Comprehensive evaluation of wind speed distribution models: A case study for North Dakota sites

Accurate analysis of long term wind data is critical to the estimation of wind energy potential for a candidate location and its nearby area. Investigating the wind speed distribution is one critical task for this purpose. This paper presents a comprehensive evaluation on probability density functio...

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Veröffentlicht in:Energy conversion and management Jg. 51; H. 7; S. 1449 - 1458
Hauptverfasser: Zhou, Junyi, Erdem, Ergin, Li, Gong, Shi, Jing
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Kidlington Elsevier Ltd 01.07.2010
Elsevier
Schlagworte:
Applied sciences
Energy
Exact sciences and technology
Goodness-of-fit
Maximum entropy principle (MEP)
Natural energy
Probability density function (PDF)
Wind energy
Wind speed
United States
North America
North Dakota
America
USA, North Dakota
Probability density function (PDF)
Wind speed
Goodness-of-fit
Maximum entropy principle (MEP)
Case study
Wind energy
Probability density function
Wind velocity
ISSN:0196-8904, 1879-2227
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Zusammenfassung:Accurate analysis of long term wind data is critical to the estimation of wind energy potential for a candidate location and its nearby area. Investigating the wind speed distribution is one critical task for this purpose. This paper presents a comprehensive evaluation on probability density functions for the wind speed data from five representative sites in North Dakota. Besides the popular Weibull and Rayleigh distributions, we also include other distributions such as gamma, lognormal, inverse Gaussian, and maximum entropy principle (MEP) derived probability density functions (PDFs). Six goodness-of-fit (GOF) statistics are used to determine the appropriate distributions for the wind speed data for each site. It is found that no particular distribution outperforms others for all five sites, while Rayleigh distribution performs poorly for most of the sites. Similar to other models, the performances of MEP-derived PDFs in fitting wind speed data varies from site to site. Also, the results demonstrate that MEP-derived PDFs are flexible and have the potential to capture other possible distribution patterns of wind speed data. Meanwhile, different GOF statistics may generate inconsistent ranking orders of fit performance among the candidate PDFs. In addition, one comprehensive metric that combines all individual statistics is proposed to rank the overall performance for the chosen statistical distributions.
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ISSN:0196-8904
1879-2227
DOI:10.1016/j.enconman.2010.01.020