Genetic algorithms applied to the design of large power distribution systems
This paper presents the application of a new genetic algorithm for the optimal design of large distribution systems, solving the optimal sizing and locating problems of feeders and substations using the corresponding fixed costs as well as the true nonlinear variable costs. It can be also applied to...
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| Veröffentlicht in: | IEEE transactions on power systems 1998-05, Vol.13 (2), p.696-703 |
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| container_title | IEEE transactions on power systems |
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| creator | Ramirez-Rosado, I.J. Bernal-Agustin, J.L. |
| description | This paper presents the application of a new genetic algorithm for the optimal design of large distribution systems, solving the optimal sizing and locating problems of feeders and substations using the corresponding fixed costs as well as the true nonlinear variable costs. It can be also applied to single stage or multistage distribution designs. The genetic algorithm has been tested with real size distribution systems achieving optimal designs in reasonable CPU times compared with respect to the dimensions of such distribution systems. On the other hand, these distribution systems present significantly larger sizes than the ones frequently found in the technical literature about the optimal distribution planning. Furthermore, original operators of the genetic algorithm have been developed in order to obtain global optimal solutions, or very close ones to them. An integer codification of the genetic algorithm has also been used to include several relevant design aspects in the distribution network optimization. |
| doi_str_mv | 10.1109/59.667402 |
| format | Article |
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It can be also applied to single stage or multistage distribution designs. The genetic algorithm has been tested with real size distribution systems achieving optimal designs in reasonable CPU times compared with respect to the dimensions of such distribution systems. On the other hand, these distribution systems present significantly larger sizes than the ones frequently found in the technical literature about the optimal distribution planning. Furthermore, original operators of the genetic algorithm have been developed in order to obtain global optimal solutions, or very close ones to them. An integer codification of the genetic algorithm has also been used to include several relevant design aspects in the distribution network optimization.</description><identifier>ISSN: 0885-8950</identifier><identifier>EISSN: 1558-0679</identifier><identifier>DOI: 10.1109/59.667402</identifier><identifier>CODEN: ITPSEG</identifier><language>eng</language><publisher>New York, NY: IEEE</publisher><subject>Algorithm design and analysis ; Applied sciences ; Cost function ; Design optimization ; Electrical engineering. Electrical power engineering ; Electrical power engineering ; Exact sciences and technology ; Genetic algorithms ; Optimization methods ; Power distribution ; Power networks and lines ; Power system modeling ; Power system planning ; Substations ; System testing ; Theory. 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It can be also applied to single stage or multistage distribution designs. The genetic algorithm has been tested with real size distribution systems achieving optimal designs in reasonable CPU times compared with respect to the dimensions of such distribution systems. On the other hand, these distribution systems present significantly larger sizes than the ones frequently found in the technical literature about the optimal distribution planning. Furthermore, original operators of the genetic algorithm have been developed in order to obtain global optimal solutions, or very close ones to them. An integer codification of the genetic algorithm has also been used to include several relevant design aspects in the distribution network optimization.</description><subject>Algorithm design and analysis</subject><subject>Applied sciences</subject><subject>Cost function</subject><subject>Design optimization</subject><subject>Electrical engineering. Electrical power engineering</subject><subject>Electrical power engineering</subject><subject>Exact sciences and technology</subject><subject>Genetic algorithms</subject><subject>Optimization methods</subject><subject>Power distribution</subject><subject>Power networks and lines</subject><subject>Power system modeling</subject><subject>Power system planning</subject><subject>Substations</subject><subject>System testing</subject><subject>Theory. Simulation</subject><issn>0885-8950</issn><issn>1558-0679</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1998</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo90DFPwzAQBWALgUQpDKxMHhASQ8o5jh17RBUUpEosMEeOc26N0iTYrlD_PUGpOr3hvnvDI-SWwYIx0E9CL6QsC8jPyIwJoTKQpT4nM1BKZEoLuCRXMX4DwMj0jKxX2GHylpp20weftrtIzTC0Hhuaepq2SBuMftPR3tHWhA3Sof_FQBsfU_D1Pvm-o_EQE-7iNblwpo14c8w5-Xp9-Vy-ZeuP1fvyeZ1ZDjJlUmhVNlwIBzU0phYIdTGmctyUEjlDm-dOorIKnBYSdFnXRmgwzgkLnM_Jw9Q7hP5njzFVOx8ttq3psN_HKlc8Z4KzET5O0IY-xoCuGoLfmXCoGFT_e1VCV9Neo70_lppoTeuC6ayPp4c8L4tCyZHdTcwj4ul67PgD9Rxy-w</recordid><startdate>19980501</startdate><enddate>19980501</enddate><creator>Ramirez-Rosado, I.J.</creator><creator>Bernal-Agustin, J.L.</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><scope>RIA</scope><scope>RIE</scope><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>8FD</scope><scope>L7M</scope></search><sort><creationdate>19980501</creationdate><title>Genetic algorithms applied to the design of large power distribution systems</title><author>Ramirez-Rosado, I.J. ; Bernal-Agustin, J.L.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c306t-65987d355f0b0dab5e0b4dab8f3a76e31ec22f6e8c80f956097bba590aff5c033</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1998</creationdate><topic>Algorithm design and analysis</topic><topic>Applied sciences</topic><topic>Cost function</topic><topic>Design optimization</topic><topic>Electrical engineering. Electrical power engineering</topic><topic>Electrical power engineering</topic><topic>Exact sciences and technology</topic><topic>Genetic algorithms</topic><topic>Optimization methods</topic><topic>Power distribution</topic><topic>Power networks and lines</topic><topic>Power system modeling</topic><topic>Power system planning</topic><topic>Substations</topic><topic>System testing</topic><topic>Theory. Simulation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ramirez-Rosado, I.J.</creatorcontrib><creatorcontrib>Bernal-Agustin, J.L.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>IEEE transactions on power systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Ramirez-Rosado, I.J.</au><au>Bernal-Agustin, J.L.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Genetic algorithms applied to the design of large power distribution systems</atitle><jtitle>IEEE transactions on power systems</jtitle><stitle>TPWRS</stitle><date>1998-05-01</date><risdate>1998</risdate><volume>13</volume><issue>2</issue><spage>696</spage><epage>703</epage><pages>696-703</pages><issn>0885-8950</issn><eissn>1558-0679</eissn><coden>ITPSEG</coden><abstract>This paper presents the application of a new genetic algorithm for the optimal design of large distribution systems, solving the optimal sizing and locating problems of feeders and substations using the corresponding fixed costs as well as the true nonlinear variable costs. It can be also applied to single stage or multistage distribution designs. The genetic algorithm has been tested with real size distribution systems achieving optimal designs in reasonable CPU times compared with respect to the dimensions of such distribution systems. On the other hand, these distribution systems present significantly larger sizes than the ones frequently found in the technical literature about the optimal distribution planning. Furthermore, original operators of the genetic algorithm have been developed in order to obtain global optimal solutions, or very close ones to them. An integer codification of the genetic algorithm has also been used to include several relevant design aspects in the distribution network optimization.</abstract><cop>New York, NY</cop><pub>IEEE</pub><doi>10.1109/59.667402</doi><tpages>8</tpages></addata></record> |
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| ispartof | IEEE transactions on power systems, 1998-05, Vol.13 (2), p.696-703 |
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| source | IEEE Electronic Library (IEL) |
| subjects | Algorithm design and analysis Applied sciences Cost function Design optimization Electrical engineering. Electrical power engineering Electrical power engineering Exact sciences and technology Genetic algorithms Optimization methods Power distribution Power networks and lines Power system modeling Power system planning Substations System testing Theory. Simulation |
| title | Genetic algorithms applied to the design of large power distribution systems |
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