(1 + PD)-PID cascade controller design for performance betterment of load frequency control in diverse electric power systems
In our world of today developing incredibly fast, load frequency control (LFC) is an indispensable and vital element in increasing the standard of living of a country by providing a good quality of electric power. To this end, rapid and notable development has been recorded in LFC area. However, res...
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description | In our world of today developing incredibly fast, load frequency control (LFC) is an indispensable and vital element in increasing the standard of living of a country by providing a good quality of electric power. To this end, rapid and notable development has been recorded in LFC area. However, researchers worldwide need for the existence of not only effective but also computationally inexpensive control algorithm considering the limitations and difficulties in practice. Hence, this paper deals with the introduction of (1 + PD)-PID cascade controller to the relevant field. The controller is simple to implement and it connects the output of 1 + PD controller with the input of PID controller where the frequency and tie-line power deviation are applied to the latter controller as feedback signals also, which is the first attempt made in the literature. To discover the most optimistic results, controller gains are tuned concurrently by dragonfly search algorithm (DSA). For the certification purpose of the advocated approach, two-area thermal system with/without governor dead band nonlinearity is considered as test systems initially. Then single/multi-area multi-source power systems with/without a HVDC link are employed for the enriched validation purpose. The results of our proposal are analyzed in comparison with those of other prevalent works, which unveil that despite its simplicity, DSA optimized (1 + PD)-PID cascade strategy delivers better performance than others in terms of smaller values of the chosen objective function and settling time/undershoot/overshoot of the frequency and tie-line power deviations following a step load perturbation. |
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To this end, rapid and notable development has been recorded in LFC area. However, researchers worldwide need for the existence of not only effective but also computationally inexpensive control algorithm considering the limitations and difficulties in practice. Hence, this paper deals with the introduction of (1 + PD)-PID cascade controller to the relevant field. The controller is simple to implement and it connects the output of 1 + PD controller with the input of PID controller where the frequency and tie-line power deviation are applied to the latter controller as feedback signals also, which is the first attempt made in the literature. To discover the most optimistic results, controller gains are tuned concurrently by dragonfly search algorithm (DSA). For the certification purpose of the advocated approach, two-area thermal system with/without governor dead band nonlinearity is considered as test systems initially. Then single/multi-area multi-source power systems with/without a HVDC link are employed for the enriched validation purpose. The results of our proposal are analyzed in comparison with those of other prevalent works, which unveil that despite its simplicity, DSA optimized (1 + PD)-PID cascade strategy delivers better performance than others in terms of smaller values of the chosen objective function and settling time/undershoot/overshoot of the frequency and tie-line power deviations following a step load perturbation.</description><identifier>ISSN: 0941-0643</identifier><identifier>EISSN: 1433-3058</identifier><identifier>DOI: 10.1007/s00521-021-06168-3</identifier><language>eng</language><publisher>London: Springer London</publisher><subject>Artificial Intelligence ; Computational Biology/Bioinformatics ; Computational Science and Engineering ; Computer Science ; Control algorithms ; Control systems design ; Control theory ; Controllers ; Data Mining and Knowledge Discovery ; Deviation ; Electric power ; Electric power systems ; Electrical loads ; Frequency control ; Image Processing and Computer Vision ; Original Article ; Perturbation ; Probability and Statistics in Computer Science ; Proportional integral derivative ; Search algorithms</subject><ispartof>Neural computing & applications, 2021-11, Vol.33 (22), p.15433-15456</ispartof><rights>The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2021</rights><rights>The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2021.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c319t-2fb9de5993cb2a4a9c9756fd557104b28726576d265ebada883eb430153462113</citedby><cites>FETCH-LOGICAL-c319t-2fb9de5993cb2a4a9c9756fd557104b28726576d265ebada883eb430153462113</cites><orcidid>0000-0002-2961-0035</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00521-021-06168-3$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00521-021-06168-3$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids></links><search><creatorcontrib>Çelik, Emre</creatorcontrib><creatorcontrib>Öztürk, Nihat</creatorcontrib><creatorcontrib>Arya, Yogendra</creatorcontrib><creatorcontrib>Ocak, Cemil</creatorcontrib><title>(1 + PD)-PID cascade controller design for performance betterment of load frequency control in diverse electric power systems</title><title>Neural computing & applications</title><addtitle>Neural Comput & Applic</addtitle><description>In our world of today developing incredibly fast, load frequency control (LFC) is an indispensable and vital element in increasing the standard of living of a country by providing a good quality of electric power. To this end, rapid and notable development has been recorded in LFC area. However, researchers worldwide need for the existence of not only effective but also computationally inexpensive control algorithm considering the limitations and difficulties in practice. Hence, this paper deals with the introduction of (1 + PD)-PID cascade controller to the relevant field. The controller is simple to implement and it connects the output of 1 + PD controller with the input of PID controller where the frequency and tie-line power deviation are applied to the latter controller as feedback signals also, which is the first attempt made in the literature. To discover the most optimistic results, controller gains are tuned concurrently by dragonfly search algorithm (DSA). For the certification purpose of the advocated approach, two-area thermal system with/without governor dead band nonlinearity is considered as test systems initially. Then single/multi-area multi-source power systems with/without a HVDC link are employed for the enriched validation purpose. The results of our proposal are analyzed in comparison with those of other prevalent works, which unveil that despite its simplicity, DSA optimized (1 + PD)-PID cascade strategy delivers better performance than others in terms of smaller values of the chosen objective function and settling time/undershoot/overshoot of the frequency and tie-line power deviations following a step load perturbation.</description><subject>Artificial Intelligence</subject><subject>Computational Biology/Bioinformatics</subject><subject>Computational Science and Engineering</subject><subject>Computer Science</subject><subject>Control algorithms</subject><subject>Control systems design</subject><subject>Control theory</subject><subject>Controllers</subject><subject>Data Mining and Knowledge Discovery</subject><subject>Deviation</subject><subject>Electric power</subject><subject>Electric power systems</subject><subject>Electrical loads</subject><subject>Frequency control</subject><subject>Image Processing and Computer Vision</subject><subject>Original Article</subject><subject>Perturbation</subject><subject>Probability and Statistics in Computer Science</subject><subject>Proportional integral derivative</subject><subject>Search algorithms</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>eNp9UMtOwzAQtBBIlMIPcLLEBYQCfuZxRC2PSpXoAc6R42yqVIkd7BTUGxz5Tb4ERwFx4zA7h52ZXQ1Cp5RcUUKSa0-IZDQiA2IapxHfQxMqOI84kek-mpBMDCvBD9GR9xtCiIhTOUEf5_Tr_fMyYDW_iFaLOdbKa1UC1tb0zjYNOFyCr9cGV9bhDlygVhkNuIC-B9eC6bGtcGNViSsHL1swevdrx7XBZf0KzgOGBnTvao07-xZS_c730PpjdFCpxsPJD0_R893t0-whWj7eL2Y3y0hzmvURq4qsBJllXBdMCZXpLJFxVUqZUCIKliYslklchgmFKlWacigEJ1RyETNK-RSdjbmds-FH3-cbu3UmnMyZTCXjTAgWVGxUaWe9d1Dlnatb5XY5JflQdT5WnZMBQ9U5DyY-mnwQmzW4v-h_XN-M_IN3</recordid><startdate>20211101</startdate><enddate>20211101</enddate><creator>Çelik, Emre</creator><creator>Öztürk, Nihat</creator><creator>Arya, Yogendra</creator><creator>Ocak, Cemil</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/0000-0002-2961-0035</orcidid></search><sort><creationdate>20211101</creationdate><title>(1 + PD)-PID cascade controller design for performance betterment of load frequency control in diverse electric power systems</title><author>Çelik, Emre ; Öztürk, Nihat ; Arya, Yogendra ; Ocak, Cemil</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c319t-2fb9de5993cb2a4a9c9756fd557104b28726576d265ebada883eb430153462113</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Artificial Intelligence</topic><topic>Computational Biology/Bioinformatics</topic><topic>Computational Science and Engineering</topic><topic>Computer Science</topic><topic>Control algorithms</topic><topic>Control systems design</topic><topic>Control theory</topic><topic>Controllers</topic><topic>Data Mining and Knowledge Discovery</topic><topic>Deviation</topic><topic>Electric power</topic><topic>Electric power systems</topic><topic>Electrical loads</topic><topic>Frequency control</topic><topic>Image Processing and Computer Vision</topic><topic>Original Article</topic><topic>Perturbation</topic><topic>Probability and Statistics in Computer Science</topic><topic>Proportional integral derivative</topic><topic>Search algorithms</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Çelik, Emre</creatorcontrib><creatorcontrib>Öztürk, Nihat</creatorcontrib><creatorcontrib>Arya, Yogendra</creatorcontrib><creatorcontrib>Ocak, Cemil</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>Çelik, Emre</au><au>Öztürk, Nihat</au><au>Arya, Yogendra</au><au>Ocak, Cemil</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>(1 + PD)-PID cascade controller design for performance betterment of load frequency control in diverse electric power systems</atitle><jtitle>Neural computing & applications</jtitle><stitle>Neural Comput & Applic</stitle><date>2021-11-01</date><risdate>2021</risdate><volume>33</volume><issue>22</issue><spage>15433</spage><epage>15456</epage><pages>15433-15456</pages><issn>0941-0643</issn><eissn>1433-3058</eissn><abstract>In our world of today developing incredibly fast, load frequency control (LFC) is an indispensable and vital element in increasing the standard of living of a country by providing a good quality of electric power. To this end, rapid and notable development has been recorded in LFC area. However, researchers worldwide need for the existence of not only effective but also computationally inexpensive control algorithm considering the limitations and difficulties in practice. Hence, this paper deals with the introduction of (1 + PD)-PID cascade controller to the relevant field. The controller is simple to implement and it connects the output of 1 + PD controller with the input of PID controller where the frequency and tie-line power deviation are applied to the latter controller as feedback signals also, which is the first attempt made in the literature. To discover the most optimistic results, controller gains are tuned concurrently by dragonfly search algorithm (DSA). For the certification purpose of the advocated approach, two-area thermal system with/without governor dead band nonlinearity is considered as test systems initially. Then single/multi-area multi-source power systems with/without a HVDC link are employed for the enriched validation purpose. The results of our proposal are analyzed in comparison with those of other prevalent works, which unveil that despite its simplicity, DSA optimized (1 + PD)-PID cascade strategy delivers better performance than others in terms of smaller values of the chosen objective function and settling time/undershoot/overshoot of the frequency and tie-line power deviations following a step load perturbation.</abstract><cop>London</cop><pub>Springer London</pub><doi>10.1007/s00521-021-06168-3</doi><tpages>24</tpages><orcidid>https://orcid.org/0000-0002-2961-0035</orcidid></addata></record> |
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subjects | Artificial Intelligence Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Control algorithms Control systems design Control theory Controllers Data Mining and Knowledge Discovery Deviation Electric power Electric power systems Electrical loads Frequency control Image Processing and Computer Vision Original Article Perturbation Probability and Statistics in Computer Science Proportional integral derivative Search algorithms |
title | (1 + PD)-PID cascade controller design for performance betterment of load frequency control in diverse electric power systems |
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