Modelling the Wind Speed Using Exponentiated Weibull Distribution: Case Study of Poprad-Tatry, Slovakia
In the paper, we statistically analysed data on the average hourly wind speed obtained from the meteorological station Poprad (located at the Poprad-Tatry airport, the Prešov region, Northern Slovakia) for the period 2005–2021. High altitude and rough mountainous terrain influence the weather condit...
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MDPI AG
2023-03-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/13/6/4031 |
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| author | Ivana Pobočíková Mária Michalková Zuzana Sedliačková Daniela Jurášová |
| author_facet | Ivana Pobočíková Mária Michalková Zuzana Sedliačková Daniela Jurášová |
| author_sort | Ivana Pobočíková |
| collection | DOAJ |
| description | In the paper, we statistically analysed data on the average hourly wind speed obtained from the meteorological station Poprad (located at the Poprad-Tatry airport, the Prešov region, Northern Slovakia) for the period 2005–2021. High altitude and rough mountainous terrain influence the weather conditions considerably and are a source of occasional weather risks. Finding an appropriate wind speed distribution for modelling the wind speed data is therefore important to determine the wind profile at this particular location. In addition to the commonly used two- and three-parameter Weibull distribution, a more flexible exponentiated Weibull (EW) distribution was applied to model the wind speed. Based on the results of the goodness-of-fit criteria (the Kolmogorov–Smirnov test, the Anderson–Darling test, Akaike’s and Bayesian information criteria, the root mean square error, and the coefficient of determination), the EW distribution obtained a significantly better fit to seasonal and monthly wind speed data, especially around the peaks of the data. The EW distribution also proved to be a good model for data with high positive skewness. Therefore, we can recommend the EW distribution as a flexible distribution for modelling a dataset with extremely strong winds or outliers in the direction of the right tail. Alongside the wind speed analysis, we also provided the wind direction analysis, finding out that the most prevailing direction was west (W)—with an occurrence rate of 34.99%, and a mean wind speed of 3.91 m/s, whereas the northern (N) direction featured the lowest occurrence rate of only 4.45% and the mean wind speed of 1.99 m/s. |
| first_indexed | 2024-03-11T06:57:28Z |
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| id | doaj.art-628aa433b16244adbaae94be74373fda |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-11T06:57:28Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-628aa433b16244adbaae94be74373fda2023-11-17T09:30:34ZengMDPI AGApplied Sciences2076-34172023-03-01136403110.3390/app13064031Modelling the Wind Speed Using Exponentiated Weibull Distribution: Case Study of Poprad-Tatry, SlovakiaIvana Pobočíková0Mária Michalková1Zuzana Sedliačková2Daniela Jurášová3Department of Applied Mathematics, Faculty of Mechanical Engineering, University of Žilina, Univerzitná 8215/1, 010 16 Žilina, SlovakiaDepartment of Applied Mathematics, Faculty of Mechanical Engineering, University of Žilina, Univerzitná 8215/1, 010 16 Žilina, SlovakiaDepartment of Applied Mathematics, Faculty of Mechanical Engineering, University of Žilina, Univerzitná 8215/1, 010 16 Žilina, SlovakiaDepartment of Building Engineering and Urban Planning, Faculty of Civil Engineering, University of Žilina, Univerzitná 8215/1, 010 16 Žilina, SlovakiaIn the paper, we statistically analysed data on the average hourly wind speed obtained from the meteorological station Poprad (located at the Poprad-Tatry airport, the Prešov region, Northern Slovakia) for the period 2005–2021. High altitude and rough mountainous terrain influence the weather conditions considerably and are a source of occasional weather risks. Finding an appropriate wind speed distribution for modelling the wind speed data is therefore important to determine the wind profile at this particular location. In addition to the commonly used two- and three-parameter Weibull distribution, a more flexible exponentiated Weibull (EW) distribution was applied to model the wind speed. Based on the results of the goodness-of-fit criteria (the Kolmogorov–Smirnov test, the Anderson–Darling test, Akaike’s and Bayesian information criteria, the root mean square error, and the coefficient of determination), the EW distribution obtained a significantly better fit to seasonal and monthly wind speed data, especially around the peaks of the data. The EW distribution also proved to be a good model for data with high positive skewness. Therefore, we can recommend the EW distribution as a flexible distribution for modelling a dataset with extremely strong winds or outliers in the direction of the right tail. Alongside the wind speed analysis, we also provided the wind direction analysis, finding out that the most prevailing direction was west (W)—with an occurrence rate of 34.99%, and a mean wind speed of 3.91 m/s, whereas the northern (N) direction featured the lowest occurrence rate of only 4.45% and the mean wind speed of 1.99 m/s.https://www.mdpi.com/2076-3417/13/6/4031wind speedtwo-parameter Weibull distributionthree-parameter Weibull distributionexponentiated Weibull distributiongoodness-of-fit criteria |
| spellingShingle | Ivana Pobočíková Mária Michalková Zuzana Sedliačková Daniela Jurášová Modelling the Wind Speed Using Exponentiated Weibull Distribution: Case Study of Poprad-Tatry, Slovakia Applied Sciences wind speed two-parameter Weibull distribution three-parameter Weibull distribution exponentiated Weibull distribution goodness-of-fit criteria |
| title | Modelling the Wind Speed Using Exponentiated Weibull Distribution: Case Study of Poprad-Tatry, Slovakia |
| title_full | Modelling the Wind Speed Using Exponentiated Weibull Distribution: Case Study of Poprad-Tatry, Slovakia |
| title_fullStr | Modelling the Wind Speed Using Exponentiated Weibull Distribution: Case Study of Poprad-Tatry, Slovakia |
| title_full_unstemmed | Modelling the Wind Speed Using Exponentiated Weibull Distribution: Case Study of Poprad-Tatry, Slovakia |
| title_short | Modelling the Wind Speed Using Exponentiated Weibull Distribution: Case Study of Poprad-Tatry, Slovakia |
| title_sort | modelling the wind speed using exponentiated weibull distribution case study of poprad tatry slovakia |
| topic | wind speed two-parameter Weibull distribution three-parameter Weibull distribution exponentiated Weibull distribution goodness-of-fit criteria |
| url | https://www.mdpi.com/2076-3417/13/6/4031 |
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