Integrated technical analysis of wind speed data for wind energy potential assessment in parts of southern and central Nigeria
Ten years daily mean wind speed data from thirteen cities in Central and Southern Nigeria were analyzed using six different methods (graphical, empirical methods of Justus and Lysten, method of moment, maximum likelihood method and energy pattern factor) of estimating Weibull parameters. The study w...
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| Format: | Article |
| Language: | English |
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Elsevier
2021-06-01
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| Series: | Cleaner Engineering and Technology |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666790821000094 |
| _version_ | 1819140998281822208 |
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| author | Ubong C. Ben Anthony E. Akpan Charles C. Mbonu Chika H. Ufuafuonye |
| author_facet | Ubong C. Ben Anthony E. Akpan Charles C. Mbonu Chika H. Ufuafuonye |
| author_sort | Ubong C. Ben |
| collection | DOAJ |
| description | Ten years daily mean wind speed data from thirteen cities in Central and Southern Nigeria were analyzed using six different methods (graphical, empirical methods of Justus and Lysten, method of moment, maximum likelihood method and energy pattern factor) of estimating Weibull parameters. The study was directed at assessing wind characteristics, variation pattern, wind power potential and rate the performance of the various estimation tools. Results indicate that the respective variations in minimum and maximum monthly mean wind speeds at 50 m are 3.53 (Afikpo) to 6.63 (Obudu) in October, and 4.62 (Abuja) to 9.16 m/s (Obudu) in April respectively. Annual mean wind speeds range from 4.06 in Afikpo to 8.01 m/s in Obudu. Obudu has highest monthly and annual wind power densities of 435.00 and 307.78W/m2, respectively while corresponding minimum of 30.52 and 46.02W/m2 were observed in Afikpo. Gboko (k = 4.53) has the steadiest wind regime while Abuja (k = 2.49) has the least. The wind speeds vary with location, elevation and season. Cities in Central and Southern parts of Nigeria belong to wind power classes 1–4. However, in Obudu, where elevation is higher than 1000 m, installation of a wind turbine with moderate power rating was recommended. Performance ratings of the various techniques adopted in the study, assessed using coefficient of determination, root mean square technique, mean bias error and mean absolute percentage error, show that the maximum likelihood method is a better technique for accurate estimation of the Weibull parameters, while the graphical method was the least performing technique. |
| first_indexed | 2024-12-22T11:47:27Z |
| format | Article |
| id | doaj.art-76f8bbb3fa834eedb774116f157978cf |
| institution | Directory Open Access Journal |
| issn | 2666-7908 |
| language | English |
| last_indexed | 2024-12-22T11:47:27Z |
| publishDate | 2021-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Cleaner Engineering and Technology |
| spelling | doaj.art-76f8bbb3fa834eedb774116f157978cf2022-12-21T18:27:06ZengElsevierCleaner Engineering and Technology2666-79082021-06-012100049Integrated technical analysis of wind speed data for wind energy potential assessment in parts of southern and central NigeriaUbong C. Ben0Anthony E. Akpan1Charles C. Mbonu2Chika H. Ufuafuonye3Applied Geophysics Programme, Department of Physics, University of Calabar, Nigeria; Corresponding author.Applied Geophysics Programme, Department of Physics, University of Calabar, NigeriaDepartment of Physics, University of Uyo, NigeriaApplied Geophysics Programme, Department of Physics, University of Calabar, NigeriaTen years daily mean wind speed data from thirteen cities in Central and Southern Nigeria were analyzed using six different methods (graphical, empirical methods of Justus and Lysten, method of moment, maximum likelihood method and energy pattern factor) of estimating Weibull parameters. The study was directed at assessing wind characteristics, variation pattern, wind power potential and rate the performance of the various estimation tools. Results indicate that the respective variations in minimum and maximum monthly mean wind speeds at 50 m are 3.53 (Afikpo) to 6.63 (Obudu) in October, and 4.62 (Abuja) to 9.16 m/s (Obudu) in April respectively. Annual mean wind speeds range from 4.06 in Afikpo to 8.01 m/s in Obudu. Obudu has highest monthly and annual wind power densities of 435.00 and 307.78W/m2, respectively while corresponding minimum of 30.52 and 46.02W/m2 were observed in Afikpo. Gboko (k = 4.53) has the steadiest wind regime while Abuja (k = 2.49) has the least. The wind speeds vary with location, elevation and season. Cities in Central and Southern parts of Nigeria belong to wind power classes 1–4. However, in Obudu, where elevation is higher than 1000 m, installation of a wind turbine with moderate power rating was recommended. Performance ratings of the various techniques adopted in the study, assessed using coefficient of determination, root mean square technique, mean bias error and mean absolute percentage error, show that the maximum likelihood method is a better technique for accurate estimation of the Weibull parameters, while the graphical method was the least performing technique.http://www.sciencedirect.com/science/article/pii/S2666790821000094Renewable energyMean wind speedWind power densityWeibullNigeria |
| spellingShingle | Ubong C. Ben Anthony E. Akpan Charles C. Mbonu Chika H. Ufuafuonye Integrated technical analysis of wind speed data for wind energy potential assessment in parts of southern and central Nigeria Cleaner Engineering and Technology Renewable energy Mean wind speed Wind power density Weibull Nigeria |
| title | Integrated technical analysis of wind speed data for wind energy potential assessment in parts of southern and central Nigeria |
| title_full | Integrated technical analysis of wind speed data for wind energy potential assessment in parts of southern and central Nigeria |
| title_fullStr | Integrated technical analysis of wind speed data for wind energy potential assessment in parts of southern and central Nigeria |
| title_full_unstemmed | Integrated technical analysis of wind speed data for wind energy potential assessment in parts of southern and central Nigeria |
| title_short | Integrated technical analysis of wind speed data for wind energy potential assessment in parts of southern and central Nigeria |
| title_sort | integrated technical analysis of wind speed data for wind energy potential assessment in parts of southern and central nigeria |
| topic | Renewable energy Mean wind speed Wind power density Weibull Nigeria |
| url | http://www.sciencedirect.com/science/article/pii/S2666790821000094 |
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