Quadratic Taylor Expansion-Based Approximate Dynamic Programming for Fully Decentralized AC-OPF of Multi-Area Power Systems
In this paper, a quadratic Taylor expansion-based approximate dynamic programming (QTE-ADP) algorithm is proposed for the decentralized solution of multi-area AC-optimal power flow (MA-ACOPF). Different from traditional ADP algorithms, the proposed algorithm does not need to approximate the value fu...
Gespeichert in:
| Veröffentlicht in: | IEEE transactions on power systems 2023-09, Vol.38 (5), p.4940-4949 |
|---|---|
| Hauptverfasser: | , , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 4949 |
|---|---|
| container_issue | 5 |
| container_start_page | 4940 |
| container_title | IEEE transactions on power systems |
| container_volume | 38 |
| creator | Ye, Hanfang Zhu, Jianquan Chen, Jiajun Wang, Zeshuang Zhuo, Yelin Liu, Haixin Liu, Mingbo |
| description | In this paper, a quadratic Taylor expansion-based approximate dynamic programming (QTE-ADP) algorithm is proposed for the decentralized solution of multi-area AC-optimal power flow (MA-ACOPF). Different from traditional ADP algorithms, the proposed algorithm does not need to approximate the value function via a given function structure, but directly obtains the quadratic Taylor expansion (QTE) of value function based on KKT conditions. Moreover, compared with the commonly used linearized value function approximation techniques, the information used to approximate the value function is also extended from first order to second order in the proposed algorithm, which helps to improve the accuracy and efficiency of ADP. When using QTE-ADP to solve the MA-ACOPF problem, only the boundary voltage information needs to be interchanged between adjacent areas, which facilitates preserving the information privacy and decision independence of each area. Numerical simulations on several test systems demonstrate that the proposed algorithm has good performance in terms of accuracy, efficiency, and adaptability. |
| doi_str_mv | 10.1109/TPWRS.2022.3217871 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_RIE</sourceid><recordid>TN_cdi_crossref_primary_10_1109_TPWRS_2022_3217871</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>9931986</ieee_id><sourcerecordid>2853023932</sourcerecordid><originalsourceid>FETCH-LOGICAL-c246t-e3fed347fdeae9ec3d36003b72caac435ba935fb344a0f4c8d731d40b8c1e1373</originalsourceid><addsrcrecordid>eNo9kMtOwzAQRS0EEqXwA7CxxDrF9uRhL0sfgFTUQotYRq4zqVLlUexENPDzpBSxmsXcM6N7CLnmbMA5U3erxfvrciCYEAMQPJIRPyE9HgTSY2GkTkmPSRl4UgXsnFw4t2WMhd2iR75fGp1YXWeGrnSbV5ZO9jtduqwqvXvtMKHD3c5W-6zQNdJxW-qiiy5stbG6KLJyQ9OOmTZ53tIxGixrq_Ps68CNvPliSquUPjd5nXlDi5ouqk-0dNm6Ggt3Sc5SnTu8-pt98jadrEaP3mz-8DQazjwj_LD2EFJMwI_SBDUqNJBAyBisI2G0Nj4Ea60gSNfg-5qlvpFJBDzx2Voajhwi6JPb492uyEeDro63VWPL7mUsZABMgALRpcQxZWzlnMU03tmutW1jzuKD5PhXcnyQHP9J7qCbI5Qh4j-gFHAlQ_gB7vN6kQ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2853023932</pqid></control><display><type>article</type><title>Quadratic Taylor Expansion-Based Approximate Dynamic Programming for Fully Decentralized AC-OPF of Multi-Area Power Systems</title><source>IEEE Electronic Library (IEL)</source><creator>Ye, Hanfang ; Zhu, Jianquan ; Chen, Jiajun ; Wang, Zeshuang ; Zhuo, Yelin ; Liu, Haixin ; Liu, Mingbo</creator><creatorcontrib>Ye, Hanfang ; Zhu, Jianquan ; Chen, Jiajun ; Wang, Zeshuang ; Zhuo, Yelin ; Liu, Haixin ; Liu, Mingbo</creatorcontrib><description>In this paper, a quadratic Taylor expansion-based approximate dynamic programming (QTE-ADP) algorithm is proposed for the decentralized solution of multi-area AC-optimal power flow (MA-ACOPF). Different from traditional ADP algorithms, the proposed algorithm does not need to approximate the value function via a given function structure, but directly obtains the quadratic Taylor expansion (QTE) of value function based on KKT conditions. Moreover, compared with the commonly used linearized value function approximation techniques, the information used to approximate the value function is also extended from first order to second order in the proposed algorithm, which helps to improve the accuracy and efficiency of ADP. When using QTE-ADP to solve the MA-ACOPF problem, only the boundary voltage information needs to be interchanged between adjacent areas, which facilitates preserving the information privacy and decision independence of each area. Numerical simulations on several test systems demonstrate that the proposed algorithm has good performance in terms of accuracy, efficiency, and adaptability.</description><identifier>ISSN: 0885-8950</identifier><identifier>EISSN: 1558-0679</identifier><identifier>DOI: 10.1109/TPWRS.2022.3217871</identifier><identifier>CODEN: ITPSEG</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>AC-OPF ; Accuracy ; Algorithms ; approximate dynamic programming ; Approximation algorithms ; decentralized optimization ; Dynamic programming ; Electric power systems ; Function approximation ; Generators ; Heuristic algorithms ; Load flow ; Mathematical models ; multi-area power systems ; Power flow ; quadratic Taylor expansion ; Taylor series ; Voltage</subject><ispartof>IEEE transactions on power systems, 2023-09, Vol.38 (5), p.4940-4949</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2023</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c246t-e3fed347fdeae9ec3d36003b72caac435ba935fb344a0f4c8d731d40b8c1e1373</cites><orcidid>0000-0001-9097-9045 ; 0000-0001-8084-7292 ; 0000-0001-6701-4018</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9931986$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9931986$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Ye, Hanfang</creatorcontrib><creatorcontrib>Zhu, Jianquan</creatorcontrib><creatorcontrib>Chen, Jiajun</creatorcontrib><creatorcontrib>Wang, Zeshuang</creatorcontrib><creatorcontrib>Zhuo, Yelin</creatorcontrib><creatorcontrib>Liu, Haixin</creatorcontrib><creatorcontrib>Liu, Mingbo</creatorcontrib><title>Quadratic Taylor Expansion-Based Approximate Dynamic Programming for Fully Decentralized AC-OPF of Multi-Area Power Systems</title><title>IEEE transactions on power systems</title><addtitle>TPWRS</addtitle><description>In this paper, a quadratic Taylor expansion-based approximate dynamic programming (QTE-ADP) algorithm is proposed for the decentralized solution of multi-area AC-optimal power flow (MA-ACOPF). Different from traditional ADP algorithms, the proposed algorithm does not need to approximate the value function via a given function structure, but directly obtains the quadratic Taylor expansion (QTE) of value function based on KKT conditions. Moreover, compared with the commonly used linearized value function approximation techniques, the information used to approximate the value function is also extended from first order to second order in the proposed algorithm, which helps to improve the accuracy and efficiency of ADP. When using QTE-ADP to solve the MA-ACOPF problem, only the boundary voltage information needs to be interchanged between adjacent areas, which facilitates preserving the information privacy and decision independence of each area. Numerical simulations on several test systems demonstrate that the proposed algorithm has good performance in terms of accuracy, efficiency, and adaptability.</description><subject>AC-OPF</subject><subject>Accuracy</subject><subject>Algorithms</subject><subject>approximate dynamic programming</subject><subject>Approximation algorithms</subject><subject>decentralized optimization</subject><subject>Dynamic programming</subject><subject>Electric power systems</subject><subject>Function approximation</subject><subject>Generators</subject><subject>Heuristic algorithms</subject><subject>Load flow</subject><subject>Mathematical models</subject><subject>multi-area power systems</subject><subject>Power flow</subject><subject>quadratic Taylor expansion</subject><subject>Taylor series</subject><subject>Voltage</subject><issn>0885-8950</issn><issn>1558-0679</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kMtOwzAQRS0EEqXwA7CxxDrF9uRhL0sfgFTUQotYRq4zqVLlUexENPDzpBSxmsXcM6N7CLnmbMA5U3erxfvrciCYEAMQPJIRPyE9HgTSY2GkTkmPSRl4UgXsnFw4t2WMhd2iR75fGp1YXWeGrnSbV5ZO9jtduqwqvXvtMKHD3c5W-6zQNdJxW-qiiy5stbG6KLJyQ9OOmTZ53tIxGixrq_Ps68CNvPliSquUPjd5nXlDi5ouqk-0dNm6Ggt3Sc5SnTu8-pt98jadrEaP3mz-8DQazjwj_LD2EFJMwI_SBDUqNJBAyBisI2G0Nj4Ea60gSNfg-5qlvpFJBDzx2Voajhwi6JPb492uyEeDro63VWPL7mUsZABMgALRpcQxZWzlnMU03tmutW1jzuKD5PhXcnyQHP9J7qCbI5Qh4j-gFHAlQ_gB7vN6kQ</recordid><startdate>202309</startdate><enddate>202309</enddate><creator>Ye, Hanfang</creator><creator>Zhu, Jianquan</creator><creator>Chen, Jiajun</creator><creator>Wang, Zeshuang</creator><creator>Zhuo, Yelin</creator><creator>Liu, Haixin</creator><creator>Liu, Mingbo</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>KR7</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0001-9097-9045</orcidid><orcidid>https://orcid.org/0000-0001-8084-7292</orcidid><orcidid>https://orcid.org/0000-0001-6701-4018</orcidid></search><sort><creationdate>202309</creationdate><title>Quadratic Taylor Expansion-Based Approximate Dynamic Programming for Fully Decentralized AC-OPF of Multi-Area Power Systems</title><author>Ye, Hanfang ; Zhu, Jianquan ; Chen, Jiajun ; Wang, Zeshuang ; Zhuo, Yelin ; Liu, Haixin ; Liu, Mingbo</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c246t-e3fed347fdeae9ec3d36003b72caac435ba935fb344a0f4c8d731d40b8c1e1373</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>AC-OPF</topic><topic>Accuracy</topic><topic>Algorithms</topic><topic>approximate dynamic programming</topic><topic>Approximation algorithms</topic><topic>decentralized optimization</topic><topic>Dynamic programming</topic><topic>Electric power systems</topic><topic>Function approximation</topic><topic>Generators</topic><topic>Heuristic algorithms</topic><topic>Load flow</topic><topic>Mathematical models</topic><topic>multi-area power systems</topic><topic>Power flow</topic><topic>quadratic Taylor expansion</topic><topic>Taylor series</topic><topic>Voltage</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ye, Hanfang</creatorcontrib><creatorcontrib>Zhu, Jianquan</creatorcontrib><creatorcontrib>Chen, Jiajun</creatorcontrib><creatorcontrib>Wang, Zeshuang</creatorcontrib><creatorcontrib>Zhuo, Yelin</creatorcontrib><creatorcontrib>Liu, Haixin</creatorcontrib><creatorcontrib>Liu, Mingbo</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>IEEE transactions on power systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Ye, Hanfang</au><au>Zhu, Jianquan</au><au>Chen, Jiajun</au><au>Wang, Zeshuang</au><au>Zhuo, Yelin</au><au>Liu, Haixin</au><au>Liu, Mingbo</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Quadratic Taylor Expansion-Based Approximate Dynamic Programming for Fully Decentralized AC-OPF of Multi-Area Power Systems</atitle><jtitle>IEEE transactions on power systems</jtitle><stitle>TPWRS</stitle><date>2023-09</date><risdate>2023</risdate><volume>38</volume><issue>5</issue><spage>4940</spage><epage>4949</epage><pages>4940-4949</pages><issn>0885-8950</issn><eissn>1558-0679</eissn><coden>ITPSEG</coden><abstract>In this paper, a quadratic Taylor expansion-based approximate dynamic programming (QTE-ADP) algorithm is proposed for the decentralized solution of multi-area AC-optimal power flow (MA-ACOPF). Different from traditional ADP algorithms, the proposed algorithm does not need to approximate the value function via a given function structure, but directly obtains the quadratic Taylor expansion (QTE) of value function based on KKT conditions. Moreover, compared with the commonly used linearized value function approximation techniques, the information used to approximate the value function is also extended from first order to second order in the proposed algorithm, which helps to improve the accuracy and efficiency of ADP. When using QTE-ADP to solve the MA-ACOPF problem, only the boundary voltage information needs to be interchanged between adjacent areas, which facilitates preserving the information privacy and decision independence of each area. Numerical simulations on several test systems demonstrate that the proposed algorithm has good performance in terms of accuracy, efficiency, and adaptability.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TPWRS.2022.3217871</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0001-9097-9045</orcidid><orcidid>https://orcid.org/0000-0001-8084-7292</orcidid><orcidid>https://orcid.org/0000-0001-6701-4018</orcidid></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISSN: 0885-8950 |
| ispartof | IEEE transactions on power systems, 2023-09, Vol.38 (5), p.4940-4949 |
| issn | 0885-8950 1558-0679 |
| language | eng |
| recordid | cdi_crossref_primary_10_1109_TPWRS_2022_3217871 |
| source | IEEE Electronic Library (IEL) |
| subjects | AC-OPF Accuracy Algorithms approximate dynamic programming Approximation algorithms decentralized optimization Dynamic programming Electric power systems Function approximation Generators Heuristic algorithms Load flow Mathematical models multi-area power systems Power flow quadratic Taylor expansion Taylor series Voltage |
| title | Quadratic Taylor Expansion-Based Approximate Dynamic Programming for Fully Decentralized AC-OPF of Multi-Area Power Systems |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-23T16%3A46%3A50IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Quadratic%20Taylor%20Expansion-Based%20Approximate%20Dynamic%20Programming%20for%20Fully%20Decentralized%20AC-OPF%20of%20Multi-Area%20Power%20Systems&rft.jtitle=IEEE%20transactions%20on%20power%20systems&rft.au=Ye,%20Hanfang&rft.date=2023-09&rft.volume=38&rft.issue=5&rft.spage=4940&rft.epage=4949&rft.pages=4940-4949&rft.issn=0885-8950&rft.eissn=1558-0679&rft.coden=ITPSEG&rft_id=info:doi/10.1109/TPWRS.2022.3217871&rft_dat=%3Cproquest_RIE%3E2853023932%3C/proquest_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2853023932&rft_id=info:pmid/&rft_ieee_id=9931986&rfr_iscdi=true |