Phase balancing using genetic algorithm
Unbalanced loads and feeders increase power system investment and operating costs. Single-phase lateral load phase swapping is one of the most popular methods to balance the systems. Phase swapping is a large-scale combinatorial optimization problem and it is necessary to apply a proper optimization...
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| creator | Gandomkar, M. |
| description | Unbalanced loads and feeders increase power system investment and operating costs. Single-phase lateral load phase swapping is one of the most popular methods to balance the systems. Phase swapping is a large-scale combinatorial optimization problem and it is necessary to apply a proper optimization method. In this paper, a genetic algorithm (GA) is used to solve the phase swapping problem for single-phase loads. An example is used to illustrate the proposed method. |
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Single-phase lateral load phase swapping is one of the most popular methods to balance the systems. Phase swapping is a large-scale combinatorial optimization problem and it is necessary to apply a proper optimization method. In this paper, a genetic algorithm (GA) is used to solve the phase swapping problem for single-phase loads. An example is used to illustrate the proposed method.</description><identifier>ISBN: 9781860433658</identifier><identifier>ISBN: 1860433650</identifier><language>eng</language><publisher>Bristol: IEEE</publisher><subject>Applied sciences ; Computational modeling ; Cost function ; Electrical engineering. 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Electrical power engineering</subject><subject>Electrical power engineering</subject><subject>Energy loss</subject><subject>Exact sciences and technology</subject><subject>Genetic algorithms</subject><subject>Large-scale systems</subject><subject>Linear programming</subject><subject>Load flow</subject><subject>Miscellaneous</subject><subject>Optimization methods</subject><subject>Power networks and lines</subject><subject>Simulated annealing</subject><subject>Voltage</subject><isbn>9781860433658</isbn><isbn>1860433650</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2004</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpFTk1LxDAUDIiwsvYX7KUX8VR4eUnzcZTFL1jQg56Xl_SlG-nWpakH_72WFZzDzMAMw1yIylsnnQGtlGndSlSlfMAvHFqn5ZW4fT1Q4TrQQGPMY19_lYV7HnnOsaah_5zyfDhei8tEQ-HqT9fi_eH-bfvU7F4en7d3uyZLhLkhZosOAmCLhg0FMClACiGkxbPS0XcdBh-VQ5TIFro2JO5aGbSWSq3FzXn3RCXSkKblVtmfpnyk6XsvrQXj9dLbnHuZmf9j7RHQqx92Vkcc</recordid><startdate>2004</startdate><enddate>2004</enddate><creator>Gandomkar, M.</creator><general>IEEE</general><general>University of the West of England (UWE)</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope><scope>IQODW</scope></search><sort><creationdate>2004</creationdate><title>Phase balancing using genetic algorithm</title><author>Gandomkar, M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i120t-aee7280b02526e6ab06fb0fbbbfab06e34c9dd2b9c382212e70d5bfed51b44133</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2004</creationdate><topic>Applied sciences</topic><topic>Computational modeling</topic><topic>Cost function</topic><topic>Electrical engineering. Electrical power engineering</topic><topic>Electrical power engineering</topic><topic>Energy loss</topic><topic>Exact sciences and technology</topic><topic>Genetic algorithms</topic><topic>Large-scale systems</topic><topic>Linear programming</topic><topic>Load flow</topic><topic>Miscellaneous</topic><topic>Optimization methods</topic><topic>Power networks and lines</topic><topic>Simulated annealing</topic><topic>Voltage</topic><toplevel>online_resources</toplevel><creatorcontrib>Gandomkar, M.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection><collection>Pascal-Francis</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Gandomkar, M.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Phase balancing using genetic algorithm</atitle><btitle>39th International Universities Power Engineering Conference, 2004. UPEC 2004</btitle><stitle>UPEC</stitle><date>2004</date><risdate>2004</risdate><volume>1</volume><spage>377</spage><epage>379 Vol. 1</epage><pages>377-379 Vol. 1</pages><isbn>9781860433658</isbn><isbn>1860433650</isbn><abstract>Unbalanced loads and feeders increase power system investment and operating costs. Single-phase lateral load phase swapping is one of the most popular methods to balance the systems. Phase swapping is a large-scale combinatorial optimization problem and it is necessary to apply a proper optimization method. In this paper, a genetic algorithm (GA) is used to solve the phase swapping problem for single-phase loads. An example is used to illustrate the proposed method.</abstract><cop>Bristol</cop><pub>IEEE</pub></addata></record> |
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| ispartof | 39th International Universities Power Engineering Conference, 2004. UPEC 2004, 2004, Vol.1, p.377-379 Vol. 1 |
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| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Applied sciences Computational modeling Cost function Electrical engineering. Electrical power engineering Electrical power engineering Energy loss Exact sciences and technology Genetic algorithms Large-scale systems Linear programming Load flow Miscellaneous Optimization methods Power networks and lines Simulated annealing Voltage |
| title | Phase balancing using genetic algorithm |
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