Multi objective comparison of GA and LP techniques for generator reactive power optimization
Optimization of Generator output tends to increase the supply capability of generators at different voltage disturbances. The Genetic Algorithm (GA) approach is used in this paper to optimize the effect on the generator reactive power. The three control parameters used are: Generator voltages, Switc...
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| creator | Rayudu, K. Jayalaxmi, A. Yesuratnam, G. Kumar, Y. D. |
| description | Optimization of Generator output tends to increase the supply capability of generators at different voltage disturbances. The Genetic Algorithm (GA) approach is used in this paper to optimize the effect on the generator reactive power. The three control parameters used are: Generator voltages, Switchable VAR Compensators (SVC) and On Load Transformer tap Changers (OLTC). The proposed technique is tested with IEEE-24 bus system. A case study is done on all optimization variables (control parameters) and effect on generator reactive power output is analyzed. The results are compared with conventional Linear Programming (LP) Technique. The comparison clearly says GA approach performs better in optimization of generator VAR output requirement and also increases voltage stability by loss reduction. |
| doi_str_mv | 10.1109/PowerI.2012.6479585 |
| format | Conference Proceeding |
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D.</creator><creatorcontrib>Rayudu, K. ; Jayalaxmi, A. ; Yesuratnam, G. ; Kumar, Y. D.</creatorcontrib><description>Optimization of Generator output tends to increase the supply capability of generators at different voltage disturbances. The Genetic Algorithm (GA) approach is used in this paper to optimize the effect on the generator reactive power. The three control parameters used are: Generator voltages, Switchable VAR Compensators (SVC) and On Load Transformer tap Changers (OLTC). The proposed technique is tested with IEEE-24 bus system. A case study is done on all optimization variables (control parameters) and effect on generator reactive power output is analyzed. The results are compared with conventional Linear Programming (LP) Technique. 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The comparison clearly says GA approach performs better in optimization of generator VAR output requirement and also increases voltage stability by loss reduction.</description><subject>Generator Reactive power</subject><subject>Generators</subject><subject>Genetic algorithm</subject><subject>Genetic algorithms</subject><subject>Linear programming</subject><subject>Natural selection</subject><subject>Optimization</subject><subject>Power loss</subject><subject>Power system stability</subject><subject>Reactive power</subject><subject>Stability analysis</subject><subject>Voltage stability</subject><isbn>1467307637</isbn><isbn>9781467307635</isbn><isbn>9781467307659</isbn><isbn>1467307661</isbn><isbn>9781467307666</isbn><isbn>1467307653</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2012</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo1kM9OAjEYxGuMiYo8AZe-ANg_2_brkRBFEowc9GZCut2vWgLbtVs0-vRiwNPMHH6TyRAy4mzCObO3q_SFeTERjIuJroxVoM7I0BrglTaSGa3sObn-D9JckmHfbxhjB1oD6Cvy-rjflkhTvUFf4idSn3ady7FPLU2BzqfUtQ1drmhB_97Gjz32NKRM37DF7MrBZXRHsvsbQ1NX4i7-uBJTe0Mugtv2ODzpgLzc3z3PHsbLp_liNl2OIzeqjAVIEaQXwcrGWge1AGic8poDMCFrqBAqg04ojd4pwzjUrmmY88EHUCgHZHTsjYi47nLcufy9Ph0ifwF7ulbE</recordid><startdate>201212</startdate><enddate>201212</enddate><creator>Rayudu, K.</creator><creator>Jayalaxmi, A.</creator><creator>Yesuratnam, G.</creator><creator>Kumar, Y. D.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201212</creationdate><title>Multi objective comparison of GA and LP techniques for generator reactive power optimization</title><author>Rayudu, K. ; Jayalaxmi, A. ; Yesuratnam, G. ; Kumar, Y. D.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-2832f3c2f93d99a8b288da5c6188023b84e847ea256eca57018badd0acfcf85e3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Generator Reactive power</topic><topic>Generators</topic><topic>Genetic algorithm</topic><topic>Genetic algorithms</topic><topic>Linear programming</topic><topic>Natural selection</topic><topic>Optimization</topic><topic>Power loss</topic><topic>Power system stability</topic><topic>Reactive power</topic><topic>Stability analysis</topic><topic>Voltage stability</topic><toplevel>online_resources</toplevel><creatorcontrib>Rayudu, K.</creatorcontrib><creatorcontrib>Jayalaxmi, A.</creatorcontrib><creatorcontrib>Yesuratnam, G.</creatorcontrib><creatorcontrib>Kumar, Y. D.</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></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Rayudu, K.</au><au>Jayalaxmi, A.</au><au>Yesuratnam, G.</au><au>Kumar, Y. D.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Multi objective comparison of GA and LP techniques for generator reactive power optimization</atitle><btitle>2012 IEEE Fifth Power India Conference</btitle><stitle>PowerI</stitle><date>2012-12</date><risdate>2012</risdate><spage>1</spage><epage>5</epage><pages>1-5</pages><isbn>1467307637</isbn><isbn>9781467307635</isbn><eisbn>9781467307659</eisbn><eisbn>1467307661</eisbn><eisbn>9781467307666</eisbn><eisbn>1467307653</eisbn><abstract>Optimization of Generator output tends to increase the supply capability of generators at different voltage disturbances. The Genetic Algorithm (GA) approach is used in this paper to optimize the effect on the generator reactive power. The three control parameters used are: Generator voltages, Switchable VAR Compensators (SVC) and On Load Transformer tap Changers (OLTC). The proposed technique is tested with IEEE-24 bus system. A case study is done on all optimization variables (control parameters) and effect on generator reactive power output is analyzed. The results are compared with conventional Linear Programming (LP) Technique. The comparison clearly says GA approach performs better in optimization of generator VAR output requirement and also increases voltage stability by loss reduction.</abstract><pub>IEEE</pub><doi>10.1109/PowerI.2012.6479585</doi><tpages>5</tpages></addata></record> |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Generator Reactive power Generators Genetic algorithm Genetic algorithms Linear programming Natural selection Optimization Power loss Power system stability Reactive power Stability analysis Voltage stability |
| title | Multi objective comparison of GA and LP techniques for generator reactive power optimization |
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