Cited 28 time in
Hourly Average Wind Speed Simulation and Forecast Based on ARMA Model in Jeju Island, Korea
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Do, Duy-Phuong N. | - |
| dc.contributor.author | Lee, Yeonchan | - |
| dc.contributor.author | Choi, Jaeseok | - |
| dc.date.accessioned | 2022-12-26T20:01:41Z | - |
| dc.date.available | 2022-12-26T20:01:41Z | - |
| dc.date.issued | 2016-11 | - |
| dc.identifier.issn | 1975-0102 | - |
| dc.identifier.issn | 2093-7423 | - |
| dc.identifier.uri | https://scholarworks.gnu.ac.kr/handle/sw.gnu/15187 | - |
| dc.description.abstract | This paper presents an application of time series analysis in hourly wind speed simulation and forecast in Jeju Island, Korea. Autoregressive moving average (ARMA) model, which is well in description of random data characteristics, is used to analyze historical wind speed data (from year of 2010 to 2012). The ARMA model requires stationary variables of data is satisfied by power law transformation and standardization. In this study, the autocorrelation analysis, Bayesian information criterion and general least squares algorithm is implemented to identify and estimate parameters of wind speed model. The ARMA (2,1) models, fitted to the wind speed data, simulate reference year and forecast hourly wind speed in Jeju Island. | - |
| dc.format.extent | 8 | - |
| dc.language | 영어 | - |
| dc.language.iso | ENG | - |
| dc.publisher | KOREAN INST ELECTR ENG | - |
| dc.title | Hourly Average Wind Speed Simulation and Forecast Based on ARMA Model in Jeju Island, Korea | - |
| dc.type | Article | - |
| dc.publisher.location | 대한민국 | - |
| dc.identifier.doi | 10.5370/JEET.2016.11.6.1548 | - |
| dc.identifier.scopusid | 2-s2.0-84991238167 | - |
| dc.identifier.wosid | 000387097700003 | - |
| dc.identifier.bibliographicCitation | JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY, v.11, no.6, pp 1548 - 1555 | - |
| dc.citation.title | JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY | - |
| dc.citation.volume | 11 | - |
| dc.citation.number | 6 | - |
| dc.citation.startPage | 1548 | - |
| dc.citation.endPage | 1555 | - |
| dc.type.docType | Article | - |
| dc.identifier.kciid | ART002157155 | - |
| dc.description.isOpenAccess | Y | - |
| dc.description.journalRegisteredClass | scie | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.description.journalRegisteredClass | kci | - |
| dc.relation.journalResearchArea | Engineering | - |
| dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
| dc.subject.keywordAuthor | Autoregressive moving average processes | - |
| dc.subject.keywordAuthor | Autoregressive processes | - |
| dc.subject.keywordAuthor | Autocorrelation function | - |
| dc.subject.keywordAuthor | Time series model | - |
| dc.subject.keywordAuthor | Wind energy | - |
| dc.subject.keywordAuthor | Wind speed forecast | - |
| dc.subject.keywordAuthor | Wind speed simulation | - |
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