Approximate dynamic programming based supplementary reactive power control for DFIG wind farm to enhance power system stability
Reactive power control of doubly fed induction generators (DFIGs) has been a heated topic in transient stability control of power systems in recent years. By using a new online supplementary learning control (OSLC) approach based on the theory of approximate dynamic programming (ADP), this paper dev...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Guo, Wentao [verfasserIn] |
|---|
| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2015transfer abstract |
|---|
| Schlagwörter: |
Approximate dynamic programming |
|---|
| Umfang: |
11 |
|---|
| Übergeordnetes Werk: |
Enthalten in: The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast - Liu, Yang ELSEVIER, 2018, an international journal, Amsterdam |
|---|---|
| Übergeordnetes Werk: |
volume:170 ; year:2015 ; day:25 ; month:12 ; pages:417-427 ; extent:11 |
| Links: |
|---|
| DOI / URN: |
10.1016/j.neucom.2015.03.089 |
|---|
| Katalog-ID: |
ELV013187147 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | ELV013187147 | ||
| 003 | DE-627 | ||
| 005 | 20230625111715.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 180602s2015 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1016/j.neucom.2015.03.089 |2 doi | |
| 028 | 5 | 2 | |a GBVA2015014000024.pica |
| 035 | |a (DE-627)ELV013187147 | ||
| 035 | |a (ELSEVIER)S0925-2312(15)00870-X | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 082 | 0 | |a 610 | |
| 082 | 0 | 4 | |a 610 |q DE-600 |
| 082 | 0 | 4 | |a 570 |q VZ |
| 084 | |a BIODIV |q DE-30 |2 fid | ||
| 084 | |a 35.70 |2 bkl | ||
| 084 | |a 42.12 |2 bkl | ||
| 100 | 1 | |a Guo, Wentao |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Approximate dynamic programming based supplementary reactive power control for DFIG wind farm to enhance power system stability |
| 264 | 1 | |c 2015transfer abstract | |
| 300 | |a 11 | ||
| 336 | |a nicht spezifiziert |b zzz |2 rdacontent | ||
| 337 | |a nicht spezifiziert |b z |2 rdamedia | ||
| 338 | |a nicht spezifiziert |b zu |2 rdacarrier | ||
| 520 | |a Reactive power control of doubly fed induction generators (DFIGs) has been a heated topic in transient stability control of power systems in recent years. By using a new online supplementary learning control (OSLC) approach based on the theory of approximate dynamic programming (ADP), this paper develops an optimal and adaptive design method for the supplementary reactive power control of DFIGs to improve transient stability of power systems. To augment the reactive power command of the rotor-side converter (RSC), a supplementary controller is designed to reduce voltage sag at the common coupling point during a fault, and to mitigate active power oscillation of the wind farm after a fault. As a result, the transient stability of both DFIGs and the power system is enhanced. For the supplementary controller design, an action dependent cost function is introduced to make the OSLC model-free and completely data-driven. Furthermore, a least-squares based policy iteration algorithm is employed to train the supplementary controller with convergence and stability guarantee. By using such techniques, the supplementary reactive power controller can be trained directly from data measurements, and therefore, can adapt to system or external changes without an explicit offline system identification process. Simulations carried out in Power System Computer Aided Design/ Electro Magnetic Transient in DC System (PSCAD/EMTDC) show that the OSLC based supplementary reactive power controller can significantly improve the transient performance of the wind farm and enhance the transient stability of the power system after sever faults. | ||
| 520 | |a Reactive power control of doubly fed induction generators (DFIGs) has been a heated topic in transient stability control of power systems in recent years. By using a new online supplementary learning control (OSLC) approach based on the theory of approximate dynamic programming (ADP), this paper develops an optimal and adaptive design method for the supplementary reactive power control of DFIGs to improve transient stability of power systems. To augment the reactive power command of the rotor-side converter (RSC), a supplementary controller is designed to reduce voltage sag at the common coupling point during a fault, and to mitigate active power oscillation of the wind farm after a fault. As a result, the transient stability of both DFIGs and the power system is enhanced. For the supplementary controller design, an action dependent cost function is introduced to make the OSLC model-free and completely data-driven. Furthermore, a least-squares based policy iteration algorithm is employed to train the supplementary controller with convergence and stability guarantee. By using such techniques, the supplementary reactive power controller can be trained directly from data measurements, and therefore, can adapt to system or external changes without an explicit offline system identification process. Simulations carried out in Power System Computer Aided Design/ Electro Magnetic Transient in DC System (PSCAD/EMTDC) show that the OSLC based supplementary reactive power controller can significantly improve the transient performance of the wind farm and enhance the transient stability of the power system after sever faults. | ||
| 650 | 7 | |a Reactive power control |2 Elsevier | |
| 650 | 7 | |a Approximate dynamic programming |2 Elsevier | |
| 650 | 7 | |a Online supplementary learning control |2 Elsevier | |
| 650 | 7 | |a Doubly fed induction generator (DFIG) |2 Elsevier | |
| 700 | 1 | |a Liu, Feng |4 oth | |
| 700 | 1 | |a Si, Jennie |4 oth | |
| 700 | 1 | |a He, Dawei |4 oth | |
| 700 | 1 | |a Harley, Ronald |4 oth | |
| 700 | 1 | |a Mei, Shengwei |4 oth | |
| 773 | 0 | 8 | |i Enthalten in |n Elsevier |a Liu, Yang ELSEVIER |t The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast |d 2018 |d an international journal |g Amsterdam |w (DE-627)ELV002603926 |
| 773 | 1 | 8 | |g volume:170 |g year:2015 |g day:25 |g month:12 |g pages:417-427 |g extent:11 |
| 856 | 4 | 0 | |u https://doi.org/10.1016/j.neucom.2015.03.089 |3 Volltext |
| 912 | |a GBV_USEFLAG_U | ||
| 912 | |a GBV_ELV | ||
| 912 | |a SYSFLAG_U | ||
| 912 | |a FID-BIODIV | ||
| 912 | |a SSG-OLC-PHA | ||
| 936 | b | k | |a 35.70 |j Biochemie: Allgemeines |q VZ |
| 936 | b | k | |a 42.12 |j Biophysik |q VZ |
| 951 | |a AR | ||
| 952 | |d 170 |j 2015 |b 25 |c 1225 |h 417-427 |g 11 | ||
| 953 | |2 045F |a 610 | ||
| author_variant |
w g wg |
|---|---|
| matchkey_str |
guowentaoliufengsijenniehedaweiharleyron:2015----:prxmtdnmcrgamnbsdupeetrratvpwrotofrfgida |
| hierarchy_sort_str |
2015transfer abstract |
| bklnumber |
35.70 42.12 |
| publishDate |
2015 |
| allfields |
10.1016/j.neucom.2015.03.089 doi GBVA2015014000024.pica (DE-627)ELV013187147 (ELSEVIER)S0925-2312(15)00870-X DE-627 ger DE-627 rakwb eng 610 610 DE-600 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl Guo, Wentao verfasserin aut Approximate dynamic programming based supplementary reactive power control for DFIG wind farm to enhance power system stability 2015transfer abstract 11 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Reactive power control of doubly fed induction generators (DFIGs) has been a heated topic in transient stability control of power systems in recent years. By using a new online supplementary learning control (OSLC) approach based on the theory of approximate dynamic programming (ADP), this paper develops an optimal and adaptive design method for the supplementary reactive power control of DFIGs to improve transient stability of power systems. To augment the reactive power command of the rotor-side converter (RSC), a supplementary controller is designed to reduce voltage sag at the common coupling point during a fault, and to mitigate active power oscillation of the wind farm after a fault. As a result, the transient stability of both DFIGs and the power system is enhanced. For the supplementary controller design, an action dependent cost function is introduced to make the OSLC model-free and completely data-driven. Furthermore, a least-squares based policy iteration algorithm is employed to train the supplementary controller with convergence and stability guarantee. By using such techniques, the supplementary reactive power controller can be trained directly from data measurements, and therefore, can adapt to system or external changes without an explicit offline system identification process. Simulations carried out in Power System Computer Aided Design/ Electro Magnetic Transient in DC System (PSCAD/EMTDC) show that the OSLC based supplementary reactive power controller can significantly improve the transient performance of the wind farm and enhance the transient stability of the power system after sever faults. Reactive power control of doubly fed induction generators (DFIGs) has been a heated topic in transient stability control of power systems in recent years. By using a new online supplementary learning control (OSLC) approach based on the theory of approximate dynamic programming (ADP), this paper develops an optimal and adaptive design method for the supplementary reactive power control of DFIGs to improve transient stability of power systems. To augment the reactive power command of the rotor-side converter (RSC), a supplementary controller is designed to reduce voltage sag at the common coupling point during a fault, and to mitigate active power oscillation of the wind farm after a fault. As a result, the transient stability of both DFIGs and the power system is enhanced. For the supplementary controller design, an action dependent cost function is introduced to make the OSLC model-free and completely data-driven. Furthermore, a least-squares based policy iteration algorithm is employed to train the supplementary controller with convergence and stability guarantee. By using such techniques, the supplementary reactive power controller can be trained directly from data measurements, and therefore, can adapt to system or external changes without an explicit offline system identification process. Simulations carried out in Power System Computer Aided Design/ Electro Magnetic Transient in DC System (PSCAD/EMTDC) show that the OSLC based supplementary reactive power controller can significantly improve the transient performance of the wind farm and enhance the transient stability of the power system after sever faults. Reactive power control Elsevier Approximate dynamic programming Elsevier Online supplementary learning control Elsevier Doubly fed induction generator (DFIG) Elsevier Liu, Feng oth Si, Jennie oth He, Dawei oth Harley, Ronald oth Mei, Shengwei oth Enthalten in Elsevier Liu, Yang ELSEVIER The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast 2018 an international journal Amsterdam (DE-627)ELV002603926 volume:170 year:2015 day:25 month:12 pages:417-427 extent:11 https://doi.org/10.1016/j.neucom.2015.03.089 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ AR 170 2015 25 1225 417-427 11 045F 610 |
| spelling |
10.1016/j.neucom.2015.03.089 doi GBVA2015014000024.pica (DE-627)ELV013187147 (ELSEVIER)S0925-2312(15)00870-X DE-627 ger DE-627 rakwb eng 610 610 DE-600 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl Guo, Wentao verfasserin aut Approximate dynamic programming based supplementary reactive power control for DFIG wind farm to enhance power system stability 2015transfer abstract 11 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Reactive power control of doubly fed induction generators (DFIGs) has been a heated topic in transient stability control of power systems in recent years. By using a new online supplementary learning control (OSLC) approach based on the theory of approximate dynamic programming (ADP), this paper develops an optimal and adaptive design method for the supplementary reactive power control of DFIGs to improve transient stability of power systems. To augment the reactive power command of the rotor-side converter (RSC), a supplementary controller is designed to reduce voltage sag at the common coupling point during a fault, and to mitigate active power oscillation of the wind farm after a fault. As a result, the transient stability of both DFIGs and the power system is enhanced. For the supplementary controller design, an action dependent cost function is introduced to make the OSLC model-free and completely data-driven. Furthermore, a least-squares based policy iteration algorithm is employed to train the supplementary controller with convergence and stability guarantee. By using such techniques, the supplementary reactive power controller can be trained directly from data measurements, and therefore, can adapt to system or external changes without an explicit offline system identification process. Simulations carried out in Power System Computer Aided Design/ Electro Magnetic Transient in DC System (PSCAD/EMTDC) show that the OSLC based supplementary reactive power controller can significantly improve the transient performance of the wind farm and enhance the transient stability of the power system after sever faults. Reactive power control of doubly fed induction generators (DFIGs) has been a heated topic in transient stability control of power systems in recent years. By using a new online supplementary learning control (OSLC) approach based on the theory of approximate dynamic programming (ADP), this paper develops an optimal and adaptive design method for the supplementary reactive power control of DFIGs to improve transient stability of power systems. To augment the reactive power command of the rotor-side converter (RSC), a supplementary controller is designed to reduce voltage sag at the common coupling point during a fault, and to mitigate active power oscillation of the wind farm after a fault. As a result, the transient stability of both DFIGs and the power system is enhanced. For the supplementary controller design, an action dependent cost function is introduced to make the OSLC model-free and completely data-driven. Furthermore, a least-squares based policy iteration algorithm is employed to train the supplementary controller with convergence and stability guarantee. By using such techniques, the supplementary reactive power controller can be trained directly from data measurements, and therefore, can adapt to system or external changes without an explicit offline system identification process. Simulations carried out in Power System Computer Aided Design/ Electro Magnetic Transient in DC System (PSCAD/EMTDC) show that the OSLC based supplementary reactive power controller can significantly improve the transient performance of the wind farm and enhance the transient stability of the power system after sever faults. Reactive power control Elsevier Approximate dynamic programming Elsevier Online supplementary learning control Elsevier Doubly fed induction generator (DFIG) Elsevier Liu, Feng oth Si, Jennie oth He, Dawei oth Harley, Ronald oth Mei, Shengwei oth Enthalten in Elsevier Liu, Yang ELSEVIER The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast 2018 an international journal Amsterdam (DE-627)ELV002603926 volume:170 year:2015 day:25 month:12 pages:417-427 extent:11 https://doi.org/10.1016/j.neucom.2015.03.089 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ AR 170 2015 25 1225 417-427 11 045F 610 |
| allfields_unstemmed |
10.1016/j.neucom.2015.03.089 doi GBVA2015014000024.pica (DE-627)ELV013187147 (ELSEVIER)S0925-2312(15)00870-X DE-627 ger DE-627 rakwb eng 610 610 DE-600 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl Guo, Wentao verfasserin aut Approximate dynamic programming based supplementary reactive power control for DFIG wind farm to enhance power system stability 2015transfer abstract 11 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Reactive power control of doubly fed induction generators (DFIGs) has been a heated topic in transient stability control of power systems in recent years. By using a new online supplementary learning control (OSLC) approach based on the theory of approximate dynamic programming (ADP), this paper develops an optimal and adaptive design method for the supplementary reactive power control of DFIGs to improve transient stability of power systems. To augment the reactive power command of the rotor-side converter (RSC), a supplementary controller is designed to reduce voltage sag at the common coupling point during a fault, and to mitigate active power oscillation of the wind farm after a fault. As a result, the transient stability of both DFIGs and the power system is enhanced. For the supplementary controller design, an action dependent cost function is introduced to make the OSLC model-free and completely data-driven. Furthermore, a least-squares based policy iteration algorithm is employed to train the supplementary controller with convergence and stability guarantee. By using such techniques, the supplementary reactive power controller can be trained directly from data measurements, and therefore, can adapt to system or external changes without an explicit offline system identification process. Simulations carried out in Power System Computer Aided Design/ Electro Magnetic Transient in DC System (PSCAD/EMTDC) show that the OSLC based supplementary reactive power controller can significantly improve the transient performance of the wind farm and enhance the transient stability of the power system after sever faults. Reactive power control of doubly fed induction generators (DFIGs) has been a heated topic in transient stability control of power systems in recent years. By using a new online supplementary learning control (OSLC) approach based on the theory of approximate dynamic programming (ADP), this paper develops an optimal and adaptive design method for the supplementary reactive power control of DFIGs to improve transient stability of power systems. To augment the reactive power command of the rotor-side converter (RSC), a supplementary controller is designed to reduce voltage sag at the common coupling point during a fault, and to mitigate active power oscillation of the wind farm after a fault. As a result, the transient stability of both DFIGs and the power system is enhanced. For the supplementary controller design, an action dependent cost function is introduced to make the OSLC model-free and completely data-driven. Furthermore, a least-squares based policy iteration algorithm is employed to train the supplementary controller with convergence and stability guarantee. By using such techniques, the supplementary reactive power controller can be trained directly from data measurements, and therefore, can adapt to system or external changes without an explicit offline system identification process. Simulations carried out in Power System Computer Aided Design/ Electro Magnetic Transient in DC System (PSCAD/EMTDC) show that the OSLC based supplementary reactive power controller can significantly improve the transient performance of the wind farm and enhance the transient stability of the power system after sever faults. Reactive power control Elsevier Approximate dynamic programming Elsevier Online supplementary learning control Elsevier Doubly fed induction generator (DFIG) Elsevier Liu, Feng oth Si, Jennie oth He, Dawei oth Harley, Ronald oth Mei, Shengwei oth Enthalten in Elsevier Liu, Yang ELSEVIER The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast 2018 an international journal Amsterdam (DE-627)ELV002603926 volume:170 year:2015 day:25 month:12 pages:417-427 extent:11 https://doi.org/10.1016/j.neucom.2015.03.089 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ AR 170 2015 25 1225 417-427 11 045F 610 |
| allfieldsGer |
10.1016/j.neucom.2015.03.089 doi GBVA2015014000024.pica (DE-627)ELV013187147 (ELSEVIER)S0925-2312(15)00870-X DE-627 ger DE-627 rakwb eng 610 610 DE-600 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl Guo, Wentao verfasserin aut Approximate dynamic programming based supplementary reactive power control for DFIG wind farm to enhance power system stability 2015transfer abstract 11 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Reactive power control of doubly fed induction generators (DFIGs) has been a heated topic in transient stability control of power systems in recent years. By using a new online supplementary learning control (OSLC) approach based on the theory of approximate dynamic programming (ADP), this paper develops an optimal and adaptive design method for the supplementary reactive power control of DFIGs to improve transient stability of power systems. To augment the reactive power command of the rotor-side converter (RSC), a supplementary controller is designed to reduce voltage sag at the common coupling point during a fault, and to mitigate active power oscillation of the wind farm after a fault. As a result, the transient stability of both DFIGs and the power system is enhanced. For the supplementary controller design, an action dependent cost function is introduced to make the OSLC model-free and completely data-driven. Furthermore, a least-squares based policy iteration algorithm is employed to train the supplementary controller with convergence and stability guarantee. By using such techniques, the supplementary reactive power controller can be trained directly from data measurements, and therefore, can adapt to system or external changes without an explicit offline system identification process. Simulations carried out in Power System Computer Aided Design/ Electro Magnetic Transient in DC System (PSCAD/EMTDC) show that the OSLC based supplementary reactive power controller can significantly improve the transient performance of the wind farm and enhance the transient stability of the power system after sever faults. Reactive power control of doubly fed induction generators (DFIGs) has been a heated topic in transient stability control of power systems in recent years. By using a new online supplementary learning control (OSLC) approach based on the theory of approximate dynamic programming (ADP), this paper develops an optimal and adaptive design method for the supplementary reactive power control of DFIGs to improve transient stability of power systems. To augment the reactive power command of the rotor-side converter (RSC), a supplementary controller is designed to reduce voltage sag at the common coupling point during a fault, and to mitigate active power oscillation of the wind farm after a fault. As a result, the transient stability of both DFIGs and the power system is enhanced. For the supplementary controller design, an action dependent cost function is introduced to make the OSLC model-free and completely data-driven. Furthermore, a least-squares based policy iteration algorithm is employed to train the supplementary controller with convergence and stability guarantee. By using such techniques, the supplementary reactive power controller can be trained directly from data measurements, and therefore, can adapt to system or external changes without an explicit offline system identification process. Simulations carried out in Power System Computer Aided Design/ Electro Magnetic Transient in DC System (PSCAD/EMTDC) show that the OSLC based supplementary reactive power controller can significantly improve the transient performance of the wind farm and enhance the transient stability of the power system after sever faults. Reactive power control Elsevier Approximate dynamic programming Elsevier Online supplementary learning control Elsevier Doubly fed induction generator (DFIG) Elsevier Liu, Feng oth Si, Jennie oth He, Dawei oth Harley, Ronald oth Mei, Shengwei oth Enthalten in Elsevier Liu, Yang ELSEVIER The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast 2018 an international journal Amsterdam (DE-627)ELV002603926 volume:170 year:2015 day:25 month:12 pages:417-427 extent:11 https://doi.org/10.1016/j.neucom.2015.03.089 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ AR 170 2015 25 1225 417-427 11 045F 610 |
| allfieldsSound |
10.1016/j.neucom.2015.03.089 doi GBVA2015014000024.pica (DE-627)ELV013187147 (ELSEVIER)S0925-2312(15)00870-X DE-627 ger DE-627 rakwb eng 610 610 DE-600 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl Guo, Wentao verfasserin aut Approximate dynamic programming based supplementary reactive power control for DFIG wind farm to enhance power system stability 2015transfer abstract 11 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Reactive power control of doubly fed induction generators (DFIGs) has been a heated topic in transient stability control of power systems in recent years. By using a new online supplementary learning control (OSLC) approach based on the theory of approximate dynamic programming (ADP), this paper develops an optimal and adaptive design method for the supplementary reactive power control of DFIGs to improve transient stability of power systems. To augment the reactive power command of the rotor-side converter (RSC), a supplementary controller is designed to reduce voltage sag at the common coupling point during a fault, and to mitigate active power oscillation of the wind farm after a fault. As a result, the transient stability of both DFIGs and the power system is enhanced. For the supplementary controller design, an action dependent cost function is introduced to make the OSLC model-free and completely data-driven. Furthermore, a least-squares based policy iteration algorithm is employed to train the supplementary controller with convergence and stability guarantee. By using such techniques, the supplementary reactive power controller can be trained directly from data measurements, and therefore, can adapt to system or external changes without an explicit offline system identification process. Simulations carried out in Power System Computer Aided Design/ Electro Magnetic Transient in DC System (PSCAD/EMTDC) show that the OSLC based supplementary reactive power controller can significantly improve the transient performance of the wind farm and enhance the transient stability of the power system after sever faults. Reactive power control of doubly fed induction generators (DFIGs) has been a heated topic in transient stability control of power systems in recent years. By using a new online supplementary learning control (OSLC) approach based on the theory of approximate dynamic programming (ADP), this paper develops an optimal and adaptive design method for the supplementary reactive power control of DFIGs to improve transient stability of power systems. To augment the reactive power command of the rotor-side converter (RSC), a supplementary controller is designed to reduce voltage sag at the common coupling point during a fault, and to mitigate active power oscillation of the wind farm after a fault. As a result, the transient stability of both DFIGs and the power system is enhanced. For the supplementary controller design, an action dependent cost function is introduced to make the OSLC model-free and completely data-driven. Furthermore, a least-squares based policy iteration algorithm is employed to train the supplementary controller with convergence and stability guarantee. By using such techniques, the supplementary reactive power controller can be trained directly from data measurements, and therefore, can adapt to system or external changes without an explicit offline system identification process. Simulations carried out in Power System Computer Aided Design/ Electro Magnetic Transient in DC System (PSCAD/EMTDC) show that the OSLC based supplementary reactive power controller can significantly improve the transient performance of the wind farm and enhance the transient stability of the power system after sever faults. Reactive power control Elsevier Approximate dynamic programming Elsevier Online supplementary learning control Elsevier Doubly fed induction generator (DFIG) Elsevier Liu, Feng oth Si, Jennie oth He, Dawei oth Harley, Ronald oth Mei, Shengwei oth Enthalten in Elsevier Liu, Yang ELSEVIER The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast 2018 an international journal Amsterdam (DE-627)ELV002603926 volume:170 year:2015 day:25 month:12 pages:417-427 extent:11 https://doi.org/10.1016/j.neucom.2015.03.089 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ AR 170 2015 25 1225 417-427 11 045F 610 |
| language |
English |
| source |
Enthalten in The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast Amsterdam volume:170 year:2015 day:25 month:12 pages:417-427 extent:11 |
| sourceStr |
Enthalten in The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast Amsterdam volume:170 year:2015 day:25 month:12 pages:417-427 extent:11 |
| format_phy_str_mv |
Article |
| bklname |
Biochemie: Allgemeines Biophysik |
| institution |
findex.gbv.de |
| topic_facet |
Reactive power control Approximate dynamic programming Online supplementary learning control Doubly fed induction generator (DFIG) |
| dewey-raw |
610 |
| isfreeaccess_bool |
false |
| container_title |
The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast |
| authorswithroles_txt_mv |
Guo, Wentao @@aut@@ Liu, Feng @@oth@@ Si, Jennie @@oth@@ He, Dawei @@oth@@ Harley, Ronald @@oth@@ Mei, Shengwei @@oth@@ |
| publishDateDaySort_date |
2015-01-25T00:00:00Z |
| hierarchy_top_id |
ELV002603926 |
| dewey-sort |
3610 |
| id |
ELV013187147 |
| language_de |
englisch |
| fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV013187147</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230625111715.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">180602s2015 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.neucom.2015.03.089</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">GBVA2015014000024.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV013187147</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0925-2312(15)00870-X</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="082" ind1="0" ind2=" "><subfield code="a">610</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="q">DE-600</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">570</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">BIODIV</subfield><subfield code="q">DE-30</subfield><subfield code="2">fid</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">35.70</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">42.12</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Guo, Wentao</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Approximate dynamic programming based supplementary reactive power control for DFIG wind farm to enhance power system stability</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2015transfer abstract</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">11</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Reactive power control of doubly fed induction generators (DFIGs) has been a heated topic in transient stability control of power systems in recent years. By using a new online supplementary learning control (OSLC) approach based on the theory of approximate dynamic programming (ADP), this paper develops an optimal and adaptive design method for the supplementary reactive power control of DFIGs to improve transient stability of power systems. To augment the reactive power command of the rotor-side converter (RSC), a supplementary controller is designed to reduce voltage sag at the common coupling point during a fault, and to mitigate active power oscillation of the wind farm after a fault. As a result, the transient stability of both DFIGs and the power system is enhanced. For the supplementary controller design, an action dependent cost function is introduced to make the OSLC model-free and completely data-driven. Furthermore, a least-squares based policy iteration algorithm is employed to train the supplementary controller with convergence and stability guarantee. By using such techniques, the supplementary reactive power controller can be trained directly from data measurements, and therefore, can adapt to system or external changes without an explicit offline system identification process. Simulations carried out in Power System Computer Aided Design/ Electro Magnetic Transient in DC System (PSCAD/EMTDC) show that the OSLC based supplementary reactive power controller can significantly improve the transient performance of the wind farm and enhance the transient stability of the power system after sever faults.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Reactive power control of doubly fed induction generators (DFIGs) has been a heated topic in transient stability control of power systems in recent years. By using a new online supplementary learning control (OSLC) approach based on the theory of approximate dynamic programming (ADP), this paper develops an optimal and adaptive design method for the supplementary reactive power control of DFIGs to improve transient stability of power systems. To augment the reactive power command of the rotor-side converter (RSC), a supplementary controller is designed to reduce voltage sag at the common coupling point during a fault, and to mitigate active power oscillation of the wind farm after a fault. As a result, the transient stability of both DFIGs and the power system is enhanced. For the supplementary controller design, an action dependent cost function is introduced to make the OSLC model-free and completely data-driven. Furthermore, a least-squares based policy iteration algorithm is employed to train the supplementary controller with convergence and stability guarantee. By using such techniques, the supplementary reactive power controller can be trained directly from data measurements, and therefore, can adapt to system or external changes without an explicit offline system identification process. Simulations carried out in Power System Computer Aided Design/ Electro Magnetic Transient in DC System (PSCAD/EMTDC) show that the OSLC based supplementary reactive power controller can significantly improve the transient performance of the wind farm and enhance the transient stability of the power system after sever faults.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Reactive power control</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Approximate dynamic programming</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Online supplementary learning control</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Doubly fed induction generator (DFIG)</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Liu, Feng</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Si, Jennie</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">He, Dawei</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Harley, Ronald</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Mei, Shengwei</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier</subfield><subfield code="a">Liu, Yang ELSEVIER</subfield><subfield code="t">The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast</subfield><subfield code="d">2018</subfield><subfield code="d">an international journal</subfield><subfield code="g">Amsterdam</subfield><subfield code="w">(DE-627)ELV002603926</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:170</subfield><subfield code="g">year:2015</subfield><subfield code="g">day:25</subfield><subfield code="g">month:12</subfield><subfield code="g">pages:417-427</subfield><subfield code="g">extent:11</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.neucom.2015.03.089</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">FID-BIODIV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">35.70</subfield><subfield code="j">Biochemie: Allgemeines</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">42.12</subfield><subfield code="j">Biophysik</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">170</subfield><subfield code="j">2015</subfield><subfield code="b">25</subfield><subfield code="c">1225</subfield><subfield code="h">417-427</subfield><subfield code="g">11</subfield></datafield><datafield tag="953" ind1=" " ind2=" "><subfield code="2">045F</subfield><subfield code="a">610</subfield></datafield></record></collection>
|
| author |
Guo, Wentao |
| spellingShingle |
Guo, Wentao ddc 610 ddc 570 fid BIODIV bkl 35.70 bkl 42.12 Elsevier Reactive power control Elsevier Approximate dynamic programming Elsevier Online supplementary learning control Elsevier Doubly fed induction generator (DFIG) Approximate dynamic programming based supplementary reactive power control for DFIG wind farm to enhance power system stability |
| authorStr |
Guo, Wentao |
| ppnlink_with_tag_str_mv |
@@773@@(DE-627)ELV002603926 |
| format |
electronic Article |
| dewey-ones |
610 - Medicine & health 570 - Life sciences; biology |
| delete_txt_mv |
keep |
| author_role |
aut |
| collection |
elsevier |
| remote_str |
true |
| illustrated |
Not Illustrated |
| topic_title |
610 610 DE-600 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl Approximate dynamic programming based supplementary reactive power control for DFIG wind farm to enhance power system stability Reactive power control Elsevier Approximate dynamic programming Elsevier Online supplementary learning control Elsevier Doubly fed induction generator (DFIG) Elsevier |
| topic |
ddc 610 ddc 570 fid BIODIV bkl 35.70 bkl 42.12 Elsevier Reactive power control Elsevier Approximate dynamic programming Elsevier Online supplementary learning control Elsevier Doubly fed induction generator (DFIG) |
| topic_unstemmed |
ddc 610 ddc 570 fid BIODIV bkl 35.70 bkl 42.12 Elsevier Reactive power control Elsevier Approximate dynamic programming Elsevier Online supplementary learning control Elsevier Doubly fed induction generator (DFIG) |
| topic_browse |
ddc 610 ddc 570 fid BIODIV bkl 35.70 bkl 42.12 Elsevier Reactive power control Elsevier Approximate dynamic programming Elsevier Online supplementary learning control Elsevier Doubly fed induction generator (DFIG) |
| format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
| format_main_str_mv |
Text Zeitschrift/Artikel |
| carriertype_str_mv |
zu |
| author2_variant |
f l fl j s js d h dh r h rh s m sm |
| hierarchy_parent_title |
The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast |
| hierarchy_parent_id |
ELV002603926 |
| dewey-tens |
610 - Medicine & health 570 - Life sciences; biology |
| hierarchy_top_title |
The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast |
| isfreeaccess_txt |
false |
| familylinks_str_mv |
(DE-627)ELV002603926 |
| title |
Approximate dynamic programming based supplementary reactive power control for DFIG wind farm to enhance power system stability |
| ctrlnum |
(DE-627)ELV013187147 (ELSEVIER)S0925-2312(15)00870-X |
| title_full |
Approximate dynamic programming based supplementary reactive power control for DFIG wind farm to enhance power system stability |
| author_sort |
Guo, Wentao |
| journal |
The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast |
| journalStr |
The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast |
| lang_code |
eng |
| isOA_bool |
false |
| dewey-hundreds |
600 - Technology 500 - Science |
| recordtype |
marc |
| publishDateSort |
2015 |
| contenttype_str_mv |
zzz |
| container_start_page |
417 |
| author_browse |
Guo, Wentao |
| container_volume |
170 |
| physical |
11 |
| class |
610 610 DE-600 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl |
| format_se |
Elektronische Aufsätze |
| author-letter |
Guo, Wentao |
| doi_str_mv |
10.1016/j.neucom.2015.03.089 |
| dewey-full |
610 570 |
| title_sort |
approximate dynamic programming based supplementary reactive power control for dfig wind farm to enhance power system stability |
| title_auth |
Approximate dynamic programming based supplementary reactive power control for DFIG wind farm to enhance power system stability |
| abstract |
Reactive power control of doubly fed induction generators (DFIGs) has been a heated topic in transient stability control of power systems in recent years. By using a new online supplementary learning control (OSLC) approach based on the theory of approximate dynamic programming (ADP), this paper develops an optimal and adaptive design method for the supplementary reactive power control of DFIGs to improve transient stability of power systems. To augment the reactive power command of the rotor-side converter (RSC), a supplementary controller is designed to reduce voltage sag at the common coupling point during a fault, and to mitigate active power oscillation of the wind farm after a fault. As a result, the transient stability of both DFIGs and the power system is enhanced. For the supplementary controller design, an action dependent cost function is introduced to make the OSLC model-free and completely data-driven. Furthermore, a least-squares based policy iteration algorithm is employed to train the supplementary controller with convergence and stability guarantee. By using such techniques, the supplementary reactive power controller can be trained directly from data measurements, and therefore, can adapt to system or external changes without an explicit offline system identification process. Simulations carried out in Power System Computer Aided Design/ Electro Magnetic Transient in DC System (PSCAD/EMTDC) show that the OSLC based supplementary reactive power controller can significantly improve the transient performance of the wind farm and enhance the transient stability of the power system after sever faults. |
| abstractGer |
Reactive power control of doubly fed induction generators (DFIGs) has been a heated topic in transient stability control of power systems in recent years. By using a new online supplementary learning control (OSLC) approach based on the theory of approximate dynamic programming (ADP), this paper develops an optimal and adaptive design method for the supplementary reactive power control of DFIGs to improve transient stability of power systems. To augment the reactive power command of the rotor-side converter (RSC), a supplementary controller is designed to reduce voltage sag at the common coupling point during a fault, and to mitigate active power oscillation of the wind farm after a fault. As a result, the transient stability of both DFIGs and the power system is enhanced. For the supplementary controller design, an action dependent cost function is introduced to make the OSLC model-free and completely data-driven. Furthermore, a least-squares based policy iteration algorithm is employed to train the supplementary controller with convergence and stability guarantee. By using such techniques, the supplementary reactive power controller can be trained directly from data measurements, and therefore, can adapt to system or external changes without an explicit offline system identification process. Simulations carried out in Power System Computer Aided Design/ Electro Magnetic Transient in DC System (PSCAD/EMTDC) show that the OSLC based supplementary reactive power controller can significantly improve the transient performance of the wind farm and enhance the transient stability of the power system after sever faults. |
| abstract_unstemmed |
Reactive power control of doubly fed induction generators (DFIGs) has been a heated topic in transient stability control of power systems in recent years. By using a new online supplementary learning control (OSLC) approach based on the theory of approximate dynamic programming (ADP), this paper develops an optimal and adaptive design method for the supplementary reactive power control of DFIGs to improve transient stability of power systems. To augment the reactive power command of the rotor-side converter (RSC), a supplementary controller is designed to reduce voltage sag at the common coupling point during a fault, and to mitigate active power oscillation of the wind farm after a fault. As a result, the transient stability of both DFIGs and the power system is enhanced. For the supplementary controller design, an action dependent cost function is introduced to make the OSLC model-free and completely data-driven. Furthermore, a least-squares based policy iteration algorithm is employed to train the supplementary controller with convergence and stability guarantee. By using such techniques, the supplementary reactive power controller can be trained directly from data measurements, and therefore, can adapt to system or external changes without an explicit offline system identification process. Simulations carried out in Power System Computer Aided Design/ Electro Magnetic Transient in DC System (PSCAD/EMTDC) show that the OSLC based supplementary reactive power controller can significantly improve the transient performance of the wind farm and enhance the transient stability of the power system after sever faults. |
| collection_details |
GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA |
| title_short |
Approximate dynamic programming based supplementary reactive power control for DFIG wind farm to enhance power system stability |
| url |
https://doi.org/10.1016/j.neucom.2015.03.089 |
| remote_bool |
true |
| author2 |
Liu, Feng Si, Jennie He, Dawei Harley, Ronald Mei, Shengwei |
| author2Str |
Liu, Feng Si, Jennie He, Dawei Harley, Ronald Mei, Shengwei |
| ppnlink |
ELV002603926 |
| mediatype_str_mv |
z |
| isOA_txt |
false |
| hochschulschrift_bool |
false |
| author2_role |
oth oth oth oth oth |
| doi_str |
10.1016/j.neucom.2015.03.089 |
| up_date |
2024-07-06T18:15:05.632Z |
| _version_ |
1803854498374877184 |
| fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV013187147</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230625111715.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">180602s2015 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.neucom.2015.03.089</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">GBVA2015014000024.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV013187147</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0925-2312(15)00870-X</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="082" ind1="0" ind2=" "><subfield code="a">610</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="q">DE-600</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">570</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">BIODIV</subfield><subfield code="q">DE-30</subfield><subfield code="2">fid</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">35.70</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">42.12</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Guo, Wentao</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Approximate dynamic programming based supplementary reactive power control for DFIG wind farm to enhance power system stability</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2015transfer abstract</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">11</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Reactive power control of doubly fed induction generators (DFIGs) has been a heated topic in transient stability control of power systems in recent years. By using a new online supplementary learning control (OSLC) approach based on the theory of approximate dynamic programming (ADP), this paper develops an optimal and adaptive design method for the supplementary reactive power control of DFIGs to improve transient stability of power systems. To augment the reactive power command of the rotor-side converter (RSC), a supplementary controller is designed to reduce voltage sag at the common coupling point during a fault, and to mitigate active power oscillation of the wind farm after a fault. As a result, the transient stability of both DFIGs and the power system is enhanced. For the supplementary controller design, an action dependent cost function is introduced to make the OSLC model-free and completely data-driven. Furthermore, a least-squares based policy iteration algorithm is employed to train the supplementary controller with convergence and stability guarantee. By using such techniques, the supplementary reactive power controller can be trained directly from data measurements, and therefore, can adapt to system or external changes without an explicit offline system identification process. Simulations carried out in Power System Computer Aided Design/ Electro Magnetic Transient in DC System (PSCAD/EMTDC) show that the OSLC based supplementary reactive power controller can significantly improve the transient performance of the wind farm and enhance the transient stability of the power system after sever faults.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Reactive power control of doubly fed induction generators (DFIGs) has been a heated topic in transient stability control of power systems in recent years. By using a new online supplementary learning control (OSLC) approach based on the theory of approximate dynamic programming (ADP), this paper develops an optimal and adaptive design method for the supplementary reactive power control of DFIGs to improve transient stability of power systems. To augment the reactive power command of the rotor-side converter (RSC), a supplementary controller is designed to reduce voltage sag at the common coupling point during a fault, and to mitigate active power oscillation of the wind farm after a fault. As a result, the transient stability of both DFIGs and the power system is enhanced. For the supplementary controller design, an action dependent cost function is introduced to make the OSLC model-free and completely data-driven. Furthermore, a least-squares based policy iteration algorithm is employed to train the supplementary controller with convergence and stability guarantee. By using such techniques, the supplementary reactive power controller can be trained directly from data measurements, and therefore, can adapt to system or external changes without an explicit offline system identification process. Simulations carried out in Power System Computer Aided Design/ Electro Magnetic Transient in DC System (PSCAD/EMTDC) show that the OSLC based supplementary reactive power controller can significantly improve the transient performance of the wind farm and enhance the transient stability of the power system after sever faults.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Reactive power control</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Approximate dynamic programming</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Online supplementary learning control</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Doubly fed induction generator (DFIG)</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Liu, Feng</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Si, Jennie</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">He, Dawei</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Harley, Ronald</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Mei, Shengwei</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier</subfield><subfield code="a">Liu, Yang ELSEVIER</subfield><subfield code="t">The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast</subfield><subfield code="d">2018</subfield><subfield code="d">an international journal</subfield><subfield code="g">Amsterdam</subfield><subfield code="w">(DE-627)ELV002603926</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:170</subfield><subfield code="g">year:2015</subfield><subfield code="g">day:25</subfield><subfield code="g">month:12</subfield><subfield code="g">pages:417-427</subfield><subfield code="g">extent:11</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.neucom.2015.03.089</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">FID-BIODIV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">35.70</subfield><subfield code="j">Biochemie: Allgemeines</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">42.12</subfield><subfield code="j">Biophysik</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">170</subfield><subfield code="j">2015</subfield><subfield code="b">25</subfield><subfield code="c">1225</subfield><subfield code="h">417-427</subfield><subfield code="g">11</subfield></datafield><datafield tag="953" ind1=" " ind2=" "><subfield code="2">045F</subfield><subfield code="a">610</subfield></datafield></record></collection>
|
| score |
7.400199 |