Simultaneous allocation of distributed resources using improved teaching learning based optimization
•Simultaneous allocation of distributed energy resources in distribution networks.•Annual energy loss reduction is optimized using a multi-level load profile.•A new penalty factor approach is suggested to check node voltage deviations.•An improved TLBO is proposed by suggesting several modifications...
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Veröffentlicht in: | Energy conversion and management 2015-10, Vol.103, p.387-400 |
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creator | Kanwar, Neeraj Gupta, Nikhil Niazi, K.R. Swarnkar, Anil |
description | •Simultaneous allocation of distributed energy resources in distribution networks.•Annual energy loss reduction is optimized using a multi-level load profile.•A new penalty factor approach is suggested to check node voltage deviations.•An improved TLBO is proposed by suggesting several modifications in standard TLBO.•An intelligent search is proposed to enhance the performance of solution technique.
Active and reactive power flow in distribution networks can be effectively controlled by optimally placing distributed resources like shunt capacitors and distributed generators. This paper presents improved variant of Teaching Learning Based Optimization (TLBO) to efficiently and effectively deal with the problem of simultaneous allocation of these distributed resources in radial distribution networks while considering multi-level load scenario. Several algorithm specific modifications are suggested in the standard form of TLBO to cope against the intrinsic flaws of this technique. In addition, an intelligent search approach is proposed to restrict the problem search space without loss of diversity. This enhances the overall performance of the proposed method. The proposed method is investigated on IEEE 33-bus, 69-bus and 83-bus test distribution systems showing promising results. |
doi_str_mv | 10.1016/j.enconman.2015.06.057 |
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Active and reactive power flow in distribution networks can be effectively controlled by optimally placing distributed resources like shunt capacitors and distributed generators. This paper presents improved variant of Teaching Learning Based Optimization (TLBO) to efficiently and effectively deal with the problem of simultaneous allocation of these distributed resources in radial distribution networks while considering multi-level load scenario. Several algorithm specific modifications are suggested in the standard form of TLBO to cope against the intrinsic flaws of this technique. In addition, an intelligent search approach is proposed to restrict the problem search space without loss of diversity. This enhances the overall performance of the proposed method. The proposed method is investigated on IEEE 33-bus, 69-bus and 83-bus test distribution systems showing promising results.</description><identifier>ISSN: 0196-8904</identifier><identifier>EISSN: 1879-2227</identifier><identifier>DOI: 10.1016/j.enconman.2015.06.057</identifier><language>eng</language><publisher>Elsevier Ltd</publisher><subject>Algorithms ; Allocations ; Distributed resources ; Education ; Intelligent search ; Learning ; Meta-heuristic technique ; Networks ; Optimization ; Searching ; Smart distribution systems ; Teaching ; Teaching learning based optimization</subject><ispartof>Energy conversion and management, 2015-10, Vol.103, p.387-400</ispartof><rights>2015 Elsevier Ltd</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c345t-e9590c3da52dad464ffe856ae13ee8dfd22625a978567ee0b7a3bc9e714e934d3</citedby><cites>FETCH-LOGICAL-c345t-e9590c3da52dad464ffe856ae13ee8dfd22625a978567ee0b7a3bc9e714e934d3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.enconman.2015.06.057$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids></links><search><creatorcontrib>Kanwar, Neeraj</creatorcontrib><creatorcontrib>Gupta, Nikhil</creatorcontrib><creatorcontrib>Niazi, K.R.</creatorcontrib><creatorcontrib>Swarnkar, Anil</creatorcontrib><title>Simultaneous allocation of distributed resources using improved teaching learning based optimization</title><title>Energy conversion and management</title><description>•Simultaneous allocation of distributed energy resources in distribution networks.•Annual energy loss reduction is optimized using a multi-level load profile.•A new penalty factor approach is suggested to check node voltage deviations.•An improved TLBO is proposed by suggesting several modifications in standard TLBO.•An intelligent search is proposed to enhance the performance of solution technique.
Active and reactive power flow in distribution networks can be effectively controlled by optimally placing distributed resources like shunt capacitors and distributed generators. This paper presents improved variant of Teaching Learning Based Optimization (TLBO) to efficiently and effectively deal with the problem of simultaneous allocation of these distributed resources in radial distribution networks while considering multi-level load scenario. Several algorithm specific modifications are suggested in the standard form of TLBO to cope against the intrinsic flaws of this technique. In addition, an intelligent search approach is proposed to restrict the problem search space without loss of diversity. This enhances the overall performance of the proposed method. The proposed method is investigated on IEEE 33-bus, 69-bus and 83-bus test distribution systems showing promising results.</description><subject>Algorithms</subject><subject>Allocations</subject><subject>Distributed resources</subject><subject>Education</subject><subject>Intelligent search</subject><subject>Learning</subject><subject>Meta-heuristic technique</subject><subject>Networks</subject><subject>Optimization</subject><subject>Searching</subject><subject>Smart distribution systems</subject><subject>Teaching</subject><subject>Teaching learning based optimization</subject><issn>0196-8904</issn><issn>1879-2227</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><recordid>eNqFUE1PxCAUJEYT19W_YHr00gptgXLTbPxKTDyoZ0LhVdm0ZQW6if56qdWzp_cyb2byZhA6J7ggmLDLbQGjduOgxqLEhBaYFZjyA7QiDRd5WZb8EK0wESxvBK6P0UkIW4xxRTFbIfNsh6mPagQ3hUz1vdMqWjdmrsuMDdHbdopgMg_BTV5DyKZgx7fMDjvv9ukQQen3GelB-XFeWhUS7nbRDvbrx-wUHXWqD3D2O9fo9fbmZXOfPz7dPWyuH3Nd1TTmIKjAujKKlkaZmtVdBw1lCkgF0JjOlCUrqRI8gRwAt1xVrRbASQ2iqk21RheLb_rtY4IQ5WCDhr5f4knCaUotalwlKluo2rsQPHRy5-2g_KckWM61yq38q1XOtUrMZKo1Ca8WIaQgewteBm0TE4z1oKM0zv5n8Q2ILIgD</recordid><startdate>20151001</startdate><enddate>20151001</enddate><creator>Kanwar, Neeraj</creator><creator>Gupta, Nikhil</creator><creator>Niazi, K.R.</creator><creator>Swarnkar, Anil</creator><general>Elsevier Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>H8D</scope><scope>KR7</scope><scope>L7M</scope></search><sort><creationdate>20151001</creationdate><title>Simultaneous allocation of distributed resources using improved teaching learning based optimization</title><author>Kanwar, Neeraj ; Gupta, Nikhil ; Niazi, K.R. ; Swarnkar, Anil</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c345t-e9590c3da52dad464ffe856ae13ee8dfd22625a978567ee0b7a3bc9e714e934d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Algorithms</topic><topic>Allocations</topic><topic>Distributed resources</topic><topic>Education</topic><topic>Intelligent search</topic><topic>Learning</topic><topic>Meta-heuristic technique</topic><topic>Networks</topic><topic>Optimization</topic><topic>Searching</topic><topic>Smart distribution systems</topic><topic>Teaching</topic><topic>Teaching learning based optimization</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kanwar, Neeraj</creatorcontrib><creatorcontrib>Gupta, Nikhil</creatorcontrib><creatorcontrib>Niazi, K.R.</creatorcontrib><creatorcontrib>Swarnkar, Anil</creatorcontrib><collection>CrossRef</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Energy conversion and management</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kanwar, Neeraj</au><au>Gupta, Nikhil</au><au>Niazi, K.R.</au><au>Swarnkar, Anil</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Simultaneous allocation of distributed resources using improved teaching learning based optimization</atitle><jtitle>Energy conversion and management</jtitle><date>2015-10-01</date><risdate>2015</risdate><volume>103</volume><spage>387</spage><epage>400</epage><pages>387-400</pages><issn>0196-8904</issn><eissn>1879-2227</eissn><abstract>•Simultaneous allocation of distributed energy resources in distribution networks.•Annual energy loss reduction is optimized using a multi-level load profile.•A new penalty factor approach is suggested to check node voltage deviations.•An improved TLBO is proposed by suggesting several modifications in standard TLBO.•An intelligent search is proposed to enhance the performance of solution technique.
Active and reactive power flow in distribution networks can be effectively controlled by optimally placing distributed resources like shunt capacitors and distributed generators. This paper presents improved variant of Teaching Learning Based Optimization (TLBO) to efficiently and effectively deal with the problem of simultaneous allocation of these distributed resources in radial distribution networks while considering multi-level load scenario. Several algorithm specific modifications are suggested in the standard form of TLBO to cope against the intrinsic flaws of this technique. In addition, an intelligent search approach is proposed to restrict the problem search space without loss of diversity. This enhances the overall performance of the proposed method. The proposed method is investigated on IEEE 33-bus, 69-bus and 83-bus test distribution systems showing promising results.</abstract><pub>Elsevier Ltd</pub><doi>10.1016/j.enconman.2015.06.057</doi><tpages>14</tpages></addata></record> |
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subjects | Algorithms Allocations Distributed resources Education Intelligent search Learning Meta-heuristic technique Networks Optimization Searching Smart distribution systems Teaching Teaching learning based optimization |
title | Simultaneous allocation of distributed resources using improved teaching learning based optimization |
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