Optimal distribution modeling and multifractal analysis of wind speed in the complex terrain of Sichuan Province, China
Abstract Increasing drought events have threaten electricity supply security in the predominantly hydropower-based Sichuan Province. Wind power has the potential to complement hydropower, yet its complex fluctuations required a systematic assessment. Accordingly, we evaluated maximum likelihood esti...
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Nature Portfolio
2025-02-01
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| Online Access: | https://doi.org/10.1038/s41598-024-83798-2 |
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| author | Cun Zhan Renjuan Wei Lu Zhao Shijun Chen Chunying Shen |
| author_facet | Cun Zhan Renjuan Wei Lu Zhao Shijun Chen Chunying Shen |
| author_sort | Cun Zhan |
| collection | DOAJ |
| description | Abstract Increasing drought events have threaten electricity supply security in the predominantly hydropower-based Sichuan Province. Wind power has the potential to complement hydropower, yet its complex fluctuations required a systematic assessment. Accordingly, we evaluated maximum likelihood estimation and three goodness-of-fit tests to identify the optimal distribution model of daily wind speed records during 1961–2017 across 156 weather stations in Sichuan Province among six commonly used probability density distributions. The study further analyzed the spatiotemporal features of persistence and multifractality in wind speed records across various landform types using multifractal detrended fluctuation analysis. The principal outcomes of our study indicated that the generalized extreme value distribution served as the optimal model for fitting wind speeds in Sichuan Province, outperforming the commonly used Weibull distribution. Persistence was evident in all wind speed series as the Hurst index exceeds 0.5, with the strongest persistence in mountainous areas and the weakest in plains. Multifractality was confirmed by the non-linear dependencies of the Generalized Hurst Exponent [h(q)] and mass exponent [τ(q)] on q, as well as by the multifractal spectrum widths exceeding 0.05. Among landform types, plains exhibited the strongest multifractality, followed by plateaus, with mountains showing the weakest multifractality. Long-range correlations were identified as the primarily caused of multifractality, as indicated by narrower multifractal spectrum widths in both shuffled and surrogate series, and stronger narrowness in the shuffled series. The multifractal spectrum width of the mountain shuffle series, which slightly exceeded 0.05, further highlighted the determinative influence of long-range correlations. Considering these findings, the southwestern mountainous region emerges as the optimal area for wind farm development, given its stability (persistence) and moderate fluctuation complexity (multifractality), crucial for effective wind resource utilization in hydropower-dominated settings. Our study provides a novel approach to assessing wind resources and offers guidance for wind farm placement in complex terrain regions, supporting sustainable energy diversification in Sichuan Province. |
| format | Article |
| id | doaj-art-dd863beafdc24c78aff010aac5786f3b |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Nature Portfolio |
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| series | Scientific Reports |
| spelling | doaj-art-dd863beafdc24c78aff010aac5786f3b2025-02-09T12:34:24ZengNature PortfolioScientific Reports2045-23222025-02-0115111610.1038/s41598-024-83798-2Optimal distribution modeling and multifractal analysis of wind speed in the complex terrain of Sichuan Province, ChinaCun Zhan0Renjuan Wei1Lu Zhao2Shijun Chen3Chunying Shen4Faculty of Electric Power Engineering, Kunming University of Science and TechnologySichuan Water Conservancy Vocational CollegeState Key Laboratory of Hydraulics and Mountain River Engineering & College of Water Resource and Hydropower, Sichuan UniversityState Key Laboratory of Hydraulics and Mountain River Engineering & College of Water Resource and Hydropower, Sichuan UniversityFaculty of Electric Power Engineering, Kunming University of Science and TechnologyAbstract Increasing drought events have threaten electricity supply security in the predominantly hydropower-based Sichuan Province. Wind power has the potential to complement hydropower, yet its complex fluctuations required a systematic assessment. Accordingly, we evaluated maximum likelihood estimation and three goodness-of-fit tests to identify the optimal distribution model of daily wind speed records during 1961–2017 across 156 weather stations in Sichuan Province among six commonly used probability density distributions. The study further analyzed the spatiotemporal features of persistence and multifractality in wind speed records across various landform types using multifractal detrended fluctuation analysis. The principal outcomes of our study indicated that the generalized extreme value distribution served as the optimal model for fitting wind speeds in Sichuan Province, outperforming the commonly used Weibull distribution. Persistence was evident in all wind speed series as the Hurst index exceeds 0.5, with the strongest persistence in mountainous areas and the weakest in plains. Multifractality was confirmed by the non-linear dependencies of the Generalized Hurst Exponent [h(q)] and mass exponent [τ(q)] on q, as well as by the multifractal spectrum widths exceeding 0.05. Among landform types, plains exhibited the strongest multifractality, followed by plateaus, with mountains showing the weakest multifractality. Long-range correlations were identified as the primarily caused of multifractality, as indicated by narrower multifractal spectrum widths in both shuffled and surrogate series, and stronger narrowness in the shuffled series. The multifractal spectrum width of the mountain shuffle series, which slightly exceeded 0.05, further highlighted the determinative influence of long-range correlations. Considering these findings, the southwestern mountainous region emerges as the optimal area for wind farm development, given its stability (persistence) and moderate fluctuation complexity (multifractality), crucial for effective wind resource utilization in hydropower-dominated settings. Our study provides a novel approach to assessing wind resources and offers guidance for wind farm placement in complex terrain regions, supporting sustainable energy diversification in Sichuan Province.https://doi.org/10.1038/s41598-024-83798-2Wind power assessmentSpatiotemporal analysisEnergy securityProbability distributionMultifractality |
| spellingShingle | Cun Zhan Renjuan Wei Lu Zhao Shijun Chen Chunying Shen Optimal distribution modeling and multifractal analysis of wind speed in the complex terrain of Sichuan Province, China Scientific Reports Wind power assessment Spatiotemporal analysis Energy security Probability distribution Multifractality |
| title | Optimal distribution modeling and multifractal analysis of wind speed in the complex terrain of Sichuan Province, China |
| title_full | Optimal distribution modeling and multifractal analysis of wind speed in the complex terrain of Sichuan Province, China |
| title_fullStr | Optimal distribution modeling and multifractal analysis of wind speed in the complex terrain of Sichuan Province, China |
| title_full_unstemmed | Optimal distribution modeling and multifractal analysis of wind speed in the complex terrain of Sichuan Province, China |
| title_short | Optimal distribution modeling and multifractal analysis of wind speed in the complex terrain of Sichuan Province, China |
| title_sort | optimal distribution modeling and multifractal analysis of wind speed in the complex terrain of sichuan province china |
| topic | Wind power assessment Spatiotemporal analysis Energy security Probability distribution Multifractality |
| url | https://doi.org/10.1038/s41598-024-83798-2 |
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