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Wind Sector Classification Method based on Spatial Similarity of Wind Vector using Spatio-temporal Wind Data
시공간 바람자료를 이용한 바람벡터의 유사성에 따른 바람권역 분류 기법

DC Field Value Language
dc.contributor.advisor박형동-
dc.contributor.author김진솔-
dc.date.accessioned2017-07-14T03:18:59Z-
dc.date.available2017-07-14T03:18:59Z-
dc.date.issued2015-02-
dc.identifier.other000000024823-
dc.identifier.urihttp://hdl.handle.net/10371/123483-
dc.description학위논문 (석사)-- 서울대학교 대학원 : 에너지시스템공학부, 2015. 2. 박형동.-
dc.description.abstractMeasurement of wind is required for wind resource assessment. In region with complex topography, uniformity of wind speed and wind direction significantly decreases and a local wind system is formed. Therefore, clear understanding of local wind system is necessary for accurate wind resource assessment. In this study, wind sector classification method, applying cluster analysis based on spatial similarity of wind vector, was proposed to describe the local wind system more clearly. Wind sectors were classified using wind resource map and the validity of classification method was examined.
Wind sector classification was applied to Jeju island and Busan, where Jeju island has relatively simple terrain and Busan has complex one. Classification result corresponds to the study area’s topography and local wind system. Furthermore, wind characteristics of identical wind sector uniformly appeared and wind characteristics of distinct wind sectors appeared differently. The general validity of wind sector classification method was verified.
The proposed wind sector classification method is helpful to describe the local wind system. Moreover, this method can provide a basic information for wind resource assessment.
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dc.description.tableofcontentsChapter 1 Introduction 1

Chapter 2 Review on wind classification methods 3
2.1 Wind field classification methods 3
2.1.1 Classification based on temporal variability 3
2.1.2 Classification based on spatial similarity 4
2.2 Wind sector classification methods 5
2.2.1 Classification based on temporal variability 5
2.2.2 Classification based on spatial similarity 6

Chapter 3 Wind sector classification method 7
3.1 Definition of distance measure 7
3.2 Clustering Algorithm 8

Chapter 4 Data and study areas 10
4.1 KIER-WindmapTM 11
4.2 Jeju island 13
4.2.1 Location, topography of Jeju island 13
4.2.2 Wind condition of Jeju island 14
4.3 Busan 15
4.3.1 Location, topography of Busan 15
4.3.2 Wind condition of Busan 18


Chapter 5 Results and Discussion 20
5.1 Jeju island 20
5.1.1 Classification of wind sectors in Jeju island 20
5.1.2 Wind characteristics in Jeju island 22
5.1.3 Validity of wind sector classification in Jeju island 26
5.2 Busan 34
5.2.1 Classification of wind sectors in Busan 34
5.2.2 Wind characteristics in Busan 37
5.2.3 Validity of wind sector classification in Busan 45

Chapter 6 Conclusion 54

References 56

Abstract 59
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dc.formatapplication/pdf-
dc.format.extent3705563 bytes-
dc.format.mediumapplication/pdf-
dc.language.isoen-
dc.publisher서울대학교 대학원-
dc.subject풍계-
dc.subject바람권역-
dc.subject군집분석-
dc.subject풍력자원평가-
dc.subject.ddc622-
dc.titleWind Sector Classification Method based on Spatial Similarity of Wind Vector using Spatio-temporal Wind Data-
dc.title.alternative시공간 바람자료를 이용한 바람벡터의 유사성에 따른 바람권역 분류 기법-
dc.typeThesis-
dc.contributor.AlternativeAuthorJinsol Kim-
dc.description.degreeMaster-
dc.citation.pagesv, 59-
dc.contributor.affiliation공과대학 에너지시스템공학부-
dc.date.awarded2015-02-
Appears in Collections:
College of Engineering/Engineering Practice School (공과대학/대학원)Dept. of Energy Systems Engineering (에너지시스템공학부)Theses (Master's Degree_에너지시스템공학부)
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