Parallel fault detection algorithm for grid-connected photovoltaic plants
In this work, we present a new algorithm for detecting faults in grid-connected photovoltaic (GCPV) plant. There are few instances of statistical tools being deployed in the analysis of PV measured data. The main focus of this paper is, therefore, to outline a parallel fault detection algorithm that...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Dhimish, Mahmoud [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2017 |
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| Schlagwörter: |
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Enthalten in: Renewable energy - Oxford [u.a.] : Pergamon Press, 1991, (2017) |
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| 520 | |a In this work, we present a new algorithm for detecting faults in grid-connected photovoltaic (GCPV) plant. There are few instances of statistical tools being deployed in the analysis of PV measured data. The main focus of this paper is, therefore, to outline a parallel fault detection algorithm that can diagnose faults on the DC-side and AC-side of the examined GCPV system based on the t-test statistical analysis method. For a given set of operational conditions, solar irradiance and module's temperature, a number of attributes such as voltage and power ratio of the PV strings are measured using virtual instrumentation (VI) LabVIEW software. The results obtained indicate that the parallel fault detection algorithm can detect and locate accurately different types of faults such as, faulty PV module, faulty PV String, Faulty Bypass diode, Faulty Maximum power point tracking (MPPT) unit and Faulty DC/AC inverter unit. The parallel fault detection algorithm has been validated using an experimental data climate, with electrical parameters based on a 1.98 and 0.52 kWp PV systems installed at the University of Huddersfield, United Kingdom. | ||
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PQ20171228 (DE-627)OLC1999320859 (DE-599)GBVOLC1999320859 (PRQ)hud_eprints_oai_eprints_hud_ac_uk_334650 (KEY)0136323920170000000000000000parallelfaultdetectionalgorithmforgridconnectedpho DE-627 ger DE-627 rakwb eng 530 620 DNB Dhimish, Mahmoud verfasserin aut Parallel fault detection algorithm for grid-connected photovoltaic plants 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier In this work, we present a new algorithm for detecting faults in grid-connected photovoltaic (GCPV) plant. There are few instances of statistical tools being deployed in the analysis of PV measured data. The main focus of this paper is, therefore, to outline a parallel fault detection algorithm that can diagnose faults on the DC-side and AC-side of the examined GCPV system based on the t-test statistical analysis method. For a given set of operational conditions, solar irradiance and module's temperature, a number of attributes such as voltage and power ratio of the PV strings are measured using virtual instrumentation (VI) LabVIEW software. The results obtained indicate that the parallel fault detection algorithm can detect and locate accurately different types of faults such as, faulty PV module, faulty PV String, Faulty Bypass diode, Faulty Maximum power point tracking (MPPT) unit and Faulty DC/AC inverter unit. The parallel fault detection algorithm has been validated using an experimental data climate, with electrical parameters based on a 1.98 and 0.52 kWp PV systems installed at the University of Huddersfield, United Kingdom. Electronics Nuclear engineering Engineering Environmental technology Electrical engineering Sanitary engineering Civil engineering Holmes, Violeta oth Dales, Mark oth Enthalten in Renewable energy Oxford [u.a.] : Pergamon Press, 1991 (2017) (DE-627)130967505 (DE-600)1068916-3 (DE-576)025187473 0960-1481 nnns year:2017 http://eprints.hud.ac.uk/33465/ GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-PHY GBV_ILN_70 AR 2017 |
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PQ20171228 (DE-627)OLC1999320859 (DE-599)GBVOLC1999320859 (PRQ)hud_eprints_oai_eprints_hud_ac_uk_334650 (KEY)0136323920170000000000000000parallelfaultdetectionalgorithmforgridconnectedpho DE-627 ger DE-627 rakwb eng 530 620 DNB Dhimish, Mahmoud verfasserin aut Parallel fault detection algorithm for grid-connected photovoltaic plants 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier In this work, we present a new algorithm for detecting faults in grid-connected photovoltaic (GCPV) plant. There are few instances of statistical tools being deployed in the analysis of PV measured data. The main focus of this paper is, therefore, to outline a parallel fault detection algorithm that can diagnose faults on the DC-side and AC-side of the examined GCPV system based on the t-test statistical analysis method. For a given set of operational conditions, solar irradiance and module's temperature, a number of attributes such as voltage and power ratio of the PV strings are measured using virtual instrumentation (VI) LabVIEW software. The results obtained indicate that the parallel fault detection algorithm can detect and locate accurately different types of faults such as, faulty PV module, faulty PV String, Faulty Bypass diode, Faulty Maximum power point tracking (MPPT) unit and Faulty DC/AC inverter unit. The parallel fault detection algorithm has been validated using an experimental data climate, with electrical parameters based on a 1.98 and 0.52 kWp PV systems installed at the University of Huddersfield, United Kingdom. Electronics Nuclear engineering Engineering Environmental technology Electrical engineering Sanitary engineering Civil engineering Holmes, Violeta oth Dales, Mark oth Enthalten in Renewable energy Oxford [u.a.] : Pergamon Press, 1991 (2017) (DE-627)130967505 (DE-600)1068916-3 (DE-576)025187473 0960-1481 nnns year:2017 http://eprints.hud.ac.uk/33465/ GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-PHY GBV_ILN_70 AR 2017 |
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PQ20171228 (DE-627)OLC1999320859 (DE-599)GBVOLC1999320859 (PRQ)hud_eprints_oai_eprints_hud_ac_uk_334650 (KEY)0136323920170000000000000000parallelfaultdetectionalgorithmforgridconnectedpho DE-627 ger DE-627 rakwb eng 530 620 DNB Dhimish, Mahmoud verfasserin aut Parallel fault detection algorithm for grid-connected photovoltaic plants 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier In this work, we present a new algorithm for detecting faults in grid-connected photovoltaic (GCPV) plant. There are few instances of statistical tools being deployed in the analysis of PV measured data. The main focus of this paper is, therefore, to outline a parallel fault detection algorithm that can diagnose faults on the DC-side and AC-side of the examined GCPV system based on the t-test statistical analysis method. For a given set of operational conditions, solar irradiance and module's temperature, a number of attributes such as voltage and power ratio of the PV strings are measured using virtual instrumentation (VI) LabVIEW software. The results obtained indicate that the parallel fault detection algorithm can detect and locate accurately different types of faults such as, faulty PV module, faulty PV String, Faulty Bypass diode, Faulty Maximum power point tracking (MPPT) unit and Faulty DC/AC inverter unit. The parallel fault detection algorithm has been validated using an experimental data climate, with electrical parameters based on a 1.98 and 0.52 kWp PV systems installed at the University of Huddersfield, United Kingdom. Electronics Nuclear engineering Engineering Environmental technology Electrical engineering Sanitary engineering Civil engineering Holmes, Violeta oth Dales, Mark oth Enthalten in Renewable energy Oxford [u.a.] : Pergamon Press, 1991 (2017) (DE-627)130967505 (DE-600)1068916-3 (DE-576)025187473 0960-1481 nnns year:2017 http://eprints.hud.ac.uk/33465/ GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-PHY GBV_ILN_70 AR 2017 |
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PQ20171228 (DE-627)OLC1999320859 (DE-599)GBVOLC1999320859 (PRQ)hud_eprints_oai_eprints_hud_ac_uk_334650 (KEY)0136323920170000000000000000parallelfaultdetectionalgorithmforgridconnectedpho DE-627 ger DE-627 rakwb eng 530 620 DNB Dhimish, Mahmoud verfasserin aut Parallel fault detection algorithm for grid-connected photovoltaic plants 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier In this work, we present a new algorithm for detecting faults in grid-connected photovoltaic (GCPV) plant. There are few instances of statistical tools being deployed in the analysis of PV measured data. The main focus of this paper is, therefore, to outline a parallel fault detection algorithm that can diagnose faults on the DC-side and AC-side of the examined GCPV system based on the t-test statistical analysis method. For a given set of operational conditions, solar irradiance and module's temperature, a number of attributes such as voltage and power ratio of the PV strings are measured using virtual instrumentation (VI) LabVIEW software. The results obtained indicate that the parallel fault detection algorithm can detect and locate accurately different types of faults such as, faulty PV module, faulty PV String, Faulty Bypass diode, Faulty Maximum power point tracking (MPPT) unit and Faulty DC/AC inverter unit. The parallel fault detection algorithm has been validated using an experimental data climate, with electrical parameters based on a 1.98 and 0.52 kWp PV systems installed at the University of Huddersfield, United Kingdom. Electronics Nuclear engineering Engineering Environmental technology Electrical engineering Sanitary engineering Civil engineering Holmes, Violeta oth Dales, Mark oth Enthalten in Renewable energy Oxford [u.a.] : Pergamon Press, 1991 (2017) (DE-627)130967505 (DE-600)1068916-3 (DE-576)025187473 0960-1481 nnns year:2017 http://eprints.hud.ac.uk/33465/ GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-PHY GBV_ILN_70 AR 2017 |
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PQ20171228 (DE-627)OLC1999320859 (DE-599)GBVOLC1999320859 (PRQ)hud_eprints_oai_eprints_hud_ac_uk_334650 (KEY)0136323920170000000000000000parallelfaultdetectionalgorithmforgridconnectedpho DE-627 ger DE-627 rakwb eng 530 620 DNB Dhimish, Mahmoud verfasserin aut Parallel fault detection algorithm for grid-connected photovoltaic plants 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier In this work, we present a new algorithm for detecting faults in grid-connected photovoltaic (GCPV) plant. There are few instances of statistical tools being deployed in the analysis of PV measured data. The main focus of this paper is, therefore, to outline a parallel fault detection algorithm that can diagnose faults on the DC-side and AC-side of the examined GCPV system based on the t-test statistical analysis method. For a given set of operational conditions, solar irradiance and module's temperature, a number of attributes such as voltage and power ratio of the PV strings are measured using virtual instrumentation (VI) LabVIEW software. The results obtained indicate that the parallel fault detection algorithm can detect and locate accurately different types of faults such as, faulty PV module, faulty PV String, Faulty Bypass diode, Faulty Maximum power point tracking (MPPT) unit and Faulty DC/AC inverter unit. The parallel fault detection algorithm has been validated using an experimental data climate, with electrical parameters based on a 1.98 and 0.52 kWp PV systems installed at the University of Huddersfield, United Kingdom. Electronics Nuclear engineering Engineering Environmental technology Electrical engineering Sanitary engineering Civil engineering Holmes, Violeta oth Dales, Mark oth Enthalten in Renewable energy Oxford [u.a.] : Pergamon Press, 1991 (2017) (DE-627)130967505 (DE-600)1068916-3 (DE-576)025187473 0960-1481 nnns year:2017 http://eprints.hud.ac.uk/33465/ GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-PHY GBV_ILN_70 AR 2017 |
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In this work, we present a new algorithm for detecting faults in grid-connected photovoltaic (GCPV) plant. There are few instances of statistical tools being deployed in the analysis of PV measured data. The main focus of this paper is, therefore, to outline a parallel fault detection algorithm that can diagnose faults on the DC-side and AC-side of the examined GCPV system based on the t-test statistical analysis method. For a given set of operational conditions, solar irradiance and module's temperature, a number of attributes such as voltage and power ratio of the PV strings are measured using virtual instrumentation (VI) LabVIEW software. The results obtained indicate that the parallel fault detection algorithm can detect and locate accurately different types of faults such as, faulty PV module, faulty PV String, Faulty Bypass diode, Faulty Maximum power point tracking (MPPT) unit and Faulty DC/AC inverter unit. The parallel fault detection algorithm has been validated using an experimental data climate, with electrical parameters based on a 1.98 and 0.52 kWp PV systems installed at the University of Huddersfield, United Kingdom. |
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In this work, we present a new algorithm for detecting faults in grid-connected photovoltaic (GCPV) plant. There are few instances of statistical tools being deployed in the analysis of PV measured data. The main focus of this paper is, therefore, to outline a parallel fault detection algorithm that can diagnose faults on the DC-side and AC-side of the examined GCPV system based on the t-test statistical analysis method. For a given set of operational conditions, solar irradiance and module's temperature, a number of attributes such as voltage and power ratio of the PV strings are measured using virtual instrumentation (VI) LabVIEW software. The results obtained indicate that the parallel fault detection algorithm can detect and locate accurately different types of faults such as, faulty PV module, faulty PV String, Faulty Bypass diode, Faulty Maximum power point tracking (MPPT) unit and Faulty DC/AC inverter unit. The parallel fault detection algorithm has been validated using an experimental data climate, with electrical parameters based on a 1.98 and 0.52 kWp PV systems installed at the University of Huddersfield, United Kingdom. |
| abstract_unstemmed |
In this work, we present a new algorithm for detecting faults in grid-connected photovoltaic (GCPV) plant. There are few instances of statistical tools being deployed in the analysis of PV measured data. The main focus of this paper is, therefore, to outline a parallel fault detection algorithm that can diagnose faults on the DC-side and AC-side of the examined GCPV system based on the t-test statistical analysis method. For a given set of operational conditions, solar irradiance and module's temperature, a number of attributes such as voltage and power ratio of the PV strings are measured using virtual instrumentation (VI) LabVIEW software. The results obtained indicate that the parallel fault detection algorithm can detect and locate accurately different types of faults such as, faulty PV module, faulty PV String, Faulty Bypass diode, Faulty Maximum power point tracking (MPPT) unit and Faulty DC/AC inverter unit. The parallel fault detection algorithm has been validated using an experimental data climate, with electrical parameters based on a 1.98 and 0.52 kWp PV systems installed at the University of Huddersfield, United Kingdom. |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a2200265 4500</leader><controlfield tag="001">OLC1999320859</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230715084103.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">171228s2017 xx ||||| 00| ||eng c</controlfield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">PQ20171228</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC1999320859</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)GBVOLC1999320859</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(PRQ)hud_eprints_oai_eprints_hud_ac_uk_334650</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(KEY)0136323920170000000000000000parallelfaultdetectionalgorithmforgridconnectedpho</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="4"><subfield code="a">530</subfield><subfield code="a">620</subfield><subfield code="q">DNB</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Dhimish, Mahmoud</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Parallel fault detection algorithm for grid-connected photovoltaic plants</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2017</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">In this work, we present a new algorithm for detecting faults in grid-connected photovoltaic (GCPV) plant. 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7.397417 |