Fault Analysis of PI and Fuzzy-Logic-Controlled DFIG-based Grid-Connected Wind Energy Conversion System
Abstract This research is based on the design of modified version of Type-III wind turbine system using DFIG (Double-Fed Induction Generator). The control technique associated with Type-III wind turbine system is Modified Type-I Fuzzy Logic Controller. Using this advanced form of controller, four di...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Ganthia, Bibhu Prasad [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2021 |
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| Schlagwörter: |
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| Anmerkung: |
© The Institution of Engineers (India) 2021 |
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| Übergeordnetes Werk: |
Enthalten in: Journal of the Institution of Engineers (India) - [New Delhi] : Springer India, 2012, 103(2021), 2 vom: 14. Sept., Seite 415-437 |
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| Übergeordnetes Werk: |
volume:103 ; year:2021 ; number:2 ; day:14 ; month:09 ; pages:415-437 |
| Links: |
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| DOI / URN: |
10.1007/s40031-021-00664-9 |
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| Katalog-ID: |
SPR046747591 |
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| 520 | |a Abstract This research is based on the design of modified version of Type-III wind turbine system using DFIG (Double-Fed Induction Generator). The control technique associated with Type-III wind turbine system is Modified Type-I Fuzzy Logic Controller. Using this advanced form of controller, four different models are designed to control the active and reactive power during the transients and unwanted faults cause voltage sags. Mechanical Drive Train-modified Type-III DFIG-based wind turbine system during various fault conditions like voltage dip conditions, swell conditions with respect to variation in wind speed is explained in MATLAB model with control action of PI controller and Fuzzy Logic Controller (FLC) with grid integration. The research highlights implementations of four types of Fuzzy structures with different modes of operations that are modeled, and comparisons were made between all the structures with PI control structure for both steady state and dynamic state. The model is assembled to the lattice of grid, and the control of the model mechanisms using PI and FLC is studied to estimate the fast response of settling time after the removal of faults. The simulation is done to find the effective controller with respect to cost and economic point of view. The model is based on transient responses to calculate the settling time with application of various fault conditions. In this paper, DFIG, i.e., Double-Fed Induction Generator, is operated through variable speed and variable pitch angle control scheme which is now mostly implemented in power generation and distribution industries. In this paper, DFIG in wind turbine model is assembled to a constant frequency and constant voltage source and tied into a grid which is modeled using MATLAB and to the corresponding generator for operation and control action on active and reactive power are highlighted. The steady state operation and transient characteristics of the whole wind energy conversion system is explained with detail study with respect to the transients due to sudden change in wind speeds. | ||
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| 700 | 1 | |a Barik, Subrat Kumar |4 aut | |
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10.1007/s40031-021-00664-9 doi (DE-627)SPR046747591 (SPR)s40031-021-00664-9-e DE-627 ger DE-627 rakwb eng Ganthia, Bibhu Prasad verfasserin (orcid)0000-0003-2351-7830 aut Fault Analysis of PI and Fuzzy-Logic-Controlled DFIG-based Grid-Connected Wind Energy Conversion System 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Institution of Engineers (India) 2021 Abstract This research is based on the design of modified version of Type-III wind turbine system using DFIG (Double-Fed Induction Generator). The control technique associated with Type-III wind turbine system is Modified Type-I Fuzzy Logic Controller. Using this advanced form of controller, four different models are designed to control the active and reactive power during the transients and unwanted faults cause voltage sags. Mechanical Drive Train-modified Type-III DFIG-based wind turbine system during various fault conditions like voltage dip conditions, swell conditions with respect to variation in wind speed is explained in MATLAB model with control action of PI controller and Fuzzy Logic Controller (FLC) with grid integration. The research highlights implementations of four types of Fuzzy structures with different modes of operations that are modeled, and comparisons were made between all the structures with PI control structure for both steady state and dynamic state. The model is assembled to the lattice of grid, and the control of the model mechanisms using PI and FLC is studied to estimate the fast response of settling time after the removal of faults. The simulation is done to find the effective controller with respect to cost and economic point of view. The model is based on transient responses to calculate the settling time with application of various fault conditions. In this paper, DFIG, i.e., Double-Fed Induction Generator, is operated through variable speed and variable pitch angle control scheme which is now mostly implemented in power generation and distribution industries. In this paper, DFIG in wind turbine model is assembled to a constant frequency and constant voltage source and tied into a grid which is modeled using MATLAB and to the corresponding generator for operation and control action on active and reactive power are highlighted. The steady state operation and transient characteristics of the whole wind energy conversion system is explained with detail study with respect to the transients due to sudden change in wind speeds. DFIG (dpeaa)DE-He213 WECS (dpeaa)DE-He213 GSC (dpeaa)DE-He213 RSC (dpeaa)DE-He213 FLC (dpeaa)DE-He213 PAC (dpeaa)DE-He213 Barik, Subrat Kumar aut Enthalten in Journal of the Institution of Engineers (India) [New Delhi] : Springer India, 2012 103(2021), 2 vom: 14. Sept., Seite 415-437 (DE-627)722236980 (DE-600)2677588-8 2250-2114 nnns volume:103 year:2021 number:2 day:14 month:09 pages:415-437 https://dx.doi.org/10.1007/s40031-021-00664-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 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_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 103 2021 2 14 09 415-437 |
| spelling |
10.1007/s40031-021-00664-9 doi (DE-627)SPR046747591 (SPR)s40031-021-00664-9-e DE-627 ger DE-627 rakwb eng Ganthia, Bibhu Prasad verfasserin (orcid)0000-0003-2351-7830 aut Fault Analysis of PI and Fuzzy-Logic-Controlled DFIG-based Grid-Connected Wind Energy Conversion System 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Institution of Engineers (India) 2021 Abstract This research is based on the design of modified version of Type-III wind turbine system using DFIG (Double-Fed Induction Generator). The control technique associated with Type-III wind turbine system is Modified Type-I Fuzzy Logic Controller. Using this advanced form of controller, four different models are designed to control the active and reactive power during the transients and unwanted faults cause voltage sags. Mechanical Drive Train-modified Type-III DFIG-based wind turbine system during various fault conditions like voltage dip conditions, swell conditions with respect to variation in wind speed is explained in MATLAB model with control action of PI controller and Fuzzy Logic Controller (FLC) with grid integration. The research highlights implementations of four types of Fuzzy structures with different modes of operations that are modeled, and comparisons were made between all the structures with PI control structure for both steady state and dynamic state. The model is assembled to the lattice of grid, and the control of the model mechanisms using PI and FLC is studied to estimate the fast response of settling time after the removal of faults. The simulation is done to find the effective controller with respect to cost and economic point of view. The model is based on transient responses to calculate the settling time with application of various fault conditions. In this paper, DFIG, i.e., Double-Fed Induction Generator, is operated through variable speed and variable pitch angle control scheme which is now mostly implemented in power generation and distribution industries. In this paper, DFIG in wind turbine model is assembled to a constant frequency and constant voltage source and tied into a grid which is modeled using MATLAB and to the corresponding generator for operation and control action on active and reactive power are highlighted. The steady state operation and transient characteristics of the whole wind energy conversion system is explained with detail study with respect to the transients due to sudden change in wind speeds. DFIG (dpeaa)DE-He213 WECS (dpeaa)DE-He213 GSC (dpeaa)DE-He213 RSC (dpeaa)DE-He213 FLC (dpeaa)DE-He213 PAC (dpeaa)DE-He213 Barik, Subrat Kumar aut Enthalten in Journal of the Institution of Engineers (India) [New Delhi] : Springer India, 2012 103(2021), 2 vom: 14. Sept., Seite 415-437 (DE-627)722236980 (DE-600)2677588-8 2250-2114 nnns volume:103 year:2021 number:2 day:14 month:09 pages:415-437 https://dx.doi.org/10.1007/s40031-021-00664-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 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_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 103 2021 2 14 09 415-437 |
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10.1007/s40031-021-00664-9 doi (DE-627)SPR046747591 (SPR)s40031-021-00664-9-e DE-627 ger DE-627 rakwb eng Ganthia, Bibhu Prasad verfasserin (orcid)0000-0003-2351-7830 aut Fault Analysis of PI and Fuzzy-Logic-Controlled DFIG-based Grid-Connected Wind Energy Conversion System 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Institution of Engineers (India) 2021 Abstract This research is based on the design of modified version of Type-III wind turbine system using DFIG (Double-Fed Induction Generator). The control technique associated with Type-III wind turbine system is Modified Type-I Fuzzy Logic Controller. Using this advanced form of controller, four different models are designed to control the active and reactive power during the transients and unwanted faults cause voltage sags. Mechanical Drive Train-modified Type-III DFIG-based wind turbine system during various fault conditions like voltage dip conditions, swell conditions with respect to variation in wind speed is explained in MATLAB model with control action of PI controller and Fuzzy Logic Controller (FLC) with grid integration. The research highlights implementations of four types of Fuzzy structures with different modes of operations that are modeled, and comparisons were made between all the structures with PI control structure for both steady state and dynamic state. The model is assembled to the lattice of grid, and the control of the model mechanisms using PI and FLC is studied to estimate the fast response of settling time after the removal of faults. The simulation is done to find the effective controller with respect to cost and economic point of view. The model is based on transient responses to calculate the settling time with application of various fault conditions. In this paper, DFIG, i.e., Double-Fed Induction Generator, is operated through variable speed and variable pitch angle control scheme which is now mostly implemented in power generation and distribution industries. In this paper, DFIG in wind turbine model is assembled to a constant frequency and constant voltage source and tied into a grid which is modeled using MATLAB and to the corresponding generator for operation and control action on active and reactive power are highlighted. The steady state operation and transient characteristics of the whole wind energy conversion system is explained with detail study with respect to the transients due to sudden change in wind speeds. DFIG (dpeaa)DE-He213 WECS (dpeaa)DE-He213 GSC (dpeaa)DE-He213 RSC (dpeaa)DE-He213 FLC (dpeaa)DE-He213 PAC (dpeaa)DE-He213 Barik, Subrat Kumar aut Enthalten in Journal of the Institution of Engineers (India) [New Delhi] : Springer India, 2012 103(2021), 2 vom: 14. Sept., Seite 415-437 (DE-627)722236980 (DE-600)2677588-8 2250-2114 nnns volume:103 year:2021 number:2 day:14 month:09 pages:415-437 https://dx.doi.org/10.1007/s40031-021-00664-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 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_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 103 2021 2 14 09 415-437 |
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10.1007/s40031-021-00664-9 doi (DE-627)SPR046747591 (SPR)s40031-021-00664-9-e DE-627 ger DE-627 rakwb eng Ganthia, Bibhu Prasad verfasserin (orcid)0000-0003-2351-7830 aut Fault Analysis of PI and Fuzzy-Logic-Controlled DFIG-based Grid-Connected Wind Energy Conversion System 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Institution of Engineers (India) 2021 Abstract This research is based on the design of modified version of Type-III wind turbine system using DFIG (Double-Fed Induction Generator). The control technique associated with Type-III wind turbine system is Modified Type-I Fuzzy Logic Controller. Using this advanced form of controller, four different models are designed to control the active and reactive power during the transients and unwanted faults cause voltage sags. Mechanical Drive Train-modified Type-III DFIG-based wind turbine system during various fault conditions like voltage dip conditions, swell conditions with respect to variation in wind speed is explained in MATLAB model with control action of PI controller and Fuzzy Logic Controller (FLC) with grid integration. The research highlights implementations of four types of Fuzzy structures with different modes of operations that are modeled, and comparisons were made between all the structures with PI control structure for both steady state and dynamic state. The model is assembled to the lattice of grid, and the control of the model mechanisms using PI and FLC is studied to estimate the fast response of settling time after the removal of faults. The simulation is done to find the effective controller with respect to cost and economic point of view. The model is based on transient responses to calculate the settling time with application of various fault conditions. In this paper, DFIG, i.e., Double-Fed Induction Generator, is operated through variable speed and variable pitch angle control scheme which is now mostly implemented in power generation and distribution industries. In this paper, DFIG in wind turbine model is assembled to a constant frequency and constant voltage source and tied into a grid which is modeled using MATLAB and to the corresponding generator for operation and control action on active and reactive power are highlighted. The steady state operation and transient characteristics of the whole wind energy conversion system is explained with detail study with respect to the transients due to sudden change in wind speeds. DFIG (dpeaa)DE-He213 WECS (dpeaa)DE-He213 GSC (dpeaa)DE-He213 RSC (dpeaa)DE-He213 FLC (dpeaa)DE-He213 PAC (dpeaa)DE-He213 Barik, Subrat Kumar aut Enthalten in Journal of the Institution of Engineers (India) [New Delhi] : Springer India, 2012 103(2021), 2 vom: 14. Sept., Seite 415-437 (DE-627)722236980 (DE-600)2677588-8 2250-2114 nnns volume:103 year:2021 number:2 day:14 month:09 pages:415-437 https://dx.doi.org/10.1007/s40031-021-00664-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 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_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 103 2021 2 14 09 415-437 |
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10.1007/s40031-021-00664-9 doi (DE-627)SPR046747591 (SPR)s40031-021-00664-9-e DE-627 ger DE-627 rakwb eng Ganthia, Bibhu Prasad verfasserin (orcid)0000-0003-2351-7830 aut Fault Analysis of PI and Fuzzy-Logic-Controlled DFIG-based Grid-Connected Wind Energy Conversion System 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Institution of Engineers (India) 2021 Abstract This research is based on the design of modified version of Type-III wind turbine system using DFIG (Double-Fed Induction Generator). The control technique associated with Type-III wind turbine system is Modified Type-I Fuzzy Logic Controller. Using this advanced form of controller, four different models are designed to control the active and reactive power during the transients and unwanted faults cause voltage sags. Mechanical Drive Train-modified Type-III DFIG-based wind turbine system during various fault conditions like voltage dip conditions, swell conditions with respect to variation in wind speed is explained in MATLAB model with control action of PI controller and Fuzzy Logic Controller (FLC) with grid integration. The research highlights implementations of four types of Fuzzy structures with different modes of operations that are modeled, and comparisons were made between all the structures with PI control structure for both steady state and dynamic state. The model is assembled to the lattice of grid, and the control of the model mechanisms using PI and FLC is studied to estimate the fast response of settling time after the removal of faults. The simulation is done to find the effective controller with respect to cost and economic point of view. The model is based on transient responses to calculate the settling time with application of various fault conditions. In this paper, DFIG, i.e., Double-Fed Induction Generator, is operated through variable speed and variable pitch angle control scheme which is now mostly implemented in power generation and distribution industries. In this paper, DFIG in wind turbine model is assembled to a constant frequency and constant voltage source and tied into a grid which is modeled using MATLAB and to the corresponding generator for operation and control action on active and reactive power are highlighted. The steady state operation and transient characteristics of the whole wind energy conversion system is explained with detail study with respect to the transients due to sudden change in wind speeds. DFIG (dpeaa)DE-He213 WECS (dpeaa)DE-He213 GSC (dpeaa)DE-He213 RSC (dpeaa)DE-He213 FLC (dpeaa)DE-He213 PAC (dpeaa)DE-He213 Barik, Subrat Kumar aut Enthalten in Journal of the Institution of Engineers (India) [New Delhi] : Springer India, 2012 103(2021), 2 vom: 14. Sept., Seite 415-437 (DE-627)722236980 (DE-600)2677588-8 2250-2114 nnns volume:103 year:2021 number:2 day:14 month:09 pages:415-437 https://dx.doi.org/10.1007/s40031-021-00664-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 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_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 103 2021 2 14 09 415-437 |
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The control technique associated with Type-III wind turbine system is Modified Type-I Fuzzy Logic Controller. Using this advanced form of controller, four different models are designed to control the active and reactive power during the transients and unwanted faults cause voltage sags. Mechanical Drive Train-modified Type-III DFIG-based wind turbine system during various fault conditions like voltage dip conditions, swell conditions with respect to variation in wind speed is explained in MATLAB model with control action of PI controller and Fuzzy Logic Controller (FLC) with grid integration. The research highlights implementations of four types of Fuzzy structures with different modes of operations that are modeled, and comparisons were made between all the structures with PI control structure for both steady state and dynamic state. The model is assembled to the lattice of grid, and the control of the model mechanisms using PI and FLC is studied to estimate the fast response of settling time after the removal of faults. The simulation is done to find the effective controller with respect to cost and economic point of view. The model is based on transient responses to calculate the settling time with application of various fault conditions. In this paper, DFIG, i.e., Double-Fed Induction Generator, is operated through variable speed and variable pitch angle control scheme which is now mostly implemented in power generation and distribution industries. In this paper, DFIG in wind turbine model is assembled to a constant frequency and constant voltage source and tied into a grid which is modeled using MATLAB and to the corresponding generator for operation and control action on active and reactive power are highlighted. 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Ganthia, Bibhu Prasad |
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Ganthia, Bibhu Prasad misc DFIG misc WECS misc GSC misc RSC misc FLC misc PAC Fault Analysis of PI and Fuzzy-Logic-Controlled DFIG-based Grid-Connected Wind Energy Conversion System |
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Fault Analysis of PI and Fuzzy-Logic-Controlled DFIG-based Grid-Connected Wind Energy Conversion System DFIG (dpeaa)DE-He213 WECS (dpeaa)DE-He213 GSC (dpeaa)DE-He213 RSC (dpeaa)DE-He213 FLC (dpeaa)DE-He213 PAC (dpeaa)DE-He213 |
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Fault Analysis of PI and Fuzzy-Logic-Controlled DFIG-based Grid-Connected Wind Energy Conversion System |
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Fault Analysis of PI and Fuzzy-Logic-Controlled DFIG-based Grid-Connected Wind Energy Conversion System |
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fault analysis of pi and fuzzy-logic-controlled dfig-based grid-connected wind energy conversion system |
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Fault Analysis of PI and Fuzzy-Logic-Controlled DFIG-based Grid-Connected Wind Energy Conversion System |
| abstract |
Abstract This research is based on the design of modified version of Type-III wind turbine system using DFIG (Double-Fed Induction Generator). The control technique associated with Type-III wind turbine system is Modified Type-I Fuzzy Logic Controller. Using this advanced form of controller, four different models are designed to control the active and reactive power during the transients and unwanted faults cause voltage sags. Mechanical Drive Train-modified Type-III DFIG-based wind turbine system during various fault conditions like voltage dip conditions, swell conditions with respect to variation in wind speed is explained in MATLAB model with control action of PI controller and Fuzzy Logic Controller (FLC) with grid integration. The research highlights implementations of four types of Fuzzy structures with different modes of operations that are modeled, and comparisons were made between all the structures with PI control structure for both steady state and dynamic state. The model is assembled to the lattice of grid, and the control of the model mechanisms using PI and FLC is studied to estimate the fast response of settling time after the removal of faults. The simulation is done to find the effective controller with respect to cost and economic point of view. The model is based on transient responses to calculate the settling time with application of various fault conditions. In this paper, DFIG, i.e., Double-Fed Induction Generator, is operated through variable speed and variable pitch angle control scheme which is now mostly implemented in power generation and distribution industries. In this paper, DFIG in wind turbine model is assembled to a constant frequency and constant voltage source and tied into a grid which is modeled using MATLAB and to the corresponding generator for operation and control action on active and reactive power are highlighted. The steady state operation and transient characteristics of the whole wind energy conversion system is explained with detail study with respect to the transients due to sudden change in wind speeds. © The Institution of Engineers (India) 2021 |
| abstractGer |
Abstract This research is based on the design of modified version of Type-III wind turbine system using DFIG (Double-Fed Induction Generator). The control technique associated with Type-III wind turbine system is Modified Type-I Fuzzy Logic Controller. Using this advanced form of controller, four different models are designed to control the active and reactive power during the transients and unwanted faults cause voltage sags. Mechanical Drive Train-modified Type-III DFIG-based wind turbine system during various fault conditions like voltage dip conditions, swell conditions with respect to variation in wind speed is explained in MATLAB model with control action of PI controller and Fuzzy Logic Controller (FLC) with grid integration. The research highlights implementations of four types of Fuzzy structures with different modes of operations that are modeled, and comparisons were made between all the structures with PI control structure for both steady state and dynamic state. The model is assembled to the lattice of grid, and the control of the model mechanisms using PI and FLC is studied to estimate the fast response of settling time after the removal of faults. The simulation is done to find the effective controller with respect to cost and economic point of view. The model is based on transient responses to calculate the settling time with application of various fault conditions. In this paper, DFIG, i.e., Double-Fed Induction Generator, is operated through variable speed and variable pitch angle control scheme which is now mostly implemented in power generation and distribution industries. In this paper, DFIG in wind turbine model is assembled to a constant frequency and constant voltage source and tied into a grid which is modeled using MATLAB and to the corresponding generator for operation and control action on active and reactive power are highlighted. The steady state operation and transient characteristics of the whole wind energy conversion system is explained with detail study with respect to the transients due to sudden change in wind speeds. © The Institution of Engineers (India) 2021 |
| abstract_unstemmed |
Abstract This research is based on the design of modified version of Type-III wind turbine system using DFIG (Double-Fed Induction Generator). The control technique associated with Type-III wind turbine system is Modified Type-I Fuzzy Logic Controller. Using this advanced form of controller, four different models are designed to control the active and reactive power during the transients and unwanted faults cause voltage sags. Mechanical Drive Train-modified Type-III DFIG-based wind turbine system during various fault conditions like voltage dip conditions, swell conditions with respect to variation in wind speed is explained in MATLAB model with control action of PI controller and Fuzzy Logic Controller (FLC) with grid integration. The research highlights implementations of four types of Fuzzy structures with different modes of operations that are modeled, and comparisons were made between all the structures with PI control structure for both steady state and dynamic state. The model is assembled to the lattice of grid, and the control of the model mechanisms using PI and FLC is studied to estimate the fast response of settling time after the removal of faults. The simulation is done to find the effective controller with respect to cost and economic point of view. The model is based on transient responses to calculate the settling time with application of various fault conditions. In this paper, DFIG, i.e., Double-Fed Induction Generator, is operated through variable speed and variable pitch angle control scheme which is now mostly implemented in power generation and distribution industries. In this paper, DFIG in wind turbine model is assembled to a constant frequency and constant voltage source and tied into a grid which is modeled using MATLAB and to the corresponding generator for operation and control action on active and reactive power are highlighted. The steady state operation and transient characteristics of the whole wind energy conversion system is explained with detail study with respect to the transients due to sudden change in wind speeds. © The Institution of Engineers (India) 2021 |
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Fault Analysis of PI and Fuzzy-Logic-Controlled DFIG-based Grid-Connected Wind Energy Conversion System |
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https://dx.doi.org/10.1007/s40031-021-00664-9 |
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| score |
7.3996277 |