Design of fractional swarming strategy for solution of optimal reactive power dispatch
Optimal reactive power dispatch (RPD) for reducing the real power losses of the transmission system is one of the paramount concerns for the research community to investigate the efficiency of power systems. In this paper, strength of meta-heuristic computing paradigm based on fractional-order Darwi...
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| Veröffentlicht in: | Neural computing & applications 2020-07, Vol.32 (14), p.10501-10518 |
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| creator | Muhammad, Yasir Khan, Rahimdad Ullah, Farman Rehman, Ata ur Aslam, Muhammad Saeed Raja, Muhammad Asif Zahoor |
| description | Optimal reactive power dispatch (RPD) for reducing the real power losses of the transmission system is one of the paramount concerns for the research community to investigate the efficiency of power systems. In this paper, strength of meta-heuristic computing paradigm based on fractional-order Darwinian particle swarm optimization (FO-DPSO) is exploited for optimization of RPD problems in energy sector. The fitness functions including line loss minimization and voltage deviation (voltage profile index) are constructed to find the optimal reactive power flow for IEEE 30- and 57-bus test systems. The rich heritage of fractional evolutionary computing through variants of FO-DPSO is applied to minimization problem of optimal power flow by determination of control variables in terms of VAR compensators, bus voltages and transformer tap settings. Comparison of the results shows that fractional swarming intelligence outperformed the state-of-the-art counterparts by means of both line loss minimization and voltage deviation. Superiority of the proposed scheme is also validated for different degrees of freedom in the optimal RPD problems. |
| doi_str_mv | 10.1007/s00521-019-04589-9 |
| format | Article |
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In this paper, strength of meta-heuristic computing paradigm based on fractional-order Darwinian particle swarm optimization (FO-DPSO) is exploited for optimization of RPD problems in energy sector. The fitness functions including line loss minimization and voltage deviation (voltage profile index) are constructed to find the optimal reactive power flow for IEEE 30- and 57-bus test systems. The rich heritage of fractional evolutionary computing through variants of FO-DPSO is applied to minimization problem of optimal power flow by determination of control variables in terms of VAR compensators, bus voltages and transformer tap settings. Comparison of the results shows that fractional swarming intelligence outperformed the state-of-the-art counterparts by means of both line loss minimization and voltage deviation. 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Khan, Rahimdad ; Ullah, Farman ; Rehman, Ata ur ; Aslam, Muhammad Saeed ; Raja, Muhammad Asif Zahoor</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c372t-8d7ed1ba85f4822d7b0351fde8f8b6c58ccf13127d17e437ab8b0b286e9f5a673</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Artificial Intelligence</topic><topic>Compensators</topic><topic>Computation</topic><topic>Computational Biology/Bioinformatics</topic><topic>Computational Science and Engineering</topic><topic>Computer Science</topic><topic>Data Mining and Knowledge Discovery</topic><topic>Deviation</topic><topic>Electric potential</topic><topic>Energy conservation</topic><topic>Evolutionary algorithms</topic><topic>Heuristic methods</topic><topic>Image Processing and Computer Vision</topic><topic>Original Article</topic><topic>Particle swarm optimization</topic><topic>Power dispatch</topic><topic>Power flow</topic><topic>Power loss</topic><topic>Probability and Statistics in Computer Science</topic><topic>Reactive power</topic><topic>Swarm intelligence</topic><topic>Swarming</topic><topic>Voltage</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Muhammad, Yasir</creatorcontrib><creatorcontrib>Khan, Rahimdad</creatorcontrib><creatorcontrib>Ullah, Farman</creatorcontrib><creatorcontrib>Rehman, Ata ur</creatorcontrib><creatorcontrib>Aslam, Muhammad Saeed</creatorcontrib><creatorcontrib>Raja, Muhammad Asif Zahoor</creatorcontrib><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><jtitle>Neural computing & applications</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Muhammad, Yasir</au><au>Khan, Rahimdad</au><au>Ullah, Farman</au><au>Rehman, Ata ur</au><au>Aslam, Muhammad Saeed</au><au>Raja, Muhammad Asif Zahoor</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Design of fractional swarming strategy for solution of optimal reactive power dispatch</atitle><jtitle>Neural computing & applications</jtitle><stitle>Neural Comput & Applic</stitle><date>2020-07-01</date><risdate>2020</risdate><volume>32</volume><issue>14</issue><spage>10501</spage><epage>10518</epage><pages>10501-10518</pages><issn>0941-0643</issn><eissn>1433-3058</eissn><abstract>Optimal reactive power dispatch (RPD) for reducing the real power losses of the transmission system is one of the paramount concerns for the research community to investigate the efficiency of power systems. In this paper, strength of meta-heuristic computing paradigm based on fractional-order Darwinian particle swarm optimization (FO-DPSO) is exploited for optimization of RPD problems in energy sector. The fitness functions including line loss minimization and voltage deviation (voltage profile index) are constructed to find the optimal reactive power flow for IEEE 30- and 57-bus test systems. The rich heritage of fractional evolutionary computing through variants of FO-DPSO is applied to minimization problem of optimal power flow by determination of control variables in terms of VAR compensators, bus voltages and transformer tap settings. Comparison of the results shows that fractional swarming intelligence outperformed the state-of-the-art counterparts by means of both line loss minimization and voltage deviation. Superiority of the proposed scheme is also validated for different degrees of freedom in the optimal RPD problems.</abstract><cop>London</cop><pub>Springer London</pub><doi>10.1007/s00521-019-04589-9</doi><tpages>18</tpages><orcidid>https://orcid.org/0000-0001-6219-4910</orcidid></addata></record> |
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| subjects | Artificial Intelligence Compensators Computation Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Data Mining and Knowledge Discovery Deviation Electric potential Energy conservation Evolutionary algorithms Heuristic methods Image Processing and Computer Vision Original Article Particle swarm optimization Power dispatch Power flow Power loss Probability and Statistics in Computer Science Reactive power Swarm intelligence Swarming Voltage |
| title | Design of fractional swarming strategy for solution of optimal reactive power dispatch |
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