Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 오기용 | - |
dc.date.accessioned | 2022-07-27T01:18:50Z | - |
dc.date.available | 2022-07-27T01:18:50Z | - |
dc.date.issued | 2020-10 | - |
dc.identifier.citation | MATHEMATICS, v. 8, no. 10, article no. 1795 | en_US |
dc.identifier.issn | 2227-7390 | - |
dc.identifier.uri | https://www.mdpi.com/2227-7390/8/10/1795 | - |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/171812 | - |
dc.description.abstract | Evaluating the economic feasibility of wind farms via long-term wind-resource assessments is indispensable because short-term data measured at a candidate wind-farm site cannot represent the long-term wind potential. Prediction errors are significant when seasonal and year-on-year variations occur. Moreover, reliable long-term reference data with a high correlation to short-term measured data are often unavailable. This paper presents an alternative solution to predict long-term wind resources for a site exhibiting seasonal and year-on-year variations, where long-term reference data are unavailable. An analysis shows that a mutually complementary measure-correlate-predict method can be employed, because several datasets obtained over short periods are used to correct long-term wind resource data in a mutually complementary manner. Moreover, this method is useful in evaluating extreme wind speeds, which is one of the main factors affecting site compliance evaluation and the selection of a suitable wind turbine class based on the International Electrotechnical Commission standards. The analysis also shows that energy density is a more sensitive metric than wind speed for sites with seasonal and year-on-year variations because of the wide distribution of wind speeds. A case study with short-term data measured at Fujeij, Jordan, clearly identifies the factors necessary to perform the reliable and accurate assessment of long-term wind potentials. | en_US |
dc.description.sponsorship | This work was supported by a National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2020R1C1C1003829). | en_US |
dc.language.iso | en | en_US |
dc.publisher | MDPI | en_US |
dc.subject | measure-correlate-predict | en_US |
dc.subject | site compliance | en_US |
dc.subject | wind-resource assessment | en_US |
dc.subject | wind potential prediction | en_US |
dc.title | Mutually Complementary Measure-Correlate-Predict Method for Enhanced Long-Term Wind-Resource Assessment | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.3390/math8101795 | - |
dc.relation.journal | MATHEMATICS | - |
dc.contributor.googleauthor | Nam, Woochul | - |
dc.contributor.googleauthor | Oh, Ki-Yong | - |
dc.relation.code | 2020047404 | - |
dc.sector.campus | S | - |
dc.sector.daehak | COLLEGE OF ENGINEERING[S] | - |
dc.sector.department | SCHOOL OF MECHANICAL ENGINEERING | - |
dc.identifier.pid | kiyongoh | - |
dc.identifier.orcid | https://orcid.org/0000-0003-2895-4749 | - |
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