Stability analysis for sub‐synchronous oscillations in multi‐DFIGs connected system considering the interaction between generators

Abstract In order to reveal the multi‐DFIGs interaction mechanism in DFIG wind farms (DFIG‐WFs), this paper proposes a method based on dynamic energy flow path for stability analysis of sub‐synchronous oscillations in multi‐DFIGs connected system. First, the detailed dynamic energy model of DFIG‐WFs...
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Autor*in:	Yaqi Shen [verfasserIn] Jing Ma [verfasserIn] Yufeng Zhao [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	DFIG wind farm energy flow path multi‐DFIGs interaction subsynchronous oscillation

Übergeordnetes Werk:	In: IET Renewable Power Generation - Wiley, 2021, 17(2023), 13, Seite 3325-3339
Übergeordnetes Werk:	volume:17 ; year:2023 ; number:13 ; pages:3325-3339

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc Journal toc

DOI / URN:	10.1049/rpg2.12847

Katalog-ID:	DOAJ098279181

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245	1	0	\|a Stability analysis for sub‐synchronous oscillations in multi‐DFIGs connected system considering the interaction between generators
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520			\|a Abstract In order to reveal the multi‐DFIGs interaction mechanism in DFIG wind farms (DFIG‐WFs), this paper proposes a method based on dynamic energy flow path for stability analysis of sub‐synchronous oscillations in multi‐DFIGs connected system. First, the detailed dynamic energy model of DFIG‐WFs is established considering the inter‐DFIGs coupling effect, and the energy flow paths among multi‐DFIGs are revealed. From this, the interaction energy coefficient is defined to describe the effect of multi‐DFIGs interaction on the system stability, which can be divided into two items: the inter‐DFIGs induction coefficient and the inter‐DFIGs circulation coefficient. On this basis, how the differences in the parameters affect these coefficients are analysed. In this way, the effects of multi‐DFIGs interaction on the oscillation are clarified. Finally, a wind farm model is built in RT‐LAB for simulation verification. The results show that, the changes in DFIG parameters may have mutually exclusive effects on the two coefficients. When the parameters of DFIGs differ greatly, the circulation effect is dominant, which is mainly determined by the difference between DFIGs. If the parameters of DFIGs are similar to each other, the induction effect is dominant and the influence law of parameters is consistent with that of single equivalent model.
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allfields	10.1049/rpg2.12847 doi (DE-627)DOAJ098279181 (DE-599)DOAJ331a9da786874110aa15baf3c2e88967 DE-627 ger DE-627 rakwb eng TJ807-830 Yaqi Shen verfasserin aut Stability analysis for sub‐synchronous oscillations in multi‐DFIGs connected system considering the interaction between generators 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In order to reveal the multi‐DFIGs interaction mechanism in DFIG wind farms (DFIG‐WFs), this paper proposes a method based on dynamic energy flow path for stability analysis of sub‐synchronous oscillations in multi‐DFIGs connected system. First, the detailed dynamic energy model of DFIG‐WFs is established considering the inter‐DFIGs coupling effect, and the energy flow paths among multi‐DFIGs are revealed. From this, the interaction energy coefficient is defined to describe the effect of multi‐DFIGs interaction on the system stability, which can be divided into two items: the inter‐DFIGs induction coefficient and the inter‐DFIGs circulation coefficient. On this basis, how the differences in the parameters affect these coefficients are analysed. In this way, the effects of multi‐DFIGs interaction on the oscillation are clarified. Finally, a wind farm model is built in RT‐LAB for simulation verification. The results show that, the changes in DFIG parameters may have mutually exclusive effects on the two coefficients. When the parameters of DFIGs differ greatly, the circulation effect is dominant, which is mainly determined by the difference between DFIGs. If the parameters of DFIGs are similar to each other, the induction effect is dominant and the influence law of parameters is consistent with that of single equivalent model. DFIG wind farm energy flow path multi‐DFIGs interaction subsynchronous oscillation Renewable energy sources Jing Ma verfasserin aut Yufeng Zhao verfasserin aut In IET Renewable Power Generation Wiley, 2021 17(2023), 13, Seite 3325-3339 (DE-627)521693772 (DE-600)2264540-8 17521424 nnns volume:17 year:2023 number:13 pages:3325-3339 https://doi.org/10.1049/rpg2.12847 kostenfrei https://doaj.org/article/331a9da786874110aa15baf3c2e88967 kostenfrei https://doi.org/10.1049/rpg2.12847 kostenfrei https://doaj.org/toc/1752-1416 Journal toc kostenfrei https://doaj.org/toc/1752-1424 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 17 2023 13 3325-3339
spelling	10.1049/rpg2.12847 doi (DE-627)DOAJ098279181 (DE-599)DOAJ331a9da786874110aa15baf3c2e88967 DE-627 ger DE-627 rakwb eng TJ807-830 Yaqi Shen verfasserin aut Stability analysis for sub‐synchronous oscillations in multi‐DFIGs connected system considering the interaction between generators 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In order to reveal the multi‐DFIGs interaction mechanism in DFIG wind farms (DFIG‐WFs), this paper proposes a method based on dynamic energy flow path for stability analysis of sub‐synchronous oscillations in multi‐DFIGs connected system. First, the detailed dynamic energy model of DFIG‐WFs is established considering the inter‐DFIGs coupling effect, and the energy flow paths among multi‐DFIGs are revealed. From this, the interaction energy coefficient is defined to describe the effect of multi‐DFIGs interaction on the system stability, which can be divided into two items: the inter‐DFIGs induction coefficient and the inter‐DFIGs circulation coefficient. On this basis, how the differences in the parameters affect these coefficients are analysed. In this way, the effects of multi‐DFIGs interaction on the oscillation are clarified. Finally, a wind farm model is built in RT‐LAB for simulation verification. The results show that, the changes in DFIG parameters may have mutually exclusive effects on the two coefficients. When the parameters of DFIGs differ greatly, the circulation effect is dominant, which is mainly determined by the difference between DFIGs. If the parameters of DFIGs are similar to each other, the induction effect is dominant and the influence law of parameters is consistent with that of single equivalent model. DFIG wind farm energy flow path multi‐DFIGs interaction subsynchronous oscillation Renewable energy sources Jing Ma verfasserin aut Yufeng Zhao verfasserin aut In IET Renewable Power Generation Wiley, 2021 17(2023), 13, Seite 3325-3339 (DE-627)521693772 (DE-600)2264540-8 17521424 nnns volume:17 year:2023 number:13 pages:3325-3339 https://doi.org/10.1049/rpg2.12847 kostenfrei https://doaj.org/article/331a9da786874110aa15baf3c2e88967 kostenfrei https://doi.org/10.1049/rpg2.12847 kostenfrei https://doaj.org/toc/1752-1416 Journal toc kostenfrei https://doaj.org/toc/1752-1424 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 17 2023 13 3325-3339
allfields_unstemmed	10.1049/rpg2.12847 doi (DE-627)DOAJ098279181 (DE-599)DOAJ331a9da786874110aa15baf3c2e88967 DE-627 ger DE-627 rakwb eng TJ807-830 Yaqi Shen verfasserin aut Stability analysis for sub‐synchronous oscillations in multi‐DFIGs connected system considering the interaction between generators 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In order to reveal the multi‐DFIGs interaction mechanism in DFIG wind farms (DFIG‐WFs), this paper proposes a method based on dynamic energy flow path for stability analysis of sub‐synchronous oscillations in multi‐DFIGs connected system. First, the detailed dynamic energy model of DFIG‐WFs is established considering the inter‐DFIGs coupling effect, and the energy flow paths among multi‐DFIGs are revealed. From this, the interaction energy coefficient is defined to describe the effect of multi‐DFIGs interaction on the system stability, which can be divided into two items: the inter‐DFIGs induction coefficient and the inter‐DFIGs circulation coefficient. On this basis, how the differences in the parameters affect these coefficients are analysed. In this way, the effects of multi‐DFIGs interaction on the oscillation are clarified. Finally, a wind farm model is built in RT‐LAB for simulation verification. The results show that, the changes in DFIG parameters may have mutually exclusive effects on the two coefficients. When the parameters of DFIGs differ greatly, the circulation effect is dominant, which is mainly determined by the difference between DFIGs. If the parameters of DFIGs are similar to each other, the induction effect is dominant and the influence law of parameters is consistent with that of single equivalent model. DFIG wind farm energy flow path multi‐DFIGs interaction subsynchronous oscillation Renewable energy sources Jing Ma verfasserin aut Yufeng Zhao verfasserin aut In IET Renewable Power Generation Wiley, 2021 17(2023), 13, Seite 3325-3339 (DE-627)521693772 (DE-600)2264540-8 17521424 nnns volume:17 year:2023 number:13 pages:3325-3339 https://doi.org/10.1049/rpg2.12847 kostenfrei https://doaj.org/article/331a9da786874110aa15baf3c2e88967 kostenfrei https://doi.org/10.1049/rpg2.12847 kostenfrei https://doaj.org/toc/1752-1416 Journal toc kostenfrei https://doaj.org/toc/1752-1424 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 17 2023 13 3325-3339
allfieldsGer	10.1049/rpg2.12847 doi (DE-627)DOAJ098279181 (DE-599)DOAJ331a9da786874110aa15baf3c2e88967 DE-627 ger DE-627 rakwb eng TJ807-830 Yaqi Shen verfasserin aut Stability analysis for sub‐synchronous oscillations in multi‐DFIGs connected system considering the interaction between generators 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In order to reveal the multi‐DFIGs interaction mechanism in DFIG wind farms (DFIG‐WFs), this paper proposes a method based on dynamic energy flow path for stability analysis of sub‐synchronous oscillations in multi‐DFIGs connected system. First, the detailed dynamic energy model of DFIG‐WFs is established considering the inter‐DFIGs coupling effect, and the energy flow paths among multi‐DFIGs are revealed. From this, the interaction energy coefficient is defined to describe the effect of multi‐DFIGs interaction on the system stability, which can be divided into two items: the inter‐DFIGs induction coefficient and the inter‐DFIGs circulation coefficient. On this basis, how the differences in the parameters affect these coefficients are analysed. In this way, the effects of multi‐DFIGs interaction on the oscillation are clarified. Finally, a wind farm model is built in RT‐LAB for simulation verification. The results show that, the changes in DFIG parameters may have mutually exclusive effects on the two coefficients. When the parameters of DFIGs differ greatly, the circulation effect is dominant, which is mainly determined by the difference between DFIGs. If the parameters of DFIGs are similar to each other, the induction effect is dominant and the influence law of parameters is consistent with that of single equivalent model. DFIG wind farm energy flow path multi‐DFIGs interaction subsynchronous oscillation Renewable energy sources Jing Ma verfasserin aut Yufeng Zhao verfasserin aut In IET Renewable Power Generation Wiley, 2021 17(2023), 13, Seite 3325-3339 (DE-627)521693772 (DE-600)2264540-8 17521424 nnns volume:17 year:2023 number:13 pages:3325-3339 https://doi.org/10.1049/rpg2.12847 kostenfrei https://doaj.org/article/331a9da786874110aa15baf3c2e88967 kostenfrei https://doi.org/10.1049/rpg2.12847 kostenfrei https://doaj.org/toc/1752-1416 Journal toc kostenfrei https://doaj.org/toc/1752-1424 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 17 2023 13 3325-3339
allfieldsSound	10.1049/rpg2.12847 doi (DE-627)DOAJ098279181 (DE-599)DOAJ331a9da786874110aa15baf3c2e88967 DE-627 ger DE-627 rakwb eng TJ807-830 Yaqi Shen verfasserin aut Stability analysis for sub‐synchronous oscillations in multi‐DFIGs connected system considering the interaction between generators 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In order to reveal the multi‐DFIGs interaction mechanism in DFIG wind farms (DFIG‐WFs), this paper proposes a method based on dynamic energy flow path for stability analysis of sub‐synchronous oscillations in multi‐DFIGs connected system. First, the detailed dynamic energy model of DFIG‐WFs is established considering the inter‐DFIGs coupling effect, and the energy flow paths among multi‐DFIGs are revealed. From this, the interaction energy coefficient is defined to describe the effect of multi‐DFIGs interaction on the system stability, which can be divided into two items: the inter‐DFIGs induction coefficient and the inter‐DFIGs circulation coefficient. On this basis, how the differences in the parameters affect these coefficients are analysed. In this way, the effects of multi‐DFIGs interaction on the oscillation are clarified. Finally, a wind farm model is built in RT‐LAB for simulation verification. The results show that, the changes in DFIG parameters may have mutually exclusive effects on the two coefficients. When the parameters of DFIGs differ greatly, the circulation effect is dominant, which is mainly determined by the difference between DFIGs. If the parameters of DFIGs are similar to each other, the induction effect is dominant and the influence law of parameters is consistent with that of single equivalent model. DFIG wind farm energy flow path multi‐DFIGs interaction subsynchronous oscillation Renewable energy sources Jing Ma verfasserin aut Yufeng Zhao verfasserin aut In IET Renewable Power Generation Wiley, 2021 17(2023), 13, Seite 3325-3339 (DE-627)521693772 (DE-600)2264540-8 17521424 nnns volume:17 year:2023 number:13 pages:3325-3339 https://doi.org/10.1049/rpg2.12847 kostenfrei https://doaj.org/article/331a9da786874110aa15baf3c2e88967 kostenfrei https://doi.org/10.1049/rpg2.12847 kostenfrei https://doaj.org/toc/1752-1416 Journal toc kostenfrei https://doaj.org/toc/1752-1424 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 17 2023 13 3325-3339
language	English
source	In IET Renewable Power Generation 17(2023), 13, Seite 3325-3339 volume:17 year:2023 number:13 pages:3325-3339
sourceStr	In IET Renewable Power Generation 17(2023), 13, Seite 3325-3339 volume:17 year:2023 number:13 pages:3325-3339
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	DFIG wind farm energy flow path multi‐DFIGs interaction subsynchronous oscillation Renewable energy sources
isfreeaccess_bool	true
container_title	IET Renewable Power Generation
authorswithroles_txt_mv	Yaqi Shen @@aut@@ Jing Ma @@aut@@ Yufeng Zhao @@aut@@
publishDateDaySort_date	2023-01-01T00:00:00Z
hierarchy_top_id	521693772
id	DOAJ098279181
language_de	englisch
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First, the detailed dynamic energy model of DFIG‐WFs is established considering the inter‐DFIGs coupling effect, and the energy flow paths among multi‐DFIGs are revealed. From this, the interaction energy coefficient is defined to describe the effect of multi‐DFIGs interaction on the system stability, which can be divided into two items: the inter‐DFIGs induction coefficient and the inter‐DFIGs circulation coefficient. On this basis, how the differences in the parameters affect these coefficients are analysed. In this way, the effects of multi‐DFIGs interaction on the oscillation are clarified. Finally, a wind farm model is built in RT‐LAB for simulation verification. The results show that, the changes in DFIG parameters may have mutually exclusive effects on the two coefficients. When the parameters of DFIGs differ greatly, the circulation effect is dominant, which is mainly determined by the difference between DFIGs. 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callnumber-first	T - Technology
author	Yaqi Shen
spellingShingle	Yaqi Shen misc TJ807-830 misc DFIG wind farm misc energy flow path misc multi‐DFIGs interaction misc subsynchronous oscillation misc Renewable energy sources Stability analysis for sub‐synchronous oscillations in multi‐DFIGs connected system considering the interaction between generators
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topic_title	TJ807-830 Stability analysis for sub‐synchronous oscillations in multi‐DFIGs connected system considering the interaction between generators DFIG wind farm energy flow path multi‐DFIGs interaction subsynchronous oscillation
topic	misc TJ807-830 misc DFIG wind farm misc energy flow path misc multi‐DFIGs interaction misc subsynchronous oscillation misc Renewable energy sources
topic_unstemmed	misc TJ807-830 misc DFIG wind farm misc energy flow path misc multi‐DFIGs interaction misc subsynchronous oscillation misc Renewable energy sources
topic_browse	misc TJ807-830 misc DFIG wind farm misc energy flow path misc multi‐DFIGs interaction misc subsynchronous oscillation misc Renewable energy sources
format_facet	Elektronische Aufsätze Aufsätze Elektronische Ressource
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title	Stability analysis for sub‐synchronous oscillations in multi‐DFIGs connected system considering the interaction between generators
ctrlnum	(DE-627)DOAJ098279181 (DE-599)DOAJ331a9da786874110aa15baf3c2e88967
title_full	Stability analysis for sub‐synchronous oscillations in multi‐DFIGs connected system considering the interaction between generators
author_sort	Yaqi Shen
journal	IET Renewable Power Generation
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author_browse	Yaqi Shen Jing Ma Yufeng Zhao
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doi_str_mv	10.1049/rpg2.12847
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title_sort	stability analysis for sub‐synchronous oscillations in multi‐dfigs connected system considering the interaction between generators
callnumber	TJ807-830
title_auth	Stability analysis for sub‐synchronous oscillations in multi‐DFIGs connected system considering the interaction between generators
abstract	Abstract In order to reveal the multi‐DFIGs interaction mechanism in DFIG wind farms (DFIG‐WFs), this paper proposes a method based on dynamic energy flow path for stability analysis of sub‐synchronous oscillations in multi‐DFIGs connected system. First, the detailed dynamic energy model of DFIG‐WFs is established considering the inter‐DFIGs coupling effect, and the energy flow paths among multi‐DFIGs are revealed. From this, the interaction energy coefficient is defined to describe the effect of multi‐DFIGs interaction on the system stability, which can be divided into two items: the inter‐DFIGs induction coefficient and the inter‐DFIGs circulation coefficient. On this basis, how the differences in the parameters affect these coefficients are analysed. In this way, the effects of multi‐DFIGs interaction on the oscillation are clarified. Finally, a wind farm model is built in RT‐LAB for simulation verification. The results show that, the changes in DFIG parameters may have mutually exclusive effects on the two coefficients. When the parameters of DFIGs differ greatly, the circulation effect is dominant, which is mainly determined by the difference between DFIGs. If the parameters of DFIGs are similar to each other, the induction effect is dominant and the influence law of parameters is consistent with that of single equivalent model.
abstractGer	Abstract In order to reveal the multi‐DFIGs interaction mechanism in DFIG wind farms (DFIG‐WFs), this paper proposes a method based on dynamic energy flow path for stability analysis of sub‐synchronous oscillations in multi‐DFIGs connected system. First, the detailed dynamic energy model of DFIG‐WFs is established considering the inter‐DFIGs coupling effect, and the energy flow paths among multi‐DFIGs are revealed. From this, the interaction energy coefficient is defined to describe the effect of multi‐DFIGs interaction on the system stability, which can be divided into two items: the inter‐DFIGs induction coefficient and the inter‐DFIGs circulation coefficient. On this basis, how the differences in the parameters affect these coefficients are analysed. In this way, the effects of multi‐DFIGs interaction on the oscillation are clarified. Finally, a wind farm model is built in RT‐LAB for simulation verification. The results show that, the changes in DFIG parameters may have mutually exclusive effects on the two coefficients. When the parameters of DFIGs differ greatly, the circulation effect is dominant, which is mainly determined by the difference between DFIGs. If the parameters of DFIGs are similar to each other, the induction effect is dominant and the influence law of parameters is consistent with that of single equivalent model.
abstract_unstemmed	Abstract In order to reveal the multi‐DFIGs interaction mechanism in DFIG wind farms (DFIG‐WFs), this paper proposes a method based on dynamic energy flow path for stability analysis of sub‐synchronous oscillations in multi‐DFIGs connected system. First, the detailed dynamic energy model of DFIG‐WFs is established considering the inter‐DFIGs coupling effect, and the energy flow paths among multi‐DFIGs are revealed. From this, the interaction energy coefficient is defined to describe the effect of multi‐DFIGs interaction on the system stability, which can be divided into two items: the inter‐DFIGs induction coefficient and the inter‐DFIGs circulation coefficient. On this basis, how the differences in the parameters affect these coefficients are analysed. In this way, the effects of multi‐DFIGs interaction on the oscillation are clarified. Finally, a wind farm model is built in RT‐LAB for simulation verification. The results show that, the changes in DFIG parameters may have mutually exclusive effects on the two coefficients. When the parameters of DFIGs differ greatly, the circulation effect is dominant, which is mainly determined by the difference between DFIGs. If the parameters of DFIGs are similar to each other, the induction effect is dominant and the influence law of parameters is consistent with that of single equivalent model.
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title_short	Stability analysis for sub‐synchronous oscillations in multi‐DFIGs connected system considering the interaction between generators
url	https://doi.org/10.1049/rpg2.12847 https://doaj.org/article/331a9da786874110aa15baf3c2e88967 https://doaj.org/toc/1752-1416 https://doaj.org/toc/1752-1424
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doi_str	10.1049/rpg2.12847
callnumber-a	TJ807-830
up_date	2024-07-03T16:25:46.306Z
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fullrecord_marcxml	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">DOAJ098279181</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20240413212958.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">240413s2023 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1049/rpg2.12847</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ098279181</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJ331a9da786874110aa15baf3c2e88967</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">TJ807-830</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Yaqi Shen</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Stability analysis for sub‐synchronous oscillations in multi‐DFIGs connected system considering the interaction between generators</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2023</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract In order to reveal the multi‐DFIGs interaction mechanism in DFIG wind farms (DFIG‐WFs), this paper proposes a method based on dynamic energy flow path for stability analysis of sub‐synchronous oscillations in multi‐DFIGs connected system. First, the detailed dynamic energy model of DFIG‐WFs is established considering the inter‐DFIGs coupling effect, and the energy flow paths among multi‐DFIGs are revealed. From this, the interaction energy coefficient is defined to describe the effect of multi‐DFIGs interaction on the system stability, which can be divided into two items: the inter‐DFIGs induction coefficient and the inter‐DFIGs circulation coefficient. On this basis, how the differences in the parameters affect these coefficients are analysed. In this way, the effects of multi‐DFIGs interaction on the oscillation are clarified. Finally, a wind farm model is built in RT‐LAB for simulation verification. The results show that, the changes in DFIG parameters may have mutually exclusive effects on the two coefficients. When the parameters of DFIGs differ greatly, the circulation effect is dominant, which is mainly determined by the difference between DFIGs. If the parameters of DFIGs are similar to each other, the induction effect is dominant and the influence law of parameters is consistent with that of single equivalent model.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">DFIG wind farm</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">energy flow path</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">multi‐DFIGs interaction</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">subsynchronous oscillation</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Renewable energy sources</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Jing Ma</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Yufeng Zhao</subfield><subfield code="e">verfasserin</subfield><subfield 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Stability analysis for sub‐synchronous oscillations in multi‐DFIGs connected system considering the interaction between generators

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