a clustering process to identify the most likely pattern trajectories. The proposed solution gives extensive information on an event's severity by providing a simple but complete visualisation of the linearised RMS-voltage patterns. In addition, these patterns are compared to current LVRT requirements to determine similarities or discrepancies. A large number of collected events can then be automatically classified and visualised for comparative purposes. Real disturbances collected from renewable sources in Spain are used to assess the proposed solution. Extensive results and discussions are also included in this study.</description><identifier>ISSN: 1751-8687</identifier><identifier>ISSN: 1751-8695</identifier><identifier>EISSN: 1751-8695</identifier><identifier>DOI: 10.1049/iet-gtd.2017.0474</identifier><language>eng</language><publisher>United States: The Institution of Engineering and Technology</publisher><subject>clustering ; clustering process ; generation unit ; linearised RMS‐voltage dip pattern identification ; linearised RMS‐voltage pattern visualisation ; linearised root‐mean‐square‐voltage trajectories ; low-voltage ride-through ; low‐voltage ride‐through requirements ; LVRT ; LVRT requirements ; pattern classification ; pattern clustering ; photovoltaic installations ; photovoltaic power systems ; power generation faults ; power grid ; power grids ; POWER TRANSMISSION AND DISTRIBUTION ; real disturbance collection ; renewable plant ; renewable sources ; Research Article ; RMS‐voltage trajectories ; Spain ; voltage dip ; wind power plants</subject><ispartof>IET generation, transmission & distribution, 2018-03, Vol.12 (6), p.1256-1262</ispartof><rights>The Institution of Engineering and Technology</rights><rights>2018 The Authors. IET Generation, Transmission & Distribution published by John Wiley & Sons, Ltd. on behalf of The Institution of Engineering and Technology</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3952-38256653d48848c7c9527a6074482d01a2896c08d5e6fe2dcacb017ef6cf524c3</citedby><cites>FETCH-LOGICAL-c3952-38256653d48848c7c9527a6074482d01a2896c08d5e6fe2dcacb017ef6cf524c3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1049%2Fiet-gtd.2017.0474$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1049%2Fiet-gtd.2017.0474$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>230,314,776,780,881,1411,11541,27901,27902,45550,45551,46027,46451</link.rule.ids><linktorsrc>$$Uhttps://onlinelibrary.wiley.com/doi/abs/10.1049%2Fiet-gtd.2017.0474$$EView_record_in_Wiley-Blackwell$$FView_record_in_$$GWiley-Blackwell</linktorsrc><backlink>$$Uhttps://www.osti.gov/biblio/1432612$$D View this record in Osti.gov$$Hfree_for_read</backlink></links><search><creatorcontrib>García-Sánchez, Tania</creatorcontrib><creatorcontrib>Gómez-Lázaro, Emilio</creatorcontrib><creatorcontrib>Muljadi, Edward</creatorcontrib><creatorcontrib>Kessler, Mathieu</creatorcontrib><creatorcontrib>Muñoz-Benavente, Irene</creatorcontrib><creatorcontrib>Molina-García, Angel</creatorcontrib><creatorcontrib>National Renewable Energy Lab. (NREL), Golden, CO (United States)</creatorcontrib><title>Identification of linearised RMS-voltage dip patterns based on clustering in renewable plants</title><title>IET generation, transmission & distribution</title><description>Generation units connected to the grid are currently required to meet low-voltage ride-through (LVRT) requirements. In most developed countries, these requirements also apply to renewable sources, mainly wind power plants and photovoltaic installations connected to the grid. This study proposes an alternative characterisation solution to classify and visualise a large number of collected events in light of current limits and requirements. The authors’ approach is based on linearised root-mean-square-(RMS)-voltage trajectories, taking into account LRVT requirements, and a clustering process to identify the most likely pattern trajectories. The proposed solution gives extensive information on an event's severity by providing a simple but complete visualisation of the linearised RMS-voltage patterns. In addition, these patterns are compared to current LVRT requirements to determine similarities or discrepancies. A large number of collected events can then be automatically classified and visualised for comparative purposes. Real disturbances collected from renewable sources in Spain are used to assess the proposed solution. Extensive results and discussions are also included in this study.</description><subject>clustering</subject><subject>clustering process</subject><subject>generation unit</subject><subject>linearised RMS‐voltage dip pattern identification</subject><subject>linearised RMS‐voltage pattern visualisation</subject><subject>linearised root‐mean‐square‐voltage trajectories</subject><subject>low-voltage ride-through</subject><subject>low‐voltage ride‐through requirements</subject><subject>LVRT</subject><subject>LVRT requirements</subject><subject>pattern classification</subject><subject>pattern clustering</subject><subject>photovoltaic installations</subject><subject>photovoltaic power systems</subject><subject>power generation faults</subject><subject>power grid</subject><subject>power grids</subject><subject>POWER TRANSMISSION AND DISTRIBUTION</subject><subject>real disturbance collection</subject><subject>renewable plant</subject><subject>renewable sources</subject><subject>Research Article</subject><subject>RMS‐voltage trajectories</subject><subject>Spain</subject><subject>voltage dip</subject><subject>wind power plants</subject><issn>1751-8687</issn><issn>1751-8695</issn><issn>1751-8695</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNqFkEFPwyAUxxujiTr9AN6INw-dQIEybzqnLpkx0Xk0hMHrxFTaFOayby_NjPGg8QQ8fn9475dlJwQPCWajcwcxX0Y7pJiUQ8xKtpMdkJKTXIoR3_3ey3I_OwzhDWPOBSsPspepBR9d5YyOrvGoqVDtPOjOBbDo8f4p_2jqqJeArGtRq2OEzge00P114k29Cqnk_BI5jzrwsNaLGlBbax_DUbZX6TrA8dc6yJ5vJvPxXT57uJ2OL2e5KUac5oWkXAheWCYlk6Y0qVhqgUvGJLWYaCpHwmBpOYgKqDXaLNKcUAlTccpMMchOt-82IToVjItgXk3jPZioCCuoIDRBZAuZrgmhg0q1nXvX3UYRrHqJKklUSaLqJapeYspcbDNrV8Pm_4C6nV_Tq5t0FP2HZ9twj701q84nB2o6mffUj0xrq8Tmv7B_N_YJkOqVTQ</recordid><startdate>20180327</startdate><enddate>20180327</enddate><creator>García-Sánchez, Tania</creator><creator>Gómez-Lázaro, Emilio</creator><creator>Muljadi, Edward</creator><creator>Kessler, Mathieu</creator><creator>Muñoz-Benavente, Irene</creator><creator>Molina-García, Angel</creator><general>The Institution of Engineering and Technology</general><general>Institution of Engineering and Technology</general><scope>AAYXX</scope><scope>CITATION</scope><scope>OTOTI</scope></search><sort><creationdate>20180327</creationdate><title>Identification of linearised RMS-voltage dip patterns based on clustering in renewable plants</title><author>García-Sánchez, Tania ; Gómez-Lázaro, Emilio ; Muljadi, Edward ; Kessler, Mathieu ; Muñoz-Benavente, Irene ; Molina-García, Angel</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3952-38256653d48848c7c9527a6074482d01a2896c08d5e6fe2dcacb017ef6cf524c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>clustering</topic><topic>clustering process</topic><topic>generation unit</topic><topic>linearised RMS‐voltage dip pattern identification</topic><topic>linearised RMS‐voltage pattern visualisation</topic><topic>linearised root‐mean‐square‐voltage trajectories</topic><topic>low-voltage ride-through</topic><topic>low‐voltage ride‐through requirements</topic><topic>LVRT</topic><topic>LVRT requirements</topic><topic>pattern classification</topic><topic>pattern clustering</topic><topic>photovoltaic installations</topic><topic>photovoltaic power systems</topic><topic>power generation faults</topic><topic>power grid</topic><topic>power grids</topic><topic>POWER TRANSMISSION AND DISTRIBUTION</topic><topic>real disturbance collection</topic><topic>renewable plant</topic><topic>renewable sources</topic><topic>Research Article</topic><topic>RMS‐voltage trajectories</topic><topic>Spain</topic><topic>voltage dip</topic><topic>wind power plants</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>García-Sánchez, Tania</creatorcontrib><creatorcontrib>Gómez-Lázaro, Emilio</creatorcontrib><creatorcontrib>Muljadi, Edward</creatorcontrib><creatorcontrib>Kessler, Mathieu</creatorcontrib><creatorcontrib>Muñoz-Benavente, Irene</creatorcontrib><creatorcontrib>Molina-García, Angel</creatorcontrib><creatorcontrib>National Renewable Energy Lab. (NREL), Golden, CO (United States)</creatorcontrib><collection>CrossRef</collection><collection>OSTI.GOV</collection><jtitle>IET generation, transmission & distribution</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>García-Sánchez, Tania</au><au>Gómez-Lázaro, Emilio</au><au>Muljadi, Edward</au><au>Kessler, Mathieu</au><au>Muñoz-Benavente, Irene</au><au>Molina-García, Angel</au><aucorp>National Renewable Energy Lab. (NREL), Golden, CO (United States)</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Identification of linearised RMS-voltage dip patterns based on clustering in renewable plants</atitle><jtitle>IET generation, transmission & distribution</jtitle><date>2018-03-27</date><risdate>2018</risdate><volume>12</volume><issue>6</issue><spage>1256</spage><epage>1262</epage><pages>1256-1262</pages><issn>1751-8687</issn><issn>1751-8695</issn><eissn>1751-8695</eissn><abstract>Generation units connected to the grid are currently required to meet low-voltage ride-through (LVRT) requirements. In most developed countries, these requirements also apply to renewable sources, mainly wind power plants and photovoltaic installations connected to the grid. This study proposes an alternative characterisation solution to classify and visualise a large number of collected events in light of current limits and requirements. The authors’ approach is based on linearised root-mean-square-(RMS)-voltage trajectories, taking into account LRVT requirements, and a clustering process to identify the most likely pattern trajectories. The proposed solution gives extensive information on an event's severity by providing a simple but complete visualisation of the linearised RMS-voltage patterns. In addition, these patterns are compared to current LVRT requirements to determine similarities or discrepancies. A large number of collected events can then be automatically classified and visualised for comparative purposes. Real disturbances collected from renewable sources in Spain are used to assess the proposed solution. Extensive results and discussions are also included in this study.</abstract><cop>United States</cop><pub>The Institution of Engineering and Technology</pub><doi>10.1049/iet-gtd.2017.0474</doi><tpages>7</tpages></addata></record> |
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| subjects | clustering clustering process generation unit linearised RMS‐voltage dip pattern identification linearised RMS‐voltage pattern visualisation linearised root‐mean‐square‐voltage trajectories low-voltage ride-through low‐voltage ride‐through requirements LVRT LVRT requirements pattern classification pattern clustering photovoltaic installations photovoltaic power systems power generation faults power grid power grids POWER TRANSMISSION AND DISTRIBUTION real disturbance collection renewable plant renewable sources Research Article RMS‐voltage trajectories Spain voltage dip wind power plants |
| title | Identification of linearised RMS-voltage dip patterns based on clustering in renewable plants |
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