Adaptive virtual-inertia control and chicken swarm optimizer for frequency stability in power-grids penetrated by renewable energy sources
In this article, a control scheme based on chicken swarm optimizer (CSO) in cooperation with adaptive virtual-inertia control (AVIC) is investigated. The proposed control scheme aims at improving the frequency stability of an interconnected power system which is penetrated by renewable energy source...
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Veröffentlicht in: | Neural computing & applications 2021-04, Vol.33 (7), p.2905-2918 |
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description | In this article, a control scheme based on chicken swarm optimizer (CSO) in cooperation with adaptive virtual-inertia control (AVIC) is investigated. The proposed control scheme aims at improving the frequency stability of an interconnected power system which is penetrated by renewable energy sources. The CSO is applied to produce the best values of the gains of the adapted standard proportional-integral-derivative (PID) controllers and required parameters of AVICs. Various scenarios are addressed in this study such as applications of sudden step load disturbances and severe variations in the inertia of the system. In addition, realistic conditions such as uncertainties of tidal power source and random load disturbances are demonstrated. Compulsory assessments with subsequent discussions to evaluate the results of the CSO are made. The proposed CSO–AVIC based control method is verified by comparisons with well-matured interesting algorithms such as differential evolution and particle swarm optimizers. Various quality specifications of the dynamic responses and the demonstrated results indicate clearly the viability of the proposed CSO–AVIC based on control scheme. It can be emphasized that the utilization of AVIC along with PID controllers are significantly improved the system dynamic performances and their dynamic response specifications meet the terms of standard acceptable criteria’s. |
doi_str_mv | 10.1007/s00521-020-05054-8 |
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The proposed control scheme aims at improving the frequency stability of an interconnected power system which is penetrated by renewable energy sources. The CSO is applied to produce the best values of the gains of the adapted standard proportional-integral-derivative (PID) controllers and required parameters of AVICs. Various scenarios are addressed in this study such as applications of sudden step load disturbances and severe variations in the inertia of the system. In addition, realistic conditions such as uncertainties of tidal power source and random load disturbances are demonstrated. Compulsory assessments with subsequent discussions to evaluate the results of the CSO are made. The proposed CSO–AVIC based control method is verified by comparisons with well-matured interesting algorithms such as differential evolution and particle swarm optimizers. Various quality specifications of the dynamic responses and the demonstrated results indicate clearly the viability of the proposed CSO–AVIC based on control scheme. 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The proposed control scheme aims at improving the frequency stability of an interconnected power system which is penetrated by renewable energy sources. The CSO is applied to produce the best values of the gains of the adapted standard proportional-integral-derivative (PID) controllers and required parameters of AVICs. Various scenarios are addressed in this study such as applications of sudden step load disturbances and severe variations in the inertia of the system. In addition, realistic conditions such as uncertainties of tidal power source and random load disturbances are demonstrated. Compulsory assessments with subsequent discussions to evaluate the results of the CSO are made. The proposed CSO–AVIC based control method is verified by comparisons with well-matured interesting algorithms such as differential evolution and particle swarm optimizers. Various quality specifications of the dynamic responses and the demonstrated results indicate clearly the viability of the proposed CSO–AVIC based on control scheme. It can be emphasized that the utilization of AVIC along with PID controllers are significantly improved the system dynamic performances and their dynamic response specifications meet the terms of standard acceptable criteria’s.</description><subject>Adaptive control</subject><subject>Alternative energy sources</subject><subject>Artificial Intelligence</subject><subject>Chickens</subject><subject>Computational Biology/Bioinformatics</subject><subject>Computational Science and Engineering</subject><subject>Computer Science</subject><subject>Control methods</subject><subject>Control stability</subject><subject>Controllers</subject><subject>Data Mining and Knowledge Discovery</subject><subject>Dynamic response</subject><subject>Energy resources</subject><subject>Evolutionary algorithms</subject><subject>Evolutionary computation</subject><subject>Frequency stability</subject><subject>Image Processing and Computer Vision</subject><subject>Inertia</subject><subject>Original Article</subject><subject>Probability and Statistics in Computer Science</subject><subject>Proportional integral derivative</subject><subject>Random loads</subject><subject>Renewable energy sources</subject><subject>Renewable resources</subject><subject>Specifications</subject><subject>Tidal energy</subject><subject>Tidal power</subject><issn>0941-0643</issn><issn>1433-3058</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNp9kM9qHDEMxk1IINs0L9CToWc38ng8f45hadPCQi7p2Xg88sbprGcqe7NsHiFPXTdb6C0HIQl9P0l8jH2S8EUCtDcJQFdSQAUCNOhadGdsJWulhALdnbMV9HUZN7W6ZB9SegKAuun0ir3ejnbJ4Rn5c6C8t5MIESkHy90cM80Tt3Hk7jG4Xxh5Olja8bkAu_CCxP1cgvD3HqM78pTtEKaQjzxEvswHJLGlMCa-YMRMNuPIhyOn0h3sMCEvBW0LN-_JYfrILrydEl7_y1fs57evD-vvYnN_92N9uxFO6S4L9L5Hbz162Q-17ZXCtvNONU0LtkepW1Cl67B2oKSzo9ddg7YdFLSo6kZdsc-nvQvN5fOUzVN5IJaTptJQad23siqq6qRyNKdE6M1CYWfpaCSYv56bk-emeG7ePDddgdQJSkUct0j_V79D_QF7D4iG</recordid><startdate>20210401</startdate><enddate>20210401</enddate><creator>Othman, Ahmed M.</creator><creator>El-Fergany, Attia A.</creator><general>Springer London</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>P5Z</scope><scope>P62</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><orcidid>https://orcid.org/0000-0003-3476-1361</orcidid></search><sort><creationdate>20210401</creationdate><title>Adaptive virtual-inertia control and chicken swarm optimizer for frequency stability in power-grids penetrated by renewable energy sources</title><author>Othman, Ahmed M. ; El-Fergany, Attia A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c358t-eff9efafef19b4a933e78fc36670a9e15703c368e4c031cadf586ea7b307e3463</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Adaptive control</topic><topic>Alternative energy sources</topic><topic>Artificial Intelligence</topic><topic>Chickens</topic><topic>Computational Biology/Bioinformatics</topic><topic>Computational Science and Engineering</topic><topic>Computer Science</topic><topic>Control methods</topic><topic>Control stability</topic><topic>Controllers</topic><topic>Data Mining and Knowledge Discovery</topic><topic>Dynamic response</topic><topic>Energy resources</topic><topic>Evolutionary algorithms</topic><topic>Evolutionary computation</topic><topic>Frequency stability</topic><topic>Image Processing and Computer Vision</topic><topic>Inertia</topic><topic>Original Article</topic><topic>Probability and Statistics in Computer Science</topic><topic>Proportional integral derivative</topic><topic>Random loads</topic><topic>Renewable energy sources</topic><topic>Renewable resources</topic><topic>Specifications</topic><topic>Tidal energy</topic><topic>Tidal power</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Othman, Ahmed M.</creatorcontrib><creatorcontrib>El-Fergany, Attia A.</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>Othman, Ahmed M.</au><au>El-Fergany, Attia A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Adaptive virtual-inertia control and chicken swarm optimizer for frequency stability in power-grids penetrated by renewable energy sources</atitle><jtitle>Neural computing & applications</jtitle><stitle>Neural Comput & Applic</stitle><date>2021-04-01</date><risdate>2021</risdate><volume>33</volume><issue>7</issue><spage>2905</spage><epage>2918</epage><pages>2905-2918</pages><issn>0941-0643</issn><eissn>1433-3058</eissn><abstract>In this article, a control scheme based on chicken swarm optimizer (CSO) in cooperation with adaptive virtual-inertia control (AVIC) is investigated. The proposed control scheme aims at improving the frequency stability of an interconnected power system which is penetrated by renewable energy sources. The CSO is applied to produce the best values of the gains of the adapted standard proportional-integral-derivative (PID) controllers and required parameters of AVICs. Various scenarios are addressed in this study such as applications of sudden step load disturbances and severe variations in the inertia of the system. In addition, realistic conditions such as uncertainties of tidal power source and random load disturbances are demonstrated. Compulsory assessments with subsequent discussions to evaluate the results of the CSO are made. The proposed CSO–AVIC based control method is verified by comparisons with well-matured interesting algorithms such as differential evolution and particle swarm optimizers. Various quality specifications of the dynamic responses and the demonstrated results indicate clearly the viability of the proposed CSO–AVIC based on control scheme. It can be emphasized that the utilization of AVIC along with PID controllers are significantly improved the system dynamic performances and their dynamic response specifications meet the terms of standard acceptable criteria’s.</abstract><cop>London</cop><pub>Springer London</pub><doi>10.1007/s00521-020-05054-8</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0003-3476-1361</orcidid></addata></record> |
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subjects | Adaptive control Alternative energy sources Artificial Intelligence Chickens Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Control methods Control stability Controllers Data Mining and Knowledge Discovery Dynamic response Energy resources Evolutionary algorithms Evolutionary computation Frequency stability Image Processing and Computer Vision Inertia Original Article Probability and Statistics in Computer Science Proportional integral derivative Random loads Renewable energy sources Renewable resources Specifications Tidal energy Tidal power |
title | Adaptive virtual-inertia control and chicken swarm optimizer for frequency stability in power-grids penetrated by renewable energy sources |
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