Combination weighting-based method for access point optimization of offshore wind farm

With the fast development of offshore wind power, the fluctuation of its output has an increasingly significant impact on the secure and stable operation of power system. Aiming at the large-scale offshore wind farms (OWFs) integrated, a method for selecting optimal access point is proposed. The cap...
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Autor*in:	Xiaoming Liu [verfasserIn] Zukuang Tan [verfasserIn] Zhenhua Yuan [verfasserIn] Yutian Liu [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	Access point Combination weighting method Offshore wind farm Power system

Übergeordnetes Werk:	In: Energy Reports - Elsevier, 2016, 8(2022), Seite 900-907
Übergeordnetes Werk:	volume:8 ; year:2022 ; pages:900-907

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1016/j.egyr.2021.11.121

Katalog-ID:	DOAJ044962096

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520			\|a With the fast development of offshore wind power, the fluctuation of its output has an increasingly significant impact on the secure and stable operation of power system. Aiming at the large-scale offshore wind farms (OWFs) integrated, a method for selecting optimal access point is proposed. The capability of wind power accommodation, voltage stability, transmission network vulnerability and construction cost are considered as evaluation indexes. Based on the theory of information entropy and fuzzy analytic hierarchy process, taking the minimum deviation of the comprehensive weight and maximum of the compressive weight value as the optimization goal, the combination weighting model is established to determine the index weight. Simulation result of Shandong Power grid of China demonstrate the effectiveness of the proposed method for selecting the access point of the OWF.
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allfields	10.1016/j.egyr.2021.11.121 doi (DE-627)DOAJ044962096 (DE-599)DOAJ8d042f5e465647ff8f32d0b9f7ed5c30 DE-627 ger DE-627 rakwb eng TK1-9971 Xiaoming Liu verfasserin aut Combination weighting-based method for access point optimization of offshore wind farm 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier With the fast development of offshore wind power, the fluctuation of its output has an increasingly significant impact on the secure and stable operation of power system. Aiming at the large-scale offshore wind farms (OWFs) integrated, a method for selecting optimal access point is proposed. The capability of wind power accommodation, voltage stability, transmission network vulnerability and construction cost are considered as evaluation indexes. Based on the theory of information entropy and fuzzy analytic hierarchy process, taking the minimum deviation of the comprehensive weight and maximum of the compressive weight value as the optimization goal, the combination weighting model is established to determine the index weight. Simulation result of Shandong Power grid of China demonstrate the effectiveness of the proposed method for selecting the access point of the OWF. Access point Combination weighting method Offshore wind farm Power system Electrical engineering. Electronics. Nuclear engineering Zukuang Tan verfasserin aut Zhenhua Yuan verfasserin aut Yutian Liu verfasserin aut In Energy Reports Elsevier, 2016 8(2022), Seite 900-907 (DE-627)820689033 (DE-600)2814795-9 23524847 nnns volume:8 year:2022 pages:900-907 https://doi.org/10.1016/j.egyr.2021.11.121 kostenfrei https://doaj.org/article/8d042f5e465647ff8f32d0b9f7ed5c30 kostenfrei http://www.sciencedirect.com/science/article/pii/S2352484721012683 kostenfrei https://doaj.org/toc/2352-4847 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 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_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 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_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 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_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 8 2022 900-907
spelling	10.1016/j.egyr.2021.11.121 doi (DE-627)DOAJ044962096 (DE-599)DOAJ8d042f5e465647ff8f32d0b9f7ed5c30 DE-627 ger DE-627 rakwb eng TK1-9971 Xiaoming Liu verfasserin aut Combination weighting-based method for access point optimization of offshore wind farm 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier With the fast development of offshore wind power, the fluctuation of its output has an increasingly significant impact on the secure and stable operation of power system. Aiming at the large-scale offshore wind farms (OWFs) integrated, a method for selecting optimal access point is proposed. The capability of wind power accommodation, voltage stability, transmission network vulnerability and construction cost are considered as evaluation indexes. Based on the theory of information entropy and fuzzy analytic hierarchy process, taking the minimum deviation of the comprehensive weight and maximum of the compressive weight value as the optimization goal, the combination weighting model is established to determine the index weight. Simulation result of Shandong Power grid of China demonstrate the effectiveness of the proposed method for selecting the access point of the OWF. Access point Combination weighting method Offshore wind farm Power system Electrical engineering. Electronics. Nuclear engineering Zukuang Tan verfasserin aut Zhenhua Yuan verfasserin aut Yutian Liu verfasserin aut In Energy Reports Elsevier, 2016 8(2022), Seite 900-907 (DE-627)820689033 (DE-600)2814795-9 23524847 nnns volume:8 year:2022 pages:900-907 https://doi.org/10.1016/j.egyr.2021.11.121 kostenfrei https://doaj.org/article/8d042f5e465647ff8f32d0b9f7ed5c30 kostenfrei http://www.sciencedirect.com/science/article/pii/S2352484721012683 kostenfrei https://doaj.org/toc/2352-4847 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 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_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 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_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 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_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 8 2022 900-907
allfields_unstemmed	10.1016/j.egyr.2021.11.121 doi (DE-627)DOAJ044962096 (DE-599)DOAJ8d042f5e465647ff8f32d0b9f7ed5c30 DE-627 ger DE-627 rakwb eng TK1-9971 Xiaoming Liu verfasserin aut Combination weighting-based method for access point optimization of offshore wind farm 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier With the fast development of offshore wind power, the fluctuation of its output has an increasingly significant impact on the secure and stable operation of power system. Aiming at the large-scale offshore wind farms (OWFs) integrated, a method for selecting optimal access point is proposed. The capability of wind power accommodation, voltage stability, transmission network vulnerability and construction cost are considered as evaluation indexes. Based on the theory of information entropy and fuzzy analytic hierarchy process, taking the minimum deviation of the comprehensive weight and maximum of the compressive weight value as the optimization goal, the combination weighting model is established to determine the index weight. Simulation result of Shandong Power grid of China demonstrate the effectiveness of the proposed method for selecting the access point of the OWF. Access point Combination weighting method Offshore wind farm Power system Electrical engineering. Electronics. Nuclear engineering Zukuang Tan verfasserin aut Zhenhua Yuan verfasserin aut Yutian Liu verfasserin aut In Energy Reports Elsevier, 2016 8(2022), Seite 900-907 (DE-627)820689033 (DE-600)2814795-9 23524847 nnns volume:8 year:2022 pages:900-907 https://doi.org/10.1016/j.egyr.2021.11.121 kostenfrei https://doaj.org/article/8d042f5e465647ff8f32d0b9f7ed5c30 kostenfrei http://www.sciencedirect.com/science/article/pii/S2352484721012683 kostenfrei https://doaj.org/toc/2352-4847 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 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_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 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_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 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_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 8 2022 900-907
allfieldsGer	10.1016/j.egyr.2021.11.121 doi (DE-627)DOAJ044962096 (DE-599)DOAJ8d042f5e465647ff8f32d0b9f7ed5c30 DE-627 ger DE-627 rakwb eng TK1-9971 Xiaoming Liu verfasserin aut Combination weighting-based method for access point optimization of offshore wind farm 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier With the fast development of offshore wind power, the fluctuation of its output has an increasingly significant impact on the secure and stable operation of power system. Aiming at the large-scale offshore wind farms (OWFs) integrated, a method for selecting optimal access point is proposed. The capability of wind power accommodation, voltage stability, transmission network vulnerability and construction cost are considered as evaluation indexes. Based on the theory of information entropy and fuzzy analytic hierarchy process, taking the minimum deviation of the comprehensive weight and maximum of the compressive weight value as the optimization goal, the combination weighting model is established to determine the index weight. Simulation result of Shandong Power grid of China demonstrate the effectiveness of the proposed method for selecting the access point of the OWF. Access point Combination weighting method Offshore wind farm Power system Electrical engineering. Electronics. Nuclear engineering Zukuang Tan verfasserin aut Zhenhua Yuan verfasserin aut Yutian Liu verfasserin aut In Energy Reports Elsevier, 2016 8(2022), Seite 900-907 (DE-627)820689033 (DE-600)2814795-9 23524847 nnns volume:8 year:2022 pages:900-907 https://doi.org/10.1016/j.egyr.2021.11.121 kostenfrei https://doaj.org/article/8d042f5e465647ff8f32d0b9f7ed5c30 kostenfrei http://www.sciencedirect.com/science/article/pii/S2352484721012683 kostenfrei https://doaj.org/toc/2352-4847 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 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_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 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_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 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_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 8 2022 900-907
allfieldsSound	10.1016/j.egyr.2021.11.121 doi (DE-627)DOAJ044962096 (DE-599)DOAJ8d042f5e465647ff8f32d0b9f7ed5c30 DE-627 ger DE-627 rakwb eng TK1-9971 Xiaoming Liu verfasserin aut Combination weighting-based method for access point optimization of offshore wind farm 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier With the fast development of offshore wind power, the fluctuation of its output has an increasingly significant impact on the secure and stable operation of power system. Aiming at the large-scale offshore wind farms (OWFs) integrated, a method for selecting optimal access point is proposed. The capability of wind power accommodation, voltage stability, transmission network vulnerability and construction cost are considered as evaluation indexes. Based on the theory of information entropy and fuzzy analytic hierarchy process, taking the minimum deviation of the comprehensive weight and maximum of the compressive weight value as the optimization goal, the combination weighting model is established to determine the index weight. Simulation result of Shandong Power grid of China demonstrate the effectiveness of the proposed method for selecting the access point of the OWF. Access point Combination weighting method Offshore wind farm Power system Electrical engineering. Electronics. Nuclear engineering Zukuang Tan verfasserin aut Zhenhua Yuan verfasserin aut Yutian Liu verfasserin aut In Energy Reports Elsevier, 2016 8(2022), Seite 900-907 (DE-627)820689033 (DE-600)2814795-9 23524847 nnns volume:8 year:2022 pages:900-907 https://doi.org/10.1016/j.egyr.2021.11.121 kostenfrei https://doaj.org/article/8d042f5e465647ff8f32d0b9f7ed5c30 kostenfrei http://www.sciencedirect.com/science/article/pii/S2352484721012683 kostenfrei https://doaj.org/toc/2352-4847 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 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_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 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_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 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_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 8 2022 900-907
language	English
source	In Energy Reports 8(2022), Seite 900-907 volume:8 year:2022 pages:900-907
sourceStr	In Energy Reports 8(2022), Seite 900-907 volume:8 year:2022 pages:900-907
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Access point Combination weighting method Offshore wind farm Power system Electrical engineering. Electronics. Nuclear engineering
isfreeaccess_bool	true
container_title	Energy Reports
authorswithroles_txt_mv	Xiaoming Liu @@aut@@ Zukuang Tan @@aut@@ Zhenhua Yuan @@aut@@ Yutian Liu @@aut@@
publishDateDaySort_date	2022-01-01T00:00:00Z
hierarchy_top_id	820689033
id	DOAJ044962096
language_de	englisch
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callnumber-first	T - Technology
author	Xiaoming Liu
spellingShingle	Xiaoming Liu misc TK1-9971 misc Access point misc Combination weighting method misc Offshore wind farm misc Power system misc Electrical engineering. Electronics. Nuclear engineering Combination weighting-based method for access point optimization of offshore wind farm
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topic_title	TK1-9971 Combination weighting-based method for access point optimization of offshore wind farm Access point Combination weighting method Offshore wind farm Power system
topic	misc TK1-9971 misc Access point misc Combination weighting method misc Offshore wind farm misc Power system misc Electrical engineering. Electronics. Nuclear engineering
topic_unstemmed	misc TK1-9971 misc Access point misc Combination weighting method misc Offshore wind farm misc Power system misc Electrical engineering. Electronics. Nuclear engineering
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title	Combination weighting-based method for access point optimization of offshore wind farm
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title_full	Combination weighting-based method for access point optimization of offshore wind farm
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title_sort	combination weighting-based method for access point optimization of offshore wind farm
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title_auth	Combination weighting-based method for access point optimization of offshore wind farm
abstract	With the fast development of offshore wind power, the fluctuation of its output has an increasingly significant impact on the secure and stable operation of power system. Aiming at the large-scale offshore wind farms (OWFs) integrated, a method for selecting optimal access point is proposed. The capability of wind power accommodation, voltage stability, transmission network vulnerability and construction cost are considered as evaluation indexes. Based on the theory of information entropy and fuzzy analytic hierarchy process, taking the minimum deviation of the comprehensive weight and maximum of the compressive weight value as the optimization goal, the combination weighting model is established to determine the index weight. Simulation result of Shandong Power grid of China demonstrate the effectiveness of the proposed method for selecting the access point of the OWF.
abstractGer	With the fast development of offshore wind power, the fluctuation of its output has an increasingly significant impact on the secure and stable operation of power system. Aiming at the large-scale offshore wind farms (OWFs) integrated, a method for selecting optimal access point is proposed. The capability of wind power accommodation, voltage stability, transmission network vulnerability and construction cost are considered as evaluation indexes. Based on the theory of information entropy and fuzzy analytic hierarchy process, taking the minimum deviation of the comprehensive weight and maximum of the compressive weight value as the optimization goal, the combination weighting model is established to determine the index weight. Simulation result of Shandong Power grid of China demonstrate the effectiveness of the proposed method for selecting the access point of the OWF.
abstract_unstemmed	With the fast development of offshore wind power, the fluctuation of its output has an increasingly significant impact on the secure and stable operation of power system. Aiming at the large-scale offshore wind farms (OWFs) integrated, a method for selecting optimal access point is proposed. The capability of wind power accommodation, voltage stability, transmission network vulnerability and construction cost are considered as evaluation indexes. Based on the theory of information entropy and fuzzy analytic hierarchy process, taking the minimum deviation of the comprehensive weight and maximum of the compressive weight value as the optimization goal, the combination weighting model is established to determine the index weight. Simulation result of Shandong Power grid of China demonstrate the effectiveness of the proposed method for selecting the access point of the OWF.
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title_short	Combination weighting-based method for access point optimization of offshore wind farm
url	https://doi.org/10.1016/j.egyr.2021.11.121 https://doaj.org/article/8d042f5e465647ff8f32d0b9f7ed5c30 http://www.sciencedirect.com/science/article/pii/S2352484721012683 https://doaj.org/toc/2352-4847
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doi_str	10.1016/j.egyr.2021.11.121
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Combination weighting-based method for access point optimization of offshore wind farm

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