Proximal Policy Optimization-Based Stability Control Method for Permanent Magnet Direct-Drive Wind Power Generation System
With the increasing proportion of wind power grid connection, the stable control performance of wind turbines is crucial for the safety and stability of the power system. This paper proposes a proximal policy optimization (PPO) algorithm-based adaptive stability control framework for low voltage rid...
Uložené v:
| Vydané v: | 2025 7th International Conference on Power and Energy Technology (ICPET) s. 695 - 699 |
|---|---|
| Hlavní autori: | , , , , |
| Médium: | Konferenčný príspevok.. |
| Jazyk: | English |
| Vydavateľské údaje: |
IEEE
04.07.2025
|
| Predmet: | |
| On-line prístup: | Získať plný text |
| Tagy: |
Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
|
| Abstract | With the increasing proportion of wind power grid connection, the stable control performance of wind turbines is crucial for the safety and stability of the power system. This paper proposes a proximal policy optimization (PPO) algorithm-based adaptive stability control framework for low voltage ride-through (LVRT) in permanent magnet direct-drive wind power generation system. Considering phase-locked loop (PLL) impact on system performance, this method real-time adjusts PLL parameters to enhance LVRT. A Markov decision process (MDP) model for LVRT control is established, and reward functions for distinct fault stages are designed. The PPO algorithm solves for the adaptive control strategy. Simulation results validate the method's effectiveness across various faults, demonstrating significant improvements in system LVRT capability, adaptability and stability control capability. |
|---|---|
| AbstractList | With the increasing proportion of wind power grid connection, the stable control performance of wind turbines is crucial for the safety and stability of the power system. This paper proposes a proximal policy optimization (PPO) algorithm-based adaptive stability control framework for low voltage ride-through (LVRT) in permanent magnet direct-drive wind power generation system. Considering phase-locked loop (PLL) impact on system performance, this method real-time adjusts PLL parameters to enhance LVRT. A Markov decision process (MDP) model for LVRT control is established, and reward functions for distinct fault stages are designed. The PPO algorithm solves for the adaptive control strategy. Simulation results validate the method's effectiveness across various faults, demonstrating significant improvements in system LVRT capability, adaptability and stability control capability. |
| Author | Ou, Wenjun Wei, Shenghua Guo, Xinran Wang, Hongxing Guo, Jingmei |
| Author_xml | – sequence: 1 givenname: Hongxing surname: Wang fullname: Wang, Hongxing email: hxwang2010@163.com organization: China Southern Power Grid Technology Co., Ltd. Guangdong Provincial Key Laboratory of New Technology for Smart Grid,Guangzhou,China – sequence: 2 givenname: Shenghua surname: Wei fullname: Wei, Shenghua email: wsh502wsh@163.com organization: China Southern Power Grid Technology Co., Ltd.,Guangzhou,China – sequence: 3 givenname: Jingmei surname: Guo fullname: Guo, Jingmei email: gjm_gddky@163.com organization: China Southern Power Grid Technology Co., Ltd. Guangdong Provincial Key Laboratory of New Technology for Smart Grid,Guangzhou,China – sequence: 4 givenname: Xinran surname: Guo fullname: Guo, Xinran email: g18820101803@163.com organization: China Southern Power Grid Technology Co., Ltd.,Guangzhou,China – sequence: 5 givenname: Wenjun surname: Ou fullname: Ou, Wenjun email: fshkenou@hotmail.com organization: China Southern Power Grid Technology Co., Ltd.,Guangzhou,China |
| BookMark | eNo10MtKAzEYBeAIutDaN3CRF5iaTO5LndZasHSgBZclM_NHAzNJSYM6fXqLl9WBs_jgnBt0GWIAhDAlM0qJuV9V9WInJSnNrCSlOJdUEs7lBZoaZTRjVHCupbpGpzrFLz_YHtex9-2IN4fsB3-y2cdQPNojdHibbeN7n0dcxZBT7PEa8nvssIsJ15AGGyBkvLZvATKe-wRtLubJfwB-9aE7y5-Q8BICpB8Wb8djhuEWXTnbH2H6lxO0e1rsqufiZbNcVQ8vhTcsF7ykre0MV4proK2xXDcdaRphtGi4akUrjbKN47R0ikgtHHHcMqlLZrV2gk3Q3S_rAWB_SOexadz_P8K-AXDLXW0 |
| ContentType | Conference Proceeding |
| DBID | 6IE 6IL CBEJK RIE RIL |
| DOI | 10.1109/ICPET66029.2025.11160446 |
| DatabaseName | IEEE Electronic Library (IEL) Conference Proceedings IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume IEEE Xplore All Conference Proceedings IEEE Xplore: IEL IEEE Proceedings Order Plans (POP All) 1998-Present |
| DatabaseTitleList | |
| Database_xml | – sequence: 1 dbid: RIE name: IEEE Electronic Library (IEL) url: https://ieeexplore.ieee.org/ sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| EISBN | 9798331544867 |
| EndPage | 699 |
| ExternalDocumentID | 11160446 |
| Genre | orig-research |
| GroupedDBID | 6IE 6IL CBEJK RIE RIL |
| ID | FETCH-LOGICAL-i93t-421cad947748e1c9a48bd0bb5985b47c5c697abf412f70685f0f4a36823a88f53 |
| IEDL.DBID | RIE |
| IngestDate | Wed Oct 01 07:05:04 EDT 2025 |
| IsPeerReviewed | false |
| IsScholarly | false |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-i93t-421cad947748e1c9a48bd0bb5985b47c5c697abf412f70685f0f4a36823a88f53 |
| PageCount | 5 |
| ParticipantIDs | ieee_primary_11160446 |
| PublicationCentury | 2000 |
| PublicationDate | 2025-July-4 |
| PublicationDateYYYYMMDD | 2025-07-04 |
| PublicationDate_xml | – month: 07 year: 2025 text: 2025-July-4 day: 04 |
| PublicationDecade | 2020 |
| PublicationTitle | 2025 7th International Conference on Power and Energy Technology (ICPET) |
| PublicationTitleAbbrev | ICPET |
| PublicationYear | 2025 |
| Publisher | IEEE |
| Publisher_xml | – name: IEEE |
| Score | 1.9139471 |
| Snippet | With the increasing proportion of wind power grid connection, the stable control performance of wind turbines is crucial for the safety and stability of the... |
| SourceID | ieee |
| SourceType | Publisher |
| StartPage | 695 |
| SubjectTerms | Deep reinforcement learning Low voltage low voltage ride through Optimization permanent magnet synchronous generator Permanent magnets Phase locked loops phase-locked loop Power system stability proximal policy optimization Simulation Stability analysis Wind power generation Wind turbines |
| Title | Proximal Policy Optimization-Based Stability Control Method for Permanent Magnet Direct-Drive Wind Power Generation System |
| URI | https://ieeexplore.ieee.org/document/11160446 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1JSwMxFA62ePCkYsWdHLymzcxkslytLQq2zqFgbyWTRQp2KuPU7debpVU8ePAWQkjgPd6S5PveA-BSCG0klxJRkRhEpBZIeqwr0QwrSq0mMmj6jo3HfDoVxZqsHrgwxpgAPjNdPwx_-XqpVv6prOfskvoPyBZoMUYjWWuDzsGid9svBhNKceoJKGne3Sz_1TglxI3h7j9P3AOdHwYeLL5jyz7YMtUB-HQz7_OFfIKxmi-8d_a-WBMp0ZWLRxq65DHAXT9gP4LQ4Sj0iIYuOYWFd8OVOxGO5GNlGhgdHrqunc-DD-567nZ-MzWMxaj9tjCWNO-AyXAw6d-gde8ENBdZg0iaKCd34pI7bhIlJOGlxmWZC56XhKlcUcFkaUmSWoYpzy22RGaUp5nk3ObZIWhXy8ocAagsM5nL2hTjgihTCmG5M1ouM0JwJsUx6Hi5zZ5jdYzZRmQnf8yfgh2vnQB5JWeg3dQrcw621Wszf6kvgk6_AJ2MphE |
| linkProvider | IEEE |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3NT8MgFCc6TfSkxhm_5eCVjbZA4ercssVt9tDE3RZKwSxxnamdX3-9QDeNBw_eCAmQvJf3Afx-7wFwLUSuJZcSMRFoRGQukHRYV5LHWDFmciK9pofxeMwnE5GsyOqeC6O19uAz3XJD_5efL9TSPZW1rV0y9wG5CbYoISGu6VprfA4W7UEn6aaM4dBRUELaWi_41TrFR47e3j_P3AfNHw4eTL6jywHY0MUh-LQz77O5fIJ1PV94by1-vqJSohsbkXJo00cPeP2AnRqGDke-SzS06SlMnCMu7IlwJB8LXcHa5aHb0no9-GAv6HbnN13Cuhy12xbWRc2bIO11004frbonoJmIKkTCQFnJE5vecR0oIQnPcpxlVHCakVhRxUQsM0OC0MSYcWqwITJiPIwk54ZGR6BRLAp9DKAysY5s3qZiLojSmRCGW7PlMiIER1KcgKaT2_S5ro8xXYvs9I_5K7DTT0fD6XAwvjsDu05THgBLzkGjKpf6Amyr12r2Ul56_X4BbA-pWA |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=proceeding&rft.title=2025+7th+International+Conference+on+Power+and+Energy+Technology+%28ICPET%29&rft.atitle=Proximal+Policy+Optimization-Based+Stability+Control+Method+for+Permanent+Magnet+Direct-Drive+Wind+Power+Generation+System&rft.au=Wang%2C+Hongxing&rft.au=Wei%2C+Shenghua&rft.au=Guo%2C+Jingmei&rft.au=Guo%2C+Xinran&rft.date=2025-07-04&rft.pub=IEEE&rft.spage=695&rft.epage=699&rft_id=info:doi/10.1109%2FICPET66029.2025.11160446&rft.externalDocID=11160446 |