Collaborative optimization of dynamic grid dispatch with wind power
Economic dispatch can promote the economic operation of power systems, and reactive power dispatch can ensure the safe and reliable operation of power systems. Essentially different from the related literature with separately optimizing the two dispatches, this paper proposes the collaborative optim...
Ausführliche Beschreibung
Autor*in: |
Liu, Jiaxin [verfasserIn] Liu, Yungang [verfasserIn] Liang, Huijun [verfasserIn] Man, Yongchao [verfasserIn] Li, Fengzhong [verfasserIn] Li, Wenjuan [verfasserIn] |
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E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2021 |
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Schlagwörter: |
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Übergeordnetes Werk: |
Enthalten in: International journal of electrical power & energy systems - Amsterdam [u.a.] : Elsevier Science, 1979, 133 |
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Übergeordnetes Werk: |
volume:133 |
DOI / URN: |
10.1016/j.ijepes.2021.107196 |
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Katalog-ID: |
ELV006449956 |
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245 | 1 | 0 | |a Collaborative optimization of dynamic grid dispatch with wind power |
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520 | |a Economic dispatch can promote the economic operation of power systems, and reactive power dispatch can ensure the safe and reliable operation of power systems. Essentially different from the related literature with separately optimizing the two dispatches, this paper proposes the collaborative optimization strategy of dynamic grid dispatch to optimize economic dispatch and reactive power dispatch simultaneously. The strategy is devoted to analyzing the internal relationship of the two dispatches, and establishing a collaborative optimization model to complete the collaborative optimization of the two dispatches. Moreover, multi-objective hybrid bat algorithm is improved by an unbalanced power distribution method, which is suitable to solve dynamic grid dispatch problem. Finally, wind power predicted by neural network is integrated in the collaborative optimization of dynamic grid dispatch, and the influence of wind power integration on grid dispatch is studied. The numerical examples on the IEEE 30-bus are provided to demonstrate the superiority of the proposed strategy. | ||
650 | 4 | |a Economic dispatch | |
650 | 4 | |a Reactive power dispatch | |
650 | 4 | |a Collaborative optimization | |
650 | 4 | |a Unbalanced power distribution | |
650 | 4 | |a Wind power integration | |
700 | 1 | |a Liu, Yungang |e verfasserin |4 aut | |
700 | 1 | |a Liang, Huijun |e verfasserin |4 aut | |
700 | 1 | |a Man, Yongchao |e verfasserin |4 aut | |
700 | 1 | |a Li, Fengzhong |e verfasserin |4 aut | |
700 | 1 | |a Li, Wenjuan |e verfasserin |4 aut | |
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2021 |
allfields |
10.1016/j.ijepes.2021.107196 doi (DE-627)ELV006449956 (ELSEVIER)S0142-0615(21)00435-X DE-627 ger DE-627 rda eng 620 DE-600 53.30 bkl Liu, Jiaxin verfasserin aut Collaborative optimization of dynamic grid dispatch with wind power 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Economic dispatch can promote the economic operation of power systems, and reactive power dispatch can ensure the safe and reliable operation of power systems. Essentially different from the related literature with separately optimizing the two dispatches, this paper proposes the collaborative optimization strategy of dynamic grid dispatch to optimize economic dispatch and reactive power dispatch simultaneously. The strategy is devoted to analyzing the internal relationship of the two dispatches, and establishing a collaborative optimization model to complete the collaborative optimization of the two dispatches. Moreover, multi-objective hybrid bat algorithm is improved by an unbalanced power distribution method, which is suitable to solve dynamic grid dispatch problem. Finally, wind power predicted by neural network is integrated in the collaborative optimization of dynamic grid dispatch, and the influence of wind power integration on grid dispatch is studied. The numerical examples on the IEEE 30-bus are provided to demonstrate the superiority of the proposed strategy. Economic dispatch Reactive power dispatch Collaborative optimization Unbalanced power distribution Wind power integration Liu, Yungang verfasserin aut Liang, Huijun verfasserin aut Man, Yongchao verfasserin aut Li, Fengzhong verfasserin aut Li, Wenjuan verfasserin aut Enthalten in International journal of electrical power & energy systems Amsterdam [u.a.] : Elsevier Science, 1979 133 Online-Ressource (DE-627)320411907 (DE-600)2001425-9 (DE-576)259271101 0142-0615 nnns volume:133 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 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_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 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_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_4393 GBV_ILN_4700 53.30 Elektrische Energietechnik: Allgemeines AR 133 |
spelling |
10.1016/j.ijepes.2021.107196 doi (DE-627)ELV006449956 (ELSEVIER)S0142-0615(21)00435-X DE-627 ger DE-627 rda eng 620 DE-600 53.30 bkl Liu, Jiaxin verfasserin aut Collaborative optimization of dynamic grid dispatch with wind power 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Economic dispatch can promote the economic operation of power systems, and reactive power dispatch can ensure the safe and reliable operation of power systems. Essentially different from the related literature with separately optimizing the two dispatches, this paper proposes the collaborative optimization strategy of dynamic grid dispatch to optimize economic dispatch and reactive power dispatch simultaneously. The strategy is devoted to analyzing the internal relationship of the two dispatches, and establishing a collaborative optimization model to complete the collaborative optimization of the two dispatches. Moreover, multi-objective hybrid bat algorithm is improved by an unbalanced power distribution method, which is suitable to solve dynamic grid dispatch problem. Finally, wind power predicted by neural network is integrated in the collaborative optimization of dynamic grid dispatch, and the influence of wind power integration on grid dispatch is studied. The numerical examples on the IEEE 30-bus are provided to demonstrate the superiority of the proposed strategy. Economic dispatch Reactive power dispatch Collaborative optimization Unbalanced power distribution Wind power integration Liu, Yungang verfasserin aut Liang, Huijun verfasserin aut Man, Yongchao verfasserin aut Li, Fengzhong verfasserin aut Li, Wenjuan verfasserin aut Enthalten in International journal of electrical power & energy systems Amsterdam [u.a.] : Elsevier Science, 1979 133 Online-Ressource (DE-627)320411907 (DE-600)2001425-9 (DE-576)259271101 0142-0615 nnns volume:133 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 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_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 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_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_4393 GBV_ILN_4700 53.30 Elektrische Energietechnik: Allgemeines AR 133 |
allfields_unstemmed |
10.1016/j.ijepes.2021.107196 doi (DE-627)ELV006449956 (ELSEVIER)S0142-0615(21)00435-X DE-627 ger DE-627 rda eng 620 DE-600 53.30 bkl Liu, Jiaxin verfasserin aut Collaborative optimization of dynamic grid dispatch with wind power 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Economic dispatch can promote the economic operation of power systems, and reactive power dispatch can ensure the safe and reliable operation of power systems. Essentially different from the related literature with separately optimizing the two dispatches, this paper proposes the collaborative optimization strategy of dynamic grid dispatch to optimize economic dispatch and reactive power dispatch simultaneously. The strategy is devoted to analyzing the internal relationship of the two dispatches, and establishing a collaborative optimization model to complete the collaborative optimization of the two dispatches. Moreover, multi-objective hybrid bat algorithm is improved by an unbalanced power distribution method, which is suitable to solve dynamic grid dispatch problem. Finally, wind power predicted by neural network is integrated in the collaborative optimization of dynamic grid dispatch, and the influence of wind power integration on grid dispatch is studied. The numerical examples on the IEEE 30-bus are provided to demonstrate the superiority of the proposed strategy. Economic dispatch Reactive power dispatch Collaborative optimization Unbalanced power distribution Wind power integration Liu, Yungang verfasserin aut Liang, Huijun verfasserin aut Man, Yongchao verfasserin aut Li, Fengzhong verfasserin aut Li, Wenjuan verfasserin aut Enthalten in International journal of electrical power & energy systems Amsterdam [u.a.] : Elsevier Science, 1979 133 Online-Ressource (DE-627)320411907 (DE-600)2001425-9 (DE-576)259271101 0142-0615 nnns volume:133 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 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_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 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_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_4393 GBV_ILN_4700 53.30 Elektrische Energietechnik: Allgemeines AR 133 |
allfieldsGer |
10.1016/j.ijepes.2021.107196 doi (DE-627)ELV006449956 (ELSEVIER)S0142-0615(21)00435-X DE-627 ger DE-627 rda eng 620 DE-600 53.30 bkl Liu, Jiaxin verfasserin aut Collaborative optimization of dynamic grid dispatch with wind power 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Economic dispatch can promote the economic operation of power systems, and reactive power dispatch can ensure the safe and reliable operation of power systems. Essentially different from the related literature with separately optimizing the two dispatches, this paper proposes the collaborative optimization strategy of dynamic grid dispatch to optimize economic dispatch and reactive power dispatch simultaneously. The strategy is devoted to analyzing the internal relationship of the two dispatches, and establishing a collaborative optimization model to complete the collaborative optimization of the two dispatches. Moreover, multi-objective hybrid bat algorithm is improved by an unbalanced power distribution method, which is suitable to solve dynamic grid dispatch problem. Finally, wind power predicted by neural network is integrated in the collaborative optimization of dynamic grid dispatch, and the influence of wind power integration on grid dispatch is studied. The numerical examples on the IEEE 30-bus are provided to demonstrate the superiority of the proposed strategy. Economic dispatch Reactive power dispatch Collaborative optimization Unbalanced power distribution Wind power integration Liu, Yungang verfasserin aut Liang, Huijun verfasserin aut Man, Yongchao verfasserin aut Li, Fengzhong verfasserin aut Li, Wenjuan verfasserin aut Enthalten in International journal of electrical power & energy systems Amsterdam [u.a.] : Elsevier Science, 1979 133 Online-Ressource (DE-627)320411907 (DE-600)2001425-9 (DE-576)259271101 0142-0615 nnns volume:133 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 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_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 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_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_4393 GBV_ILN_4700 53.30 Elektrische Energietechnik: Allgemeines AR 133 |
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10.1016/j.ijepes.2021.107196 doi (DE-627)ELV006449956 (ELSEVIER)S0142-0615(21)00435-X DE-627 ger DE-627 rda eng 620 DE-600 53.30 bkl Liu, Jiaxin verfasserin aut Collaborative optimization of dynamic grid dispatch with wind power 2021 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Economic dispatch can promote the economic operation of power systems, and reactive power dispatch can ensure the safe and reliable operation of power systems. Essentially different from the related literature with separately optimizing the two dispatches, this paper proposes the collaborative optimization strategy of dynamic grid dispatch to optimize economic dispatch and reactive power dispatch simultaneously. The strategy is devoted to analyzing the internal relationship of the two dispatches, and establishing a collaborative optimization model to complete the collaborative optimization of the two dispatches. Moreover, multi-objective hybrid bat algorithm is improved by an unbalanced power distribution method, which is suitable to solve dynamic grid dispatch problem. Finally, wind power predicted by neural network is integrated in the collaborative optimization of dynamic grid dispatch, and the influence of wind power integration on grid dispatch is studied. The numerical examples on the IEEE 30-bus are provided to demonstrate the superiority of the proposed strategy. Economic dispatch Reactive power dispatch Collaborative optimization Unbalanced power distribution Wind power integration Liu, Yungang verfasserin aut Liang, Huijun verfasserin aut Man, Yongchao verfasserin aut Li, Fengzhong verfasserin aut Li, Wenjuan verfasserin aut Enthalten in International journal of electrical power & energy systems Amsterdam [u.a.] : Elsevier Science, 1979 133 Online-Ressource (DE-627)320411907 (DE-600)2001425-9 (DE-576)259271101 0142-0615 nnns volume:133 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 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_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 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_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_4393 GBV_ILN_4700 53.30 Elektrische Energietechnik: Allgemeines AR 133 |
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Economic dispatch Reactive power dispatch Collaborative optimization Unbalanced power distribution Wind power integration |
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International journal of electrical power & energy systems |
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Liu, Jiaxin @@aut@@ Liu, Yungang @@aut@@ Liang, Huijun @@aut@@ Man, Yongchao @@aut@@ Li, Fengzhong @@aut@@ Li, Wenjuan @@aut@@ |
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Liu, Jiaxin ddc 620 bkl 53.30 misc Economic dispatch misc Reactive power dispatch misc Collaborative optimization misc Unbalanced power distribution misc Wind power integration Collaborative optimization of dynamic grid dispatch with wind power |
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620 DE-600 53.30 bkl Collaborative optimization of dynamic grid dispatch with wind power Economic dispatch Reactive power dispatch Collaborative optimization Unbalanced power distribution Wind power integration |
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collaborative optimization of dynamic grid dispatch with wind power |
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Collaborative optimization of dynamic grid dispatch with wind power |
abstract |
Economic dispatch can promote the economic operation of power systems, and reactive power dispatch can ensure the safe and reliable operation of power systems. Essentially different from the related literature with separately optimizing the two dispatches, this paper proposes the collaborative optimization strategy of dynamic grid dispatch to optimize economic dispatch and reactive power dispatch simultaneously. The strategy is devoted to analyzing the internal relationship of the two dispatches, and establishing a collaborative optimization model to complete the collaborative optimization of the two dispatches. Moreover, multi-objective hybrid bat algorithm is improved by an unbalanced power distribution method, which is suitable to solve dynamic grid dispatch problem. Finally, wind power predicted by neural network is integrated in the collaborative optimization of dynamic grid dispatch, and the influence of wind power integration on grid dispatch is studied. The numerical examples on the IEEE 30-bus are provided to demonstrate the superiority of the proposed strategy. |
abstractGer |
Economic dispatch can promote the economic operation of power systems, and reactive power dispatch can ensure the safe and reliable operation of power systems. Essentially different from the related literature with separately optimizing the two dispatches, this paper proposes the collaborative optimization strategy of dynamic grid dispatch to optimize economic dispatch and reactive power dispatch simultaneously. The strategy is devoted to analyzing the internal relationship of the two dispatches, and establishing a collaborative optimization model to complete the collaborative optimization of the two dispatches. Moreover, multi-objective hybrid bat algorithm is improved by an unbalanced power distribution method, which is suitable to solve dynamic grid dispatch problem. Finally, wind power predicted by neural network is integrated in the collaborative optimization of dynamic grid dispatch, and the influence of wind power integration on grid dispatch is studied. The numerical examples on the IEEE 30-bus are provided to demonstrate the superiority of the proposed strategy. |
abstract_unstemmed |
Economic dispatch can promote the economic operation of power systems, and reactive power dispatch can ensure the safe and reliable operation of power systems. Essentially different from the related literature with separately optimizing the two dispatches, this paper proposes the collaborative optimization strategy of dynamic grid dispatch to optimize economic dispatch and reactive power dispatch simultaneously. The strategy is devoted to analyzing the internal relationship of the two dispatches, and establishing a collaborative optimization model to complete the collaborative optimization of the two dispatches. Moreover, multi-objective hybrid bat algorithm is improved by an unbalanced power distribution method, which is suitable to solve dynamic grid dispatch problem. Finally, wind power predicted by neural network is integrated in the collaborative optimization of dynamic grid dispatch, and the influence of wind power integration on grid dispatch is studied. The numerical examples on the IEEE 30-bus are provided to demonstrate the superiority of the proposed strategy. |
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score |
7.402815 |