Artificial Immune Systems applied to the reconfiguration of electrical power distribution networks for energy loss minimization
•The Artificial Immune System is proposed to reconfigure distribution networks.•The proposed approach seeks minimal energy loss through an improved algorithm.•The algorithm leads to good quality solutions with acceptable computation effort.•The proposed methodology meets the network radiality and co...
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| Veröffentlicht in: | International journal of electrical power & energy systems 2014-03, Vol.56, p.64-74 |
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| container_title | International journal of electrical power & energy systems |
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| creator | de Oliveira, Leonardo W. de Oliveira, Edimar J. Gomes, Flávio V. Silva, Ivo C. Marcato, André L.M. Resende, Paulo V.C. |
| description | •The Artificial Immune System is proposed to reconfigure distribution networks.•The proposed approach seeks minimal energy loss through an improved algorithm.•The algorithm leads to good quality solutions with acceptable computation effort.•The proposed methodology meets the network radiality and connectivity constraints.•Different load levels from daily load curves and the voltage levels are considered.
This paper presents a methodology for the reconfiguration of radial electrical distribution systems based on the bio-inspired meta-heuristic Artificial Immune System to minimize energy losses. The proposed approach can handle this combinatorial mixed integer problem of nonlinear programming. Radiality and connectivity constraints are considered as well as different load levels for planning the system operation. For this purpose, improvements to an algorithm in the literature are proposed to better accommodate the features of the problem and to improve the search process. The algorithm developed is tested in well-known distribution systems. |
| doi_str_mv | 10.1016/j.ijepes.2013.11.008 |
| format | Article |
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This paper presents a methodology for the reconfiguration of radial electrical distribution systems based on the bio-inspired meta-heuristic Artificial Immune System to minimize energy losses. The proposed approach can handle this combinatorial mixed integer problem of nonlinear programming. Radiality and connectivity constraints are considered as well as different load levels for planning the system operation. For this purpose, improvements to an algorithm in the literature are proposed to better accommodate the features of the problem and to improve the search process. The algorithm developed is tested in well-known distribution systems.</description><identifier>ISSN: 0142-0615</identifier><identifier>EISSN: 1879-3517</identifier><identifier>DOI: 10.1016/j.ijepes.2013.11.008</identifier><identifier>CODEN: IEPSDC</identifier><language>eng</language><publisher>Oxford: Elsevier Ltd</publisher><subject>Algorithms ; Applied sciences ; Artificial Immune System ; Artificial intelligence ; Combinatorial analysis ; Distribution system ; Electrical engineering. Electrical power engineering ; Electrical power engineering ; Energy conservation ; Energy distribution ; Energy loss ; Exact sciences and technology ; Miscellaneous ; Mixed integer ; Nonlinear programming ; Power networks and lines ; Reconfiguration</subject><ispartof>International journal of electrical power & energy systems, 2014-03, Vol.56, p.64-74</ispartof><rights>2013 Elsevier Ltd</rights><rights>2015 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c369t-6170b24f5d4ef185dcf6e54d144ba7aef77e8f6e8234e96b0e4b8ecf8c385bb3</citedby><cites>FETCH-LOGICAL-c369t-6170b24f5d4ef185dcf6e54d144ba7aef77e8f6e8234e96b0e4b8ecf8c385bb3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0142061513004663$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=28312777$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>de Oliveira, Leonardo W.</creatorcontrib><creatorcontrib>de Oliveira, Edimar J.</creatorcontrib><creatorcontrib>Gomes, Flávio V.</creatorcontrib><creatorcontrib>Silva, Ivo C.</creatorcontrib><creatorcontrib>Marcato, André L.M.</creatorcontrib><creatorcontrib>Resende, Paulo V.C.</creatorcontrib><title>Artificial Immune Systems applied to the reconfiguration of electrical power distribution networks for energy loss minimization</title><title>International journal of electrical power & energy systems</title><description>•The Artificial Immune System is proposed to reconfigure distribution networks.•The proposed approach seeks minimal energy loss through an improved algorithm.•The algorithm leads to good quality solutions with acceptable computation effort.•The proposed methodology meets the network radiality and connectivity constraints.•Different load levels from daily load curves and the voltage levels are considered.
This paper presents a methodology for the reconfiguration of radial electrical distribution systems based on the bio-inspired meta-heuristic Artificial Immune System to minimize energy losses. The proposed approach can handle this combinatorial mixed integer problem of nonlinear programming. Radiality and connectivity constraints are considered as well as different load levels for planning the system operation. For this purpose, improvements to an algorithm in the literature are proposed to better accommodate the features of the problem and to improve the search process. The algorithm developed is tested in well-known distribution systems.</description><subject>Algorithms</subject><subject>Applied sciences</subject><subject>Artificial Immune System</subject><subject>Artificial intelligence</subject><subject>Combinatorial analysis</subject><subject>Distribution system</subject><subject>Electrical engineering. Electrical power engineering</subject><subject>Electrical power engineering</subject><subject>Energy conservation</subject><subject>Energy distribution</subject><subject>Energy loss</subject><subject>Exact sciences and technology</subject><subject>Miscellaneous</subject><subject>Mixed integer</subject><subject>Nonlinear programming</subject><subject>Power networks and lines</subject><subject>Reconfiguration</subject><issn>0142-0615</issn><issn>1879-3517</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><recordid>eNp9kMFu1DAQhiMEEkvhDTj4gsQlweM4sfeCVFUUKlXiQO-W44zLLEkcbIdqufDquN2qx55GHn3_zPirqvfAG-DQfzo0dMAVUyM4tA1Aw7l-Ue1Aq33ddqBeVjsOUtS8h-519SalA-dc7aXYVf_OYyZPjuzEruZ5W5D9OKaMc2J2XSfCkeXA8k9kEV1YPN1u0WYKCwue4YQuR3Ilu4Y7jGykVN7D9gAsmO9C_JWYD5HhgvH2yKaQEptpoZn-Pox5W73ydkr47rGeVTeXX24uvtXX379eXZxf167t97nuQfFBSN-NEj3obnS-x06OIOVglUWvFOrS0qKVuO8HjnLQ6Lx2re6GoT2rPp7GrjH83jBlM1NyOE12wbAlA10LnINoRUHlCXWxHBvRmzXSbOPRADf3us3BnHSbe90GwBTdJfbhcYNNRYiPdnGUnrJCtyCUUoX7fOKw_PYPYTTJES4ORyqGsxkDPb_oPxX5nBU</recordid><startdate>20140301</startdate><enddate>20140301</enddate><creator>de Oliveira, Leonardo W.</creator><creator>de Oliveira, Edimar J.</creator><creator>Gomes, Flávio V.</creator><creator>Silva, Ivo C.</creator><creator>Marcato, André L.M.</creator><creator>Resende, Paulo V.C.</creator><general>Elsevier Ltd</general><general>Elsevier</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>8FD</scope><scope>FR3</scope><scope>KR7</scope><scope>L7M</scope></search><sort><creationdate>20140301</creationdate><title>Artificial Immune Systems applied to the reconfiguration of electrical power distribution networks for energy loss minimization</title><author>de Oliveira, Leonardo W. ; de Oliveira, Edimar J. ; Gomes, Flávio V. ; Silva, Ivo C. ; Marcato, André L.M. ; Resende, Paulo V.C.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c369t-6170b24f5d4ef185dcf6e54d144ba7aef77e8f6e8234e96b0e4b8ecf8c385bb3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Algorithms</topic><topic>Applied sciences</topic><topic>Artificial Immune System</topic><topic>Artificial intelligence</topic><topic>Combinatorial analysis</topic><topic>Distribution system</topic><topic>Electrical engineering. Electrical power engineering</topic><topic>Electrical power engineering</topic><topic>Energy conservation</topic><topic>Energy distribution</topic><topic>Energy loss</topic><topic>Exact sciences and technology</topic><topic>Miscellaneous</topic><topic>Mixed integer</topic><topic>Nonlinear programming</topic><topic>Power networks and lines</topic><topic>Reconfiguration</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>de Oliveira, Leonardo W.</creatorcontrib><creatorcontrib>de Oliveira, Edimar J.</creatorcontrib><creatorcontrib>Gomes, Flávio V.</creatorcontrib><creatorcontrib>Silva, Ivo C.</creatorcontrib><creatorcontrib>Marcato, André L.M.</creatorcontrib><creatorcontrib>Resende, Paulo V.C.</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Electronics & Communications 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>International journal of electrical power & energy systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>de Oliveira, Leonardo W.</au><au>de Oliveira, Edimar J.</au><au>Gomes, Flávio V.</au><au>Silva, Ivo C.</au><au>Marcato, André L.M.</au><au>Resende, Paulo V.C.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Artificial Immune Systems applied to the reconfiguration of electrical power distribution networks for energy loss minimization</atitle><jtitle>International journal of electrical power & energy systems</jtitle><date>2014-03-01</date><risdate>2014</risdate><volume>56</volume><spage>64</spage><epage>74</epage><pages>64-74</pages><issn>0142-0615</issn><eissn>1879-3517</eissn><coden>IEPSDC</coden><abstract>•The Artificial Immune System is proposed to reconfigure distribution networks.•The proposed approach seeks minimal energy loss through an improved algorithm.•The algorithm leads to good quality solutions with acceptable computation effort.•The proposed methodology meets the network radiality and connectivity constraints.•Different load levels from daily load curves and the voltage levels are considered.
This paper presents a methodology for the reconfiguration of radial electrical distribution systems based on the bio-inspired meta-heuristic Artificial Immune System to minimize energy losses. The proposed approach can handle this combinatorial mixed integer problem of nonlinear programming. Radiality and connectivity constraints are considered as well as different load levels for planning the system operation. For this purpose, improvements to an algorithm in the literature are proposed to better accommodate the features of the problem and to improve the search process. The algorithm developed is tested in well-known distribution systems.</abstract><cop>Oxford</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.ijepes.2013.11.008</doi><tpages>11</tpages></addata></record> |
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| ispartof | International journal of electrical power & energy systems, 2014-03, Vol.56, p.64-74 |
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| language | eng |
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| source | Elsevier ScienceDirect Journals |
| subjects | Algorithms Applied sciences Artificial Immune System Artificial intelligence Combinatorial analysis Distribution system Electrical engineering. Electrical power engineering Electrical power engineering Energy conservation Energy distribution Energy loss Exact sciences and technology Miscellaneous Mixed integer Nonlinear programming Power networks and lines Reconfiguration |
| title | Artificial Immune Systems applied to the reconfiguration of electrical power distribution networks for energy loss minimization |
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