Application of time–frequency representation in the study of the cyclical behavior of wind speed in Algeria: wavelet transform
Abstract This study proposes a process of assessment of wind potential using descriptive statistics and time–frequency analysis. Via the time–frequency analysis, the variation of the spectral content of wind speed with respect to time is analyzed by the determination of the frequencies, the duration...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Chellali, Farouk [verfasserIn] Khellaf, Abdallah [verfasserIn] Belouchrani, Adel [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2010 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Stochastic environmental research and risk assessment - Berlin : Springer, 1987, 24(2010), 8 vom: 10. Apr., Seite 1233-1239 |
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| Übergeordnetes Werk: |
volume:24 ; year:2010 ; number:8 ; day:10 ; month:04 ; pages:1233-1239 |
| Links: |
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| DOI / URN: |
10.1007/s00477-010-0388-x |
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| Katalog-ID: |
SPR006400485 |
|---|
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| 100 | 1 | |a Chellali, Farouk |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Application of time–frequency representation in the study of the cyclical behavior of wind speed in Algeria: wavelet transform |
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| 520 | |a Abstract This study proposes a process of assessment of wind potential using descriptive statistics and time–frequency analysis. Via the time–frequency analysis, the variation of the spectral content of wind speed with respect to time is analyzed by the determination of the frequencies, the durations and the occurrence-time of significant fluctuations. The study is carried out for six sites in Algeria during a time interval of 1 year and over a frequency range from 1.1 × $ 10^{−2} $ to 2.4 cycles/day (i.e., periods from 10 h to about 90 days). The study has allowed to deduce that the windiest regions are located in the southern part of the country with annual mean from 5 to 6 m/s. The time–frequency analysis reveals the presence of three types of oscillations. In the warm season, diurnal oscillations have been distinguished especially in the costal and mountainous regions. However, in the cold season, synoptic oscillations of periods around 9–13 days have been observed. The Southern regions are characterized by long oscillations of periods around 33–50 days. | ||
| 650 | 4 | |a Wind speed |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Wind potential |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Time–frequency analysis |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Wavelet transform |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Descriptive statistics |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Diurnal oscillations and synoptic oscillations |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Khellaf, Abdallah |e verfasserin |4 aut | |
| 700 | 1 | |a Belouchrani, Adel |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Stochastic environmental research and risk assessment |d Berlin : Springer, 1987 |g 24(2010), 8 vom: 10. Apr., Seite 1233-1239 |w (DE-627)27160235X |w (DE-600)1481263-0 |x 1436-3259 |7 nnns |
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10.1007/s00477-010-0388-x doi (DE-627)SPR006400485 (SPR)s00477-010-0388-x-e DE-627 ger DE-627 rakwb eng 550 ASE 43.03 bkl 58.50 bkl Chellali, Farouk verfasserin aut Application of time–frequency representation in the study of the cyclical behavior of wind speed in Algeria: wavelet transform 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This study proposes a process of assessment of wind potential using descriptive statistics and time–frequency analysis. Via the time–frequency analysis, the variation of the spectral content of wind speed with respect to time is analyzed by the determination of the frequencies, the durations and the occurrence-time of significant fluctuations. The study is carried out for six sites in Algeria during a time interval of 1 year and over a frequency range from 1.1 × $ 10^{−2} $ to 2.4 cycles/day (i.e., periods from 10 h to about 90 days). The study has allowed to deduce that the windiest regions are located in the southern part of the country with annual mean from 5 to 6 m/s. The time–frequency analysis reveals the presence of three types of oscillations. In the warm season, diurnal oscillations have been distinguished especially in the costal and mountainous regions. However, in the cold season, synoptic oscillations of periods around 9–13 days have been observed. The Southern regions are characterized by long oscillations of periods around 33–50 days. Wind speed (dpeaa)DE-He213 Wind potential (dpeaa)DE-He213 Time–frequency analysis (dpeaa)DE-He213 Wavelet transform (dpeaa)DE-He213 Descriptive statistics (dpeaa)DE-He213 Diurnal oscillations and synoptic oscillations (dpeaa)DE-He213 Khellaf, Abdallah verfasserin aut Belouchrani, Adel verfasserin aut Enthalten in Stochastic environmental research and risk assessment Berlin : Springer, 1987 24(2010), 8 vom: 10. Apr., Seite 1233-1239 (DE-627)27160235X (DE-600)1481263-0 1436-3259 nnns volume:24 year:2010 number:8 day:10 month:04 pages:1233-1239 https://dx.doi.org/10.1007/s00477-010-0388-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE 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_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_267 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_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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_2190 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_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 43.03 ASE 58.50 ASE AR 24 2010 8 10 04 1233-1239 |
| spelling |
10.1007/s00477-010-0388-x doi (DE-627)SPR006400485 (SPR)s00477-010-0388-x-e DE-627 ger DE-627 rakwb eng 550 ASE 43.03 bkl 58.50 bkl Chellali, Farouk verfasserin aut Application of time–frequency representation in the study of the cyclical behavior of wind speed in Algeria: wavelet transform 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This study proposes a process of assessment of wind potential using descriptive statistics and time–frequency analysis. Via the time–frequency analysis, the variation of the spectral content of wind speed with respect to time is analyzed by the determination of the frequencies, the durations and the occurrence-time of significant fluctuations. The study is carried out for six sites in Algeria during a time interval of 1 year and over a frequency range from 1.1 × $ 10^{−2} $ to 2.4 cycles/day (i.e., periods from 10 h to about 90 days). The study has allowed to deduce that the windiest regions are located in the southern part of the country with annual mean from 5 to 6 m/s. The time–frequency analysis reveals the presence of three types of oscillations. In the warm season, diurnal oscillations have been distinguished especially in the costal and mountainous regions. However, in the cold season, synoptic oscillations of periods around 9–13 days have been observed. The Southern regions are characterized by long oscillations of periods around 33–50 days. Wind speed (dpeaa)DE-He213 Wind potential (dpeaa)DE-He213 Time–frequency analysis (dpeaa)DE-He213 Wavelet transform (dpeaa)DE-He213 Descriptive statistics (dpeaa)DE-He213 Diurnal oscillations and synoptic oscillations (dpeaa)DE-He213 Khellaf, Abdallah verfasserin aut Belouchrani, Adel verfasserin aut Enthalten in Stochastic environmental research and risk assessment Berlin : Springer, 1987 24(2010), 8 vom: 10. Apr., Seite 1233-1239 (DE-627)27160235X (DE-600)1481263-0 1436-3259 nnns volume:24 year:2010 number:8 day:10 month:04 pages:1233-1239 https://dx.doi.org/10.1007/s00477-010-0388-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE 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_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_267 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_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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_2190 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_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 43.03 ASE 58.50 ASE AR 24 2010 8 10 04 1233-1239 |
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10.1007/s00477-010-0388-x doi (DE-627)SPR006400485 (SPR)s00477-010-0388-x-e DE-627 ger DE-627 rakwb eng 550 ASE 43.03 bkl 58.50 bkl Chellali, Farouk verfasserin aut Application of time–frequency representation in the study of the cyclical behavior of wind speed in Algeria: wavelet transform 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This study proposes a process of assessment of wind potential using descriptive statistics and time–frequency analysis. Via the time–frequency analysis, the variation of the spectral content of wind speed with respect to time is analyzed by the determination of the frequencies, the durations and the occurrence-time of significant fluctuations. The study is carried out for six sites in Algeria during a time interval of 1 year and over a frequency range from 1.1 × $ 10^{−2} $ to 2.4 cycles/day (i.e., periods from 10 h to about 90 days). The study has allowed to deduce that the windiest regions are located in the southern part of the country with annual mean from 5 to 6 m/s. The time–frequency analysis reveals the presence of three types of oscillations. In the warm season, diurnal oscillations have been distinguished especially in the costal and mountainous regions. However, in the cold season, synoptic oscillations of periods around 9–13 days have been observed. The Southern regions are characterized by long oscillations of periods around 33–50 days. Wind speed (dpeaa)DE-He213 Wind potential (dpeaa)DE-He213 Time–frequency analysis (dpeaa)DE-He213 Wavelet transform (dpeaa)DE-He213 Descriptive statistics (dpeaa)DE-He213 Diurnal oscillations and synoptic oscillations (dpeaa)DE-He213 Khellaf, Abdallah verfasserin aut Belouchrani, Adel verfasserin aut Enthalten in Stochastic environmental research and risk assessment Berlin : Springer, 1987 24(2010), 8 vom: 10. Apr., Seite 1233-1239 (DE-627)27160235X (DE-600)1481263-0 1436-3259 nnns volume:24 year:2010 number:8 day:10 month:04 pages:1233-1239 https://dx.doi.org/10.1007/s00477-010-0388-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE 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_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_267 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_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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_2190 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_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 43.03 ASE 58.50 ASE AR 24 2010 8 10 04 1233-1239 |
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10.1007/s00477-010-0388-x doi (DE-627)SPR006400485 (SPR)s00477-010-0388-x-e DE-627 ger DE-627 rakwb eng 550 ASE 43.03 bkl 58.50 bkl Chellali, Farouk verfasserin aut Application of time–frequency representation in the study of the cyclical behavior of wind speed in Algeria: wavelet transform 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This study proposes a process of assessment of wind potential using descriptive statistics and time–frequency analysis. Via the time–frequency analysis, the variation of the spectral content of wind speed with respect to time is analyzed by the determination of the frequencies, the durations and the occurrence-time of significant fluctuations. The study is carried out for six sites in Algeria during a time interval of 1 year and over a frequency range from 1.1 × $ 10^{−2} $ to 2.4 cycles/day (i.e., periods from 10 h to about 90 days). The study has allowed to deduce that the windiest regions are located in the southern part of the country with annual mean from 5 to 6 m/s. The time–frequency analysis reveals the presence of three types of oscillations. In the warm season, diurnal oscillations have been distinguished especially in the costal and mountainous regions. However, in the cold season, synoptic oscillations of periods around 9–13 days have been observed. The Southern regions are characterized by long oscillations of periods around 33–50 days. Wind speed (dpeaa)DE-He213 Wind potential (dpeaa)DE-He213 Time–frequency analysis (dpeaa)DE-He213 Wavelet transform (dpeaa)DE-He213 Descriptive statistics (dpeaa)DE-He213 Diurnal oscillations and synoptic oscillations (dpeaa)DE-He213 Khellaf, Abdallah verfasserin aut Belouchrani, Adel verfasserin aut Enthalten in Stochastic environmental research and risk assessment Berlin : Springer, 1987 24(2010), 8 vom: 10. Apr., Seite 1233-1239 (DE-627)27160235X (DE-600)1481263-0 1436-3259 nnns volume:24 year:2010 number:8 day:10 month:04 pages:1233-1239 https://dx.doi.org/10.1007/s00477-010-0388-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE 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_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_267 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_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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_2190 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_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 43.03 ASE 58.50 ASE AR 24 2010 8 10 04 1233-1239 |
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10.1007/s00477-010-0388-x doi (DE-627)SPR006400485 (SPR)s00477-010-0388-x-e DE-627 ger DE-627 rakwb eng 550 ASE 43.03 bkl 58.50 bkl Chellali, Farouk verfasserin aut Application of time–frequency representation in the study of the cyclical behavior of wind speed in Algeria: wavelet transform 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This study proposes a process of assessment of wind potential using descriptive statistics and time–frequency analysis. Via the time–frequency analysis, the variation of the spectral content of wind speed with respect to time is analyzed by the determination of the frequencies, the durations and the occurrence-time of significant fluctuations. The study is carried out for six sites in Algeria during a time interval of 1 year and over a frequency range from 1.1 × $ 10^{−2} $ to 2.4 cycles/day (i.e., periods from 10 h to about 90 days). The study has allowed to deduce that the windiest regions are located in the southern part of the country with annual mean from 5 to 6 m/s. The time–frequency analysis reveals the presence of three types of oscillations. In the warm season, diurnal oscillations have been distinguished especially in the costal and mountainous regions. However, in the cold season, synoptic oscillations of periods around 9–13 days have been observed. The Southern regions are characterized by long oscillations of periods around 33–50 days. Wind speed (dpeaa)DE-He213 Wind potential (dpeaa)DE-He213 Time–frequency analysis (dpeaa)DE-He213 Wavelet transform (dpeaa)DE-He213 Descriptive statistics (dpeaa)DE-He213 Diurnal oscillations and synoptic oscillations (dpeaa)DE-He213 Khellaf, Abdallah verfasserin aut Belouchrani, Adel verfasserin aut Enthalten in Stochastic environmental research and risk assessment Berlin : Springer, 1987 24(2010), 8 vom: 10. Apr., Seite 1233-1239 (DE-627)27160235X (DE-600)1481263-0 1436-3259 nnns volume:24 year:2010 number:8 day:10 month:04 pages:1233-1239 https://dx.doi.org/10.1007/s00477-010-0388-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE 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_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_267 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_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_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 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_2116 GBV_ILN_2118 GBV_ILN_2119 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_2190 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_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 43.03 ASE 58.50 ASE AR 24 2010 8 10 04 1233-1239 |
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Enthalten in Stochastic environmental research and risk assessment 24(2010), 8 vom: 10. Apr., Seite 1233-1239 volume:24 year:2010 number:8 day:10 month:04 pages:1233-1239 |
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Wind speed Wind potential Time–frequency analysis Wavelet transform Descriptive statistics Diurnal oscillations and synoptic oscillations |
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Stochastic environmental research and risk assessment |
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Chellali, Farouk @@aut@@ Khellaf, Abdallah @@aut@@ Belouchrani, Adel @@aut@@ |
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Via the time–frequency analysis, the variation of the spectral content of wind speed with respect to time is analyzed by the determination of the frequencies, the durations and the occurrence-time of significant fluctuations. The study is carried out for six sites in Algeria during a time interval of 1 year and over a frequency range from 1.1 × $ 10^{−2} $ to 2.4 cycles/day (i.e., periods from 10 h to about 90 days). The study has allowed to deduce that the windiest regions are located in the southern part of the country with annual mean from 5 to 6 m/s. The time–frequency analysis reveals the presence of three types of oscillations. In the warm season, diurnal oscillations have been distinguished especially in the costal and mountainous regions. However, in the cold season, synoptic oscillations of periods around 9–13 days have been observed. 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Chellali, Farouk |
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Chellali, Farouk ddc 550 bkl 43.03 bkl 58.50 misc Wind speed misc Wind potential misc Time–frequency analysis misc Wavelet transform misc Descriptive statistics misc Diurnal oscillations and synoptic oscillations Application of time–frequency representation in the study of the cyclical behavior of wind speed in Algeria: wavelet transform |
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application of time–frequency representation in the study of the cyclical behavior of wind speed in algeria: wavelet transform |
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Application of time–frequency representation in the study of the cyclical behavior of wind speed in Algeria: wavelet transform |
| abstract |
Abstract This study proposes a process of assessment of wind potential using descriptive statistics and time–frequency analysis. Via the time–frequency analysis, the variation of the spectral content of wind speed with respect to time is analyzed by the determination of the frequencies, the durations and the occurrence-time of significant fluctuations. The study is carried out for six sites in Algeria during a time interval of 1 year and over a frequency range from 1.1 × $ 10^{−2} $ to 2.4 cycles/day (i.e., periods from 10 h to about 90 days). The study has allowed to deduce that the windiest regions are located in the southern part of the country with annual mean from 5 to 6 m/s. The time–frequency analysis reveals the presence of three types of oscillations. In the warm season, diurnal oscillations have been distinguished especially in the costal and mountainous regions. However, in the cold season, synoptic oscillations of periods around 9–13 days have been observed. The Southern regions are characterized by long oscillations of periods around 33–50 days. |
| abstractGer |
Abstract This study proposes a process of assessment of wind potential using descriptive statistics and time–frequency analysis. Via the time–frequency analysis, the variation of the spectral content of wind speed with respect to time is analyzed by the determination of the frequencies, the durations and the occurrence-time of significant fluctuations. The study is carried out for six sites in Algeria during a time interval of 1 year and over a frequency range from 1.1 × $ 10^{−2} $ to 2.4 cycles/day (i.e., periods from 10 h to about 90 days). The study has allowed to deduce that the windiest regions are located in the southern part of the country with annual mean from 5 to 6 m/s. The time–frequency analysis reveals the presence of three types of oscillations. In the warm season, diurnal oscillations have been distinguished especially in the costal and mountainous regions. However, in the cold season, synoptic oscillations of periods around 9–13 days have been observed. The Southern regions are characterized by long oscillations of periods around 33–50 days. |
| abstract_unstemmed |
Abstract This study proposes a process of assessment of wind potential using descriptive statistics and time–frequency analysis. Via the time–frequency analysis, the variation of the spectral content of wind speed with respect to time is analyzed by the determination of the frequencies, the durations and the occurrence-time of significant fluctuations. The study is carried out for six sites in Algeria during a time interval of 1 year and over a frequency range from 1.1 × $ 10^{−2} $ to 2.4 cycles/day (i.e., periods from 10 h to about 90 days). The study has allowed to deduce that the windiest regions are located in the southern part of the country with annual mean from 5 to 6 m/s. The time–frequency analysis reveals the presence of three types of oscillations. In the warm season, diurnal oscillations have been distinguished especially in the costal and mountainous regions. However, in the cold season, synoptic oscillations of periods around 9–13 days have been observed. The Southern regions are characterized by long oscillations of periods around 33–50 days. |
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8 |
| title_short |
Application of time–frequency representation in the study of the cyclical behavior of wind speed in Algeria: wavelet transform |
| url |
https://dx.doi.org/10.1007/s00477-010-0388-x |
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true |
| author2 |
Khellaf, Abdallah Belouchrani, Adel |
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Khellaf, Abdallah Belouchrani, Adel |
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| doi_str |
10.1007/s00477-010-0388-x |
| up_date |
2024-07-03T22:49:40.310Z |
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| score |
7.402629 |