A Distributed Computing Platform Supporting Power System Security Knowledge Discovery Based on Online Simulation
Power systems are generating masses of data, including measurement and simulation data. To operate and control power systems more effectively, this paper establishes a distributed platform to store, read, and compute massive amounts of data. Our distributed computing platform can support online simu...
Gespeichert in:
| Veröffentlicht in: | IEEE transactions on smart grid 2017-05, Vol.8 (3), p.1513-1524 |
|---|---|
| Hauptverfasser: | , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 1524 |
|---|---|
| container_issue | 3 |
| container_start_page | 1513 |
| container_title | IEEE transactions on smart grid |
| container_volume | 8 |
| creator | Huang, Tian-en Guo, Qinglai Sun, Hongbin |
| description | Power systems are generating masses of data, including measurement and simulation data. To operate and control power systems more effectively, this paper establishes a distributed platform to store, read, and compute massive amounts of data. Our distributed computing platform can support online simulation based power system security knowledge discovery through big data analysis. First, a framework for a distributed computing platform is designed. Then, distributed algorithms are developed, including a distributed massive sampling simulation method and a distributed feature selection method. Next, the software platform and hardware platform for the distributed computing platform are established. Finally, the platform is applied to the Guangdong Province Power System in China to evaluate its accuracy and efficiency. The simulation results show that the distributed computing platform can improve computing efficiency and perform better than a centralized platform. |
| doi_str_mv | 10.1109/TSG.2016.2571442 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_RIE</sourceid><recordid>TN_cdi_crossref_primary_10_1109_TSG_2016_2571442</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>7475869</ieee_id><sourcerecordid>1891107942</sourcerecordid><originalsourceid>FETCH-LOGICAL-c291t-83d9576ae92e3cff1ebbe56bc8109b8fb975685e22955d5f7146d3fb387888b23</originalsourceid><addsrcrecordid>eNo9kN9LwzAQx4soOHTvgi8BnzubpEmTxzl1ioMJnc-lPy4jo21q0jr635uysXu548v3vsd9guABRwuMI_m8S9cLEmG-ICzBcUyughmWsQxpxPH1ZWb0Npg7d4h8UUo5kbOgW6JX7Xqri6GHCq1M0w29bvfou857ZWyD0qHrjD1p5ggWpaPrwetQDlb3I_pqzbGGag9TUmn-wI7oJXc-zbRo29a6BZTqZvCB2rT3wY3Kawfzc78Lft7fdquPcLNdf66Wm7AkEvehoJVkCc9BEqClUhiKAhgvSuH_LYQqZMK4YECIZKxiyr_NK6oKKhIhREHoXfB0yu2s-R3A9dnBDLb1JzMspKeWyHhyRSdXaY1zFlTWWd3kdsxwlE1oM482m9BmZ7R-5fG0ogHgYk_ihAku6T9BSXXu</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1891107942</pqid></control><display><type>article</type><title>A Distributed Computing Platform Supporting Power System Security Knowledge Discovery Based on Online Simulation</title><source>IEEE Electronic Library (IEL)</source><creator>Huang, Tian-en ; Guo, Qinglai ; Sun, Hongbin</creator><creatorcontrib>Huang, Tian-en ; Guo, Qinglai ; Sun, Hongbin</creatorcontrib><description>Power systems are generating masses of data, including measurement and simulation data. To operate and control power systems more effectively, this paper establishes a distributed platform to store, read, and compute massive amounts of data. Our distributed computing platform can support online simulation based power system security knowledge discovery through big data analysis. First, a framework for a distributed computing platform is designed. Then, distributed algorithms are developed, including a distributed massive sampling simulation method and a distributed feature selection method. Next, the software platform and hardware platform for the distributed computing platform are established. Finally, the platform is applied to the Guangdong Province Power System in China to evaluate its accuracy and efficiency. The simulation results show that the distributed computing platform can improve computing efficiency and perform better than a centralized platform.</description><identifier>ISSN: 1949-3053</identifier><identifier>EISSN: 1949-3061</identifier><identifier>DOI: 10.1109/TSG.2016.2571442</identifier><identifier>CODEN: ITSGBQ</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>Computational modeling ; Computer networks ; Computer simulation ; Computing time ; Cybersecurity ; Data analysis ; Data management ; Data mining ; Distributed computing platform ; Distributed databases ; distributed feature selection ; distributed massive sampling simulation ; Distributed processing ; Electric power distribution ; Knowledge discovery ; On-line systems ; online simulation ; Power system security ; power system security knowledge discovery ; Power system stability ; Simulation ; System effectiveness</subject><ispartof>IEEE transactions on smart grid, 2017-05, Vol.8 (3), p.1513-1524</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2017</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c291t-83d9576ae92e3cff1ebbe56bc8109b8fb975685e22955d5f7146d3fb387888b23</citedby><cites>FETCH-LOGICAL-c291t-83d9576ae92e3cff1ebbe56bc8109b8fb975685e22955d5f7146d3fb387888b23</cites><orcidid>0000-0002-5465-9818</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/7475869$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27903,27904,54736</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/7475869$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Huang, Tian-en</creatorcontrib><creatorcontrib>Guo, Qinglai</creatorcontrib><creatorcontrib>Sun, Hongbin</creatorcontrib><title>A Distributed Computing Platform Supporting Power System Security Knowledge Discovery Based on Online Simulation</title><title>IEEE transactions on smart grid</title><addtitle>TSG</addtitle><description>Power systems are generating masses of data, including measurement and simulation data. To operate and control power systems more effectively, this paper establishes a distributed platform to store, read, and compute massive amounts of data. Our distributed computing platform can support online simulation based power system security knowledge discovery through big data analysis. First, a framework for a distributed computing platform is designed. Then, distributed algorithms are developed, including a distributed massive sampling simulation method and a distributed feature selection method. Next, the software platform and hardware platform for the distributed computing platform are established. Finally, the platform is applied to the Guangdong Province Power System in China to evaluate its accuracy and efficiency. The simulation results show that the distributed computing platform can improve computing efficiency and perform better than a centralized platform.</description><subject>Computational modeling</subject><subject>Computer networks</subject><subject>Computer simulation</subject><subject>Computing time</subject><subject>Cybersecurity</subject><subject>Data analysis</subject><subject>Data management</subject><subject>Data mining</subject><subject>Distributed computing platform</subject><subject>Distributed databases</subject><subject>distributed feature selection</subject><subject>distributed massive sampling simulation</subject><subject>Distributed processing</subject><subject>Electric power distribution</subject><subject>Knowledge discovery</subject><subject>On-line systems</subject><subject>online simulation</subject><subject>Power system security</subject><subject>power system security knowledge discovery</subject><subject>Power system stability</subject><subject>Simulation</subject><subject>System effectiveness</subject><issn>1949-3053</issn><issn>1949-3061</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kN9LwzAQx4soOHTvgi8BnzubpEmTxzl1ioMJnc-lPy4jo21q0jr635uysXu548v3vsd9guABRwuMI_m8S9cLEmG-ICzBcUyughmWsQxpxPH1ZWb0Npg7d4h8UUo5kbOgW6JX7Xqri6GHCq1M0w29bvfou857ZWyD0qHrjD1p5ggWpaPrwetQDlb3I_pqzbGGag9TUmn-wI7oJXc-zbRo29a6BZTqZvCB2rT3wY3Kawfzc78Lft7fdquPcLNdf66Wm7AkEvehoJVkCc9BEqClUhiKAhgvSuH_LYQqZMK4YECIZKxiyr_NK6oKKhIhREHoXfB0yu2s-R3A9dnBDLb1JzMspKeWyHhyRSdXaY1zFlTWWd3kdsxwlE1oM482m9BmZ7R-5fG0ogHgYk_ihAku6T9BSXXu</recordid><startdate>20170501</startdate><enddate>20170501</enddate><creator>Huang, Tian-en</creator><creator>Guo, Qinglai</creator><creator>Sun, Hongbin</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><orcidid>https://orcid.org/0000-0002-5465-9818</orcidid></search><sort><creationdate>20170501</creationdate><title>A Distributed Computing Platform Supporting Power System Security Knowledge Discovery Based on Online Simulation</title><author>Huang, Tian-en ; Guo, Qinglai ; Sun, Hongbin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c291t-83d9576ae92e3cff1ebbe56bc8109b8fb975685e22955d5f7146d3fb387888b23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Computational modeling</topic><topic>Computer networks</topic><topic>Computer simulation</topic><topic>Computing time</topic><topic>Cybersecurity</topic><topic>Data analysis</topic><topic>Data management</topic><topic>Data mining</topic><topic>Distributed computing platform</topic><topic>Distributed databases</topic><topic>distributed feature selection</topic><topic>distributed massive sampling simulation</topic><topic>Distributed processing</topic><topic>Electric power distribution</topic><topic>Knowledge discovery</topic><topic>On-line systems</topic><topic>online simulation</topic><topic>Power system security</topic><topic>power system security knowledge discovery</topic><topic>Power system stability</topic><topic>Simulation</topic><topic>System effectiveness</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Huang, Tian-en</creatorcontrib><creatorcontrib>Guo, Qinglai</creatorcontrib><creatorcontrib>Sun, Hongbin</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><jtitle>IEEE transactions on smart grid</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Huang, Tian-en</au><au>Guo, Qinglai</au><au>Sun, Hongbin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Distributed Computing Platform Supporting Power System Security Knowledge Discovery Based on Online Simulation</atitle><jtitle>IEEE transactions on smart grid</jtitle><stitle>TSG</stitle><date>2017-05-01</date><risdate>2017</risdate><volume>8</volume><issue>3</issue><spage>1513</spage><epage>1524</epage><pages>1513-1524</pages><issn>1949-3053</issn><eissn>1949-3061</eissn><coden>ITSGBQ</coden><abstract>Power systems are generating masses of data, including measurement and simulation data. To operate and control power systems more effectively, this paper establishes a distributed platform to store, read, and compute massive amounts of data. Our distributed computing platform can support online simulation based power system security knowledge discovery through big data analysis. First, a framework for a distributed computing platform is designed. Then, distributed algorithms are developed, including a distributed massive sampling simulation method and a distributed feature selection method. Next, the software platform and hardware platform for the distributed computing platform are established. Finally, the platform is applied to the Guangdong Province Power System in China to evaluate its accuracy and efficiency. The simulation results show that the distributed computing platform can improve computing efficiency and perform better than a centralized platform.</abstract><cop>Piscataway</cop><pub>IEEE</pub><doi>10.1109/TSG.2016.2571442</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0002-5465-9818</orcidid></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISSN: 1949-3053 |
| ispartof | IEEE transactions on smart grid, 2017-05, Vol.8 (3), p.1513-1524 |
| issn | 1949-3053 1949-3061 |
| language | eng |
| recordid | cdi_crossref_primary_10_1109_TSG_2016_2571442 |
| source | IEEE Electronic Library (IEL) |
| subjects | Computational modeling Computer networks Computer simulation Computing time Cybersecurity Data analysis Data management Data mining Distributed computing platform Distributed databases distributed feature selection distributed massive sampling simulation Distributed processing Electric power distribution Knowledge discovery On-line systems online simulation Power system security power system security knowledge discovery Power system stability Simulation System effectiveness |
| title | A Distributed Computing Platform Supporting Power System Security Knowledge Discovery Based on Online Simulation |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-28T01%3A18%3A41IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20Distributed%20Computing%20Platform%20Supporting%20Power%20System%20Security%20Knowledge%20Discovery%20Based%20on%20Online%20Simulation&rft.jtitle=IEEE%20transactions%20on%20smart%20grid&rft.au=Huang,%20Tian-en&rft.date=2017-05-01&rft.volume=8&rft.issue=3&rft.spage=1513&rft.epage=1524&rft.pages=1513-1524&rft.issn=1949-3053&rft.eissn=1949-3061&rft.coden=ITSGBQ&rft_id=info:doi/10.1109/TSG.2016.2571442&rft_dat=%3Cproquest_RIE%3E1891107942%3C/proquest_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1891107942&rft_id=info:pmid/&rft_ieee_id=7475869&rfr_iscdi=true |