Distribution feeder reconfiguration for load balancing and service restoration by using G-nets inference mechanism
In this paper, the customer information in customer information systems (CIS) and information of customer and distribution transformers in outage management information systems (OMIS) in Taiwan Power Company (Taipower), are used to determine the daily load patterns of service areas, sectionalizing s...
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| Veröffentlicht in: | IEEE transactions on power delivery 2004-07, Vol.19 (3), p.1426-1433 |
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| creator | Ke, Y.-L. |
| description | In this paper, the customer information in customer information systems (CIS) and information of customer and distribution transformers in outage management information systems (OMIS) in Taiwan Power Company (Taipower), are used to determine the daily load patterns of service areas, sectionalizing switches, distribution feeders, and main transformers. During system normal operation conditions, the feeder reconfiguration for load balancing among distribution feeders is obtained by the G-Nets inference mechanism to enhance the operation performance of distribution systems. For distribution contingencies, such as feeder overloading and/or short-circuit fault, the G-Nets inference mechanism with operation rules is applied to derive the optimal switching operation decision for service restoration to perform the optimal load transfer among distribution feeders after the fault has been identified and isolated. To determine the effectiveness of the proposed methodology, a practical Taiwan power distribution system with daily load patterns derived by load survey study is selected to perform the computer simulation. It is found that the G-Nets inference mechanism approach can enhance the solution process of fault restoration with proper load transfer and improve feeder load balancing for distribution systems by considering the load characteristics of the service customers. |
| doi_str_mv | 10.1109/TPWRD.2004.829156 |
| format | Article |
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During system normal operation conditions, the feeder reconfiguration for load balancing among distribution feeders is obtained by the G-Nets inference mechanism to enhance the operation performance of distribution systems. For distribution contingencies, such as feeder overloading and/or short-circuit fault, the G-Nets inference mechanism with operation rules is applied to derive the optimal switching operation decision for service restoration to perform the optimal load transfer among distribution feeders after the fault has been identified and isolated. To determine the effectiveness of the proposed methodology, a practical Taiwan power distribution system with daily load patterns derived by load survey study is selected to perform the computer simulation. It is found that the G-Nets inference mechanism approach can enhance the solution process of fault restoration with proper load transfer and improve feeder load balancing for distribution systems by considering the load characteristics of the service customers.</description><identifier>ISSN: 0885-8977</identifier><identifier>EISSN: 1937-4208</identifier><identifier>DOI: 10.1109/TPWRD.2004.829156</identifier><identifier>CODEN: ITPDE5</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Computational Intelligence Society ; Computer simulation ; Customer satisfaction ; Electric utilities ; Fault diagnosis ; Faults ; Feeders ; Inference ; Inference mechanisms ; Load balancing ; Load balancing (computing) ; Load management ; Management information systems ; Power distribution ; Power system restoration ; Stress concentration ; Studies ; Switches ; Transformers</subject><ispartof>IEEE transactions on power delivery, 2004-07, Vol.19 (3), p.1426-1433</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2004</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c353t-d857537ade6516176d398a889d1984a8fa58d0f95df7dfcba1a85c4f980271053</citedby><cites>FETCH-LOGICAL-c353t-d857537ade6516176d398a889d1984a8fa58d0f95df7dfcba1a85c4f980271053</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/1308376$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/1308376$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Ke, Y.-L.</creatorcontrib><title>Distribution feeder reconfiguration for load balancing and service restoration by using G-nets inference mechanism</title><title>IEEE transactions on power delivery</title><addtitle>TPWRD</addtitle><description>In this paper, the customer information in customer information systems (CIS) and information of customer and distribution transformers in outage management information systems (OMIS) in Taiwan Power Company (Taipower), are used to determine the daily load patterns of service areas, sectionalizing switches, distribution feeders, and main transformers. During system normal operation conditions, the feeder reconfiguration for load balancing among distribution feeders is obtained by the G-Nets inference mechanism to enhance the operation performance of distribution systems. For distribution contingencies, such as feeder overloading and/or short-circuit fault, the G-Nets inference mechanism with operation rules is applied to derive the optimal switching operation decision for service restoration to perform the optimal load transfer among distribution feeders after the fault has been identified and isolated. To determine the effectiveness of the proposed methodology, a practical Taiwan power distribution system with daily load patterns derived by load survey study is selected to perform the computer simulation. It is found that the G-Nets inference mechanism approach can enhance the solution process of fault restoration with proper load transfer and improve feeder load balancing for distribution systems by considering the load characteristics of the service customers.</description><subject>Computational Intelligence Society</subject><subject>Computer simulation</subject><subject>Customer satisfaction</subject><subject>Electric utilities</subject><subject>Fault diagnosis</subject><subject>Faults</subject><subject>Feeders</subject><subject>Inference</subject><subject>Inference mechanisms</subject><subject>Load balancing</subject><subject>Load balancing (computing)</subject><subject>Load management</subject><subject>Management information systems</subject><subject>Power distribution</subject><subject>Power system restoration</subject><subject>Stress concentration</subject><subject>Studies</subject><subject>Switches</subject><subject>Transformers</subject><issn>0885-8977</issn><issn>1937-4208</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2004</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNp90U1rHDEMBmATWug27Q8ouQw9NKfZ-mM8lo8l3xBoKSk9Gq8tpw67dmrPFPLv480ECjnkJBCPhMRLyCdG14xR_fXmx--fp2tO6bAGrpkcD8iKaaH6gVN4Q1YUQPaglXpH3td6Rxukmq5IOY11KnEzTzGnLiB6LF1Bl1OIt3OxSzuXbput7zZ2a5OL6bazyXcVy7_osPE65We6eejmugcXfcKpdjEFLJia2qH7Y1Osuw_kbbDbih-f6yH5dX52c3LZX3-_uDr5dt07IcXUe5BKCmU9jpKNTI1eaLAA2jMNg4VgJXgatPRB-eA2llmQbggaKFeMSnFIjpe99yX_nduNZherw217AfNcDeiRM8WEbvLLq5IDh3EcWIOfX8C7PJfUvjAAAjgXUjXEFuRKrrVgMPcl7mx5MIyafVjmKSyzD8ssYbWZo2UmIuJ_LygINYpHj32R7A</recordid><startdate>20040701</startdate><enddate>20040701</enddate><creator>Ke, Y.-L.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><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><scope>F28</scope></search><sort><creationdate>20040701</creationdate><title>Distribution feeder reconfiguration for load balancing and service restoration by using G-nets inference mechanism</title><author>Ke, Y.-L.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c353t-d857537ade6516176d398a889d1984a8fa58d0f95df7dfcba1a85c4f980271053</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2004</creationdate><topic>Computational Intelligence Society</topic><topic>Computer simulation</topic><topic>Customer satisfaction</topic><topic>Electric utilities</topic><topic>Fault diagnosis</topic><topic>Faults</topic><topic>Feeders</topic><topic>Inference</topic><topic>Inference mechanisms</topic><topic>Load balancing</topic><topic>Load balancing (computing)</topic><topic>Load management</topic><topic>Management information systems</topic><topic>Power distribution</topic><topic>Power system restoration</topic><topic>Stress concentration</topic><topic>Studies</topic><topic>Switches</topic><topic>Transformers</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ke, Y.-L.</creatorcontrib><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><collection>ANTE: Abstracts in New Technology & Engineering</collection><jtitle>IEEE transactions on power delivery</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Ke, Y.-L.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Distribution feeder reconfiguration for load balancing and service restoration by using G-nets inference mechanism</atitle><jtitle>IEEE transactions on power delivery</jtitle><stitle>TPWRD</stitle><date>2004-07-01</date><risdate>2004</risdate><volume>19</volume><issue>3</issue><spage>1426</spage><epage>1433</epage><pages>1426-1433</pages><issn>0885-8977</issn><eissn>1937-4208</eissn><coden>ITPDE5</coden><abstract>In this paper, the customer information in customer information systems (CIS) and information of customer and distribution transformers in outage management information systems (OMIS) in Taiwan Power Company (Taipower), are used to determine the daily load patterns of service areas, sectionalizing switches, distribution feeders, and main transformers. During system normal operation conditions, the feeder reconfiguration for load balancing among distribution feeders is obtained by the G-Nets inference mechanism to enhance the operation performance of distribution systems. For distribution contingencies, such as feeder overloading and/or short-circuit fault, the G-Nets inference mechanism with operation rules is applied to derive the optimal switching operation decision for service restoration to perform the optimal load transfer among distribution feeders after the fault has been identified and isolated. To determine the effectiveness of the proposed methodology, a practical Taiwan power distribution system with daily load patterns derived by load survey study is selected to perform the computer simulation. It is found that the G-Nets inference mechanism approach can enhance the solution process of fault restoration with proper load transfer and improve feeder load balancing for distribution systems by considering the load characteristics of the service customers.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TPWRD.2004.829156</doi><tpages>8</tpages></addata></record> |
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| ispartof | IEEE transactions on power delivery, 2004-07, Vol.19 (3), p.1426-1433 |
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| language | eng |
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| source | IEEE Electronic Library (IEL) |
| subjects | Computational Intelligence Society Computer simulation Customer satisfaction Electric utilities Fault diagnosis Faults Feeders Inference Inference mechanisms Load balancing Load balancing (computing) Load management Management information systems Power distribution Power system restoration Stress concentration Studies Switches Transformers |
| title | Distribution feeder reconfiguration for load balancing and service restoration by using G-nets inference mechanism |
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