CIM/E Oriented Graph Database Model Architecture and Parallel Network Topology Processing
CIM/E is an easy and efficient electric power model exchange standard between different Energy Management System vendors. With the rapid growth of data size and system complexity, the traditional relational database is not the best option to store and process the data. In contrast, the graph databas...
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| creator | Zhou, Zhangxin Yuan, Chen Yao, Ziyan Dai, Jiangpeng Liu, Guangyi Dai, Renchang Wang, Zhiwei Huang, Garng M |
| description | CIM/E is an easy and efficient electric power model exchange standard between
different Energy Management System vendors. With the rapid growth of data size
and system complexity, the traditional relational database is not the best
option to store and process the data. In contrast, the graph database and graph
computation show their potential advantages to handle the power system data and
perform real-time data analytics and computation. The graph concept fits power
grid data naturally because of the fundamental structure similarity. Vertex and
edge in the graph database can act as both a parallel storage unit and a
computation unit. In this paper, the CIM/E data is modeled into the graph
database. Based on this model, the parallel network topology processing
algorithm is established and conducted by applying graph computation. The
modeling and parallel network topology processing have been demonstrated in the
modified IEEE test cases and practical Sichuan power network. The processing
efficiency is greatly improved using the proposed method. |
| doi_str_mv | 10.48550/arxiv.1803.05935 |
| format | Article |
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different Energy Management System vendors. With the rapid growth of data size
and system complexity, the traditional relational database is not the best
option to store and process the data. In contrast, the graph database and graph
computation show their potential advantages to handle the power system data and
perform real-time data analytics and computation. The graph concept fits power
grid data naturally because of the fundamental structure similarity. Vertex and
edge in the graph database can act as both a parallel storage unit and a
computation unit. In this paper, the CIM/E data is modeled into the graph
database. Based on this model, the parallel network topology processing
algorithm is established and conducted by applying graph computation. The
modeling and parallel network topology processing have been demonstrated in the
modified IEEE test cases and practical Sichuan power network. The processing
efficiency is greatly improved using the proposed method.</description><identifier>DOI: 10.48550/arxiv.1803.05935</identifier><language>eng</language><subject>Computer Science - Distributed, Parallel, and Cluster Computing</subject><creationdate>2018-03</creationdate><rights>http://arxiv.org/licenses/nonexclusive-distrib/1.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,776,881</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/1803.05935$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.1803.05935$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Zhou, Zhangxin</creatorcontrib><creatorcontrib>Yuan, Chen</creatorcontrib><creatorcontrib>Yao, Ziyan</creatorcontrib><creatorcontrib>Dai, Jiangpeng</creatorcontrib><creatorcontrib>Liu, Guangyi</creatorcontrib><creatorcontrib>Dai, Renchang</creatorcontrib><creatorcontrib>Wang, Zhiwei</creatorcontrib><creatorcontrib>Huang, Garng M</creatorcontrib><title>CIM/E Oriented Graph Database Model Architecture and Parallel Network Topology Processing</title><description>CIM/E is an easy and efficient electric power model exchange standard between
different Energy Management System vendors. With the rapid growth of data size
and system complexity, the traditional relational database is not the best
option to store and process the data. In contrast, the graph database and graph
computation show their potential advantages to handle the power system data and
perform real-time data analytics and computation. The graph concept fits power
grid data naturally because of the fundamental structure similarity. Vertex and
edge in the graph database can act as both a parallel storage unit and a
computation unit. In this paper, the CIM/E data is modeled into the graph
database. Based on this model, the parallel network topology processing
algorithm is established and conducted by applying graph computation. The
modeling and parallel network topology processing have been demonstrated in the
modified IEEE test cases and practical Sichuan power network. The processing
efficiency is greatly improved using the proposed method.</description><subject>Computer Science - Distributed, Parallel, and Cluster Computing</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNotz71OwzAYhWEvDKhwAUz4BpI6sR3HYxVKqdTSDlmYos_25zYixJETfnr3tIXpDK90pIeQh4ylopSSzSH-tF9pVjKeMqm5vCVv1Xo7X9JdbLGf0NFVhOFIn2ACAyPSbXDY0UW0x3ZCO31GpNA7uocIXXcurzh9h_hO6zCELhxOdB-DxXFs-8MdufHQjXj_vzNSPy_r6iXZ7FbrarFJoFAyyZVWZeYEs4aL0hvNmfFWO4ZemiKXlmthvTIadF6AwHNElzEvhDXWcsVn5PHv9mprhth-QDw1F2NzNfJf765NRA</recordid><startdate>20180315</startdate><enddate>20180315</enddate><creator>Zhou, Zhangxin</creator><creator>Yuan, Chen</creator><creator>Yao, Ziyan</creator><creator>Dai, Jiangpeng</creator><creator>Liu, Guangyi</creator><creator>Dai, Renchang</creator><creator>Wang, Zhiwei</creator><creator>Huang, Garng M</creator><scope>AKY</scope><scope>GOX</scope></search><sort><creationdate>20180315</creationdate><title>CIM/E Oriented Graph Database Model Architecture and Parallel Network Topology Processing</title><author>Zhou, Zhangxin ; Yuan, Chen ; Yao, Ziyan ; Dai, Jiangpeng ; Liu, Guangyi ; Dai, Renchang ; Wang, Zhiwei ; Huang, Garng M</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a675-279781d40cb348fb930bfc9d0ef5b625c394cf7b9a926a4ebfced10f44cbcc373</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Computer Science - Distributed, Parallel, and Cluster Computing</topic><toplevel>online_resources</toplevel><creatorcontrib>Zhou, Zhangxin</creatorcontrib><creatorcontrib>Yuan, Chen</creatorcontrib><creatorcontrib>Yao, Ziyan</creatorcontrib><creatorcontrib>Dai, Jiangpeng</creatorcontrib><creatorcontrib>Liu, Guangyi</creatorcontrib><creatorcontrib>Dai, Renchang</creatorcontrib><creatorcontrib>Wang, Zhiwei</creatorcontrib><creatorcontrib>Huang, Garng M</creatorcontrib><collection>arXiv Computer Science</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Zhou, Zhangxin</au><au>Yuan, Chen</au><au>Yao, Ziyan</au><au>Dai, Jiangpeng</au><au>Liu, Guangyi</au><au>Dai, Renchang</au><au>Wang, Zhiwei</au><au>Huang, Garng M</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>CIM/E Oriented Graph Database Model Architecture and Parallel Network Topology Processing</atitle><date>2018-03-15</date><risdate>2018</risdate><abstract>CIM/E is an easy and efficient electric power model exchange standard between
different Energy Management System vendors. With the rapid growth of data size
and system complexity, the traditional relational database is not the best
option to store and process the data. In contrast, the graph database and graph
computation show their potential advantages to handle the power system data and
perform real-time data analytics and computation. The graph concept fits power
grid data naturally because of the fundamental structure similarity. Vertex and
edge in the graph database can act as both a parallel storage unit and a
computation unit. In this paper, the CIM/E data is modeled into the graph
database. Based on this model, the parallel network topology processing
algorithm is established and conducted by applying graph computation. The
modeling and parallel network topology processing have been demonstrated in the
modified IEEE test cases and practical Sichuan power network. The processing
efficiency is greatly improved using the proposed method.</abstract><doi>10.48550/arxiv.1803.05935</doi><oa>free_for_read</oa></addata></record> |
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| subjects | Computer Science - Distributed, Parallel, and Cluster Computing |
| title | CIM/E Oriented Graph Database Model Architecture and Parallel Network Topology Processing |
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