Determination of key transmission section and strong correlation section based on matrix aggregation algorithm
With the increasing complexity of high-proportion new energy connected to power systems, the volatility and uncertainty of the power system increase, resulting in the changing operation status of the system. The original general sections may become key transmission sections. According to the power f...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Wu, Weirong [verfasserIn] Yang, Dongsheng [verfasserIn] Yu, Ziyang [verfasserIn] Zhou, Bowen [verfasserIn] Lv, Chen [verfasserIn] Gu, Jun [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2023 |
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| Schlagwörter: |
Transmission section characteristics |
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| Übergeordnetes Werk: |
Enthalten in: International journal of electrical power & energy systems - Amsterdam [u.a.] : Elsevier Science, 1979, 153 |
|---|---|
| Übergeordnetes Werk: |
volume:153 |
| DOI / URN: |
10.1016/j.ijepes.2023.109387 |
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| Katalog-ID: |
ELV06180889X |
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| 245 | 1 | 0 | |a Determination of key transmission section and strong correlation section based on matrix aggregation algorithm |
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| 520 | |a With the increasing complexity of high-proportion new energy connected to power systems, the volatility and uncertainty of the power system increase, resulting in the changing operation status of the system. The original general sections may become key transmission sections. According to the power flow characteristics of power systems, this paper proposes an improved matrix aggregation algorithm to determine the initial transmission sections. On this basis, this paper defines an improved comprehensive index based on line outage distribution factor and line load rate. According to the principle of emphasis on detection in the actual power system operation, weight coefficients are considered for the two parameters to determine the key transmission sections. Finally, the correlation between multiple transmission sections is analyzed by quantifying the impact of the trip off line on the power flow transfer of other lines, and the strong correlation section is obtained. Case studies of the IEEE 39 bus system show the validity and effectiveness of the proposed method in this paper. | ||
| 650 | 4 | |a Transmission section characteristics | |
| 650 | 4 | |a Key Transmission Section | |
| 650 | 4 | |a Power flow transfer impact ratio | |
| 650 | 4 | |a Strong correlation section | |
| 700 | 1 | |a Yang, Dongsheng |e verfasserin |4 aut | |
| 700 | 1 | |a Yu, Ziyang |e verfasserin |4 aut | |
| 700 | 1 | |a Zhou, Bowen |e verfasserin |0 (orcid)0000-0002-7400-6603 |4 aut | |
| 700 | 1 | |a Lv, Chen |e verfasserin |4 aut | |
| 700 | 1 | |a Gu, Jun |e verfasserin |4 aut | |
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10.1016/j.ijepes.2023.109387 doi (DE-627)ELV06180889X (ELSEVIER)S0142-0615(23)00444-1 DE-627 ger DE-627 rda eng 620 VZ 53.30 bkl Wu, Weirong verfasserin aut Determination of key transmission section and strong correlation section based on matrix aggregation algorithm 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier With the increasing complexity of high-proportion new energy connected to power systems, the volatility and uncertainty of the power system increase, resulting in the changing operation status of the system. The original general sections may become key transmission sections. According to the power flow characteristics of power systems, this paper proposes an improved matrix aggregation algorithm to determine the initial transmission sections. On this basis, this paper defines an improved comprehensive index based on line outage distribution factor and line load rate. According to the principle of emphasis on detection in the actual power system operation, weight coefficients are considered for the two parameters to determine the key transmission sections. Finally, the correlation between multiple transmission sections is analyzed by quantifying the impact of the trip off line on the power flow transfer of other lines, and the strong correlation section is obtained. Case studies of the IEEE 39 bus system show the validity and effectiveness of the proposed method in this paper. Transmission section characteristics Key Transmission Section Power flow transfer impact ratio Strong correlation section Yang, Dongsheng verfasserin aut Yu, Ziyang verfasserin aut Zhou, Bowen verfasserin (orcid)0000-0002-7400-6603 aut Lv, Chen verfasserin aut Gu, Jun verfasserin aut Enthalten in International journal of electrical power & energy systems Amsterdam [u.a.] : Elsevier Science, 1979 153 Online-Ressource (DE-627)320411907 (DE-600)2001425-9 (DE-576)259271101 0142-0615 nnns volume:153 GBV_USEFLAG_U GBV_ELV SYSFLAG_U 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_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_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_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_2106 GBV_ILN_2110 GBV_ILN_2111 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_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 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_4338 GBV_ILN_4393 GBV_ILN_4700 53.30 Elektrische Energietechnik: Allgemeines VZ AR 153 |
| spelling |
10.1016/j.ijepes.2023.109387 doi (DE-627)ELV06180889X (ELSEVIER)S0142-0615(23)00444-1 DE-627 ger DE-627 rda eng 620 VZ 53.30 bkl Wu, Weirong verfasserin aut Determination of key transmission section and strong correlation section based on matrix aggregation algorithm 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier With the increasing complexity of high-proportion new energy connected to power systems, the volatility and uncertainty of the power system increase, resulting in the changing operation status of the system. The original general sections may become key transmission sections. According to the power flow characteristics of power systems, this paper proposes an improved matrix aggregation algorithm to determine the initial transmission sections. On this basis, this paper defines an improved comprehensive index based on line outage distribution factor and line load rate. According to the principle of emphasis on detection in the actual power system operation, weight coefficients are considered for the two parameters to determine the key transmission sections. Finally, the correlation between multiple transmission sections is analyzed by quantifying the impact of the trip off line on the power flow transfer of other lines, and the strong correlation section is obtained. Case studies of the IEEE 39 bus system show the validity and effectiveness of the proposed method in this paper. Transmission section characteristics Key Transmission Section Power flow transfer impact ratio Strong correlation section Yang, Dongsheng verfasserin aut Yu, Ziyang verfasserin aut Zhou, Bowen verfasserin (orcid)0000-0002-7400-6603 aut Lv, Chen verfasserin aut Gu, Jun verfasserin aut Enthalten in International journal of electrical power & energy systems Amsterdam [u.a.] : Elsevier Science, 1979 153 Online-Ressource (DE-627)320411907 (DE-600)2001425-9 (DE-576)259271101 0142-0615 nnns volume:153 GBV_USEFLAG_U GBV_ELV SYSFLAG_U 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_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_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_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_2106 GBV_ILN_2110 GBV_ILN_2111 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_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 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_4338 GBV_ILN_4393 GBV_ILN_4700 53.30 Elektrische Energietechnik: Allgemeines VZ AR 153 |
| allfields_unstemmed |
10.1016/j.ijepes.2023.109387 doi (DE-627)ELV06180889X (ELSEVIER)S0142-0615(23)00444-1 DE-627 ger DE-627 rda eng 620 VZ 53.30 bkl Wu, Weirong verfasserin aut Determination of key transmission section and strong correlation section based on matrix aggregation algorithm 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier With the increasing complexity of high-proportion new energy connected to power systems, the volatility and uncertainty of the power system increase, resulting in the changing operation status of the system. The original general sections may become key transmission sections. According to the power flow characteristics of power systems, this paper proposes an improved matrix aggregation algorithm to determine the initial transmission sections. On this basis, this paper defines an improved comprehensive index based on line outage distribution factor and line load rate. According to the principle of emphasis on detection in the actual power system operation, weight coefficients are considered for the two parameters to determine the key transmission sections. Finally, the correlation between multiple transmission sections is analyzed by quantifying the impact of the trip off line on the power flow transfer of other lines, and the strong correlation section is obtained. Case studies of the IEEE 39 bus system show the validity and effectiveness of the proposed method in this paper. Transmission section characteristics Key Transmission Section Power flow transfer impact ratio Strong correlation section Yang, Dongsheng verfasserin aut Yu, Ziyang verfasserin aut Zhou, Bowen verfasserin (orcid)0000-0002-7400-6603 aut Lv, Chen verfasserin aut Gu, Jun verfasserin aut Enthalten in International journal of electrical power & energy systems Amsterdam [u.a.] : Elsevier Science, 1979 153 Online-Ressource (DE-627)320411907 (DE-600)2001425-9 (DE-576)259271101 0142-0615 nnns volume:153 GBV_USEFLAG_U GBV_ELV SYSFLAG_U 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_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_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_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_2106 GBV_ILN_2110 GBV_ILN_2111 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_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 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_4338 GBV_ILN_4393 GBV_ILN_4700 53.30 Elektrische Energietechnik: Allgemeines VZ AR 153 |
| allfieldsGer |
10.1016/j.ijepes.2023.109387 doi (DE-627)ELV06180889X (ELSEVIER)S0142-0615(23)00444-1 DE-627 ger DE-627 rda eng 620 VZ 53.30 bkl Wu, Weirong verfasserin aut Determination of key transmission section and strong correlation section based on matrix aggregation algorithm 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier With the increasing complexity of high-proportion new energy connected to power systems, the volatility and uncertainty of the power system increase, resulting in the changing operation status of the system. The original general sections may become key transmission sections. According to the power flow characteristics of power systems, this paper proposes an improved matrix aggregation algorithm to determine the initial transmission sections. On this basis, this paper defines an improved comprehensive index based on line outage distribution factor and line load rate. According to the principle of emphasis on detection in the actual power system operation, weight coefficients are considered for the two parameters to determine the key transmission sections. Finally, the correlation between multiple transmission sections is analyzed by quantifying the impact of the trip off line on the power flow transfer of other lines, and the strong correlation section is obtained. Case studies of the IEEE 39 bus system show the validity and effectiveness of the proposed method in this paper. Transmission section characteristics Key Transmission Section Power flow transfer impact ratio Strong correlation section Yang, Dongsheng verfasserin aut Yu, Ziyang verfasserin aut Zhou, Bowen verfasserin (orcid)0000-0002-7400-6603 aut Lv, Chen verfasserin aut Gu, Jun verfasserin aut Enthalten in International journal of electrical power & energy systems Amsterdam [u.a.] : Elsevier Science, 1979 153 Online-Ressource (DE-627)320411907 (DE-600)2001425-9 (DE-576)259271101 0142-0615 nnns volume:153 GBV_USEFLAG_U GBV_ELV SYSFLAG_U 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_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_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_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_2106 GBV_ILN_2110 GBV_ILN_2111 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_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 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_4338 GBV_ILN_4393 GBV_ILN_4700 53.30 Elektrische Energietechnik: Allgemeines VZ AR 153 |
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Determination of key transmission section and strong correlation section based on matrix aggregation algorithm |
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Determination of key transmission section and strong correlation section based on matrix aggregation algorithm |
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Wu, Weirong |
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International journal of electrical power & energy systems |
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Wu, Weirong Yang, Dongsheng Yu, Ziyang Zhou, Bowen Lv, Chen Gu, Jun |
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10.1016/j.ijepes.2023.109387 |
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determination of key transmission section and strong correlation section based on matrix aggregation algorithm |
| title_auth |
Determination of key transmission section and strong correlation section based on matrix aggregation algorithm |
| abstract |
With the increasing complexity of high-proportion new energy connected to power systems, the volatility and uncertainty of the power system increase, resulting in the changing operation status of the system. The original general sections may become key transmission sections. According to the power flow characteristics of power systems, this paper proposes an improved matrix aggregation algorithm to determine the initial transmission sections. On this basis, this paper defines an improved comprehensive index based on line outage distribution factor and line load rate. According to the principle of emphasis on detection in the actual power system operation, weight coefficients are considered for the two parameters to determine the key transmission sections. Finally, the correlation between multiple transmission sections is analyzed by quantifying the impact of the trip off line on the power flow transfer of other lines, and the strong correlation section is obtained. Case studies of the IEEE 39 bus system show the validity and effectiveness of the proposed method in this paper. |
| abstractGer |
With the increasing complexity of high-proportion new energy connected to power systems, the volatility and uncertainty of the power system increase, resulting in the changing operation status of the system. The original general sections may become key transmission sections. According to the power flow characteristics of power systems, this paper proposes an improved matrix aggregation algorithm to determine the initial transmission sections. On this basis, this paper defines an improved comprehensive index based on line outage distribution factor and line load rate. According to the principle of emphasis on detection in the actual power system operation, weight coefficients are considered for the two parameters to determine the key transmission sections. Finally, the correlation between multiple transmission sections is analyzed by quantifying the impact of the trip off line on the power flow transfer of other lines, and the strong correlation section is obtained. Case studies of the IEEE 39 bus system show the validity and effectiveness of the proposed method in this paper. |
| abstract_unstemmed |
With the increasing complexity of high-proportion new energy connected to power systems, the volatility and uncertainty of the power system increase, resulting in the changing operation status of the system. The original general sections may become key transmission sections. According to the power flow characteristics of power systems, this paper proposes an improved matrix aggregation algorithm to determine the initial transmission sections. On this basis, this paper defines an improved comprehensive index based on line outage distribution factor and line load rate. According to the principle of emphasis on detection in the actual power system operation, weight coefficients are considered for the two parameters to determine the key transmission sections. Finally, the correlation between multiple transmission sections is analyzed by quantifying the impact of the trip off line on the power flow transfer of other lines, and the strong correlation section is obtained. Case studies of the IEEE 39 bus system show the validity and effectiveness of the proposed method in this paper. |
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Determination of key transmission section and strong correlation section based on matrix aggregation algorithm |
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