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An investigation of operating behavior characteristics of a wind power system using a fuzzy clustering method
- Authors
- Choi, Seongjin; Kim, Sungho
- Issue Date
- 15-Sep-2017
- Publisher
- PERGAMON-ELSEVIER SCIENCE LTD
- Keywords
- Fault monitoring; Fuzzy clustering; Operating behavior; Relative distance index; Wind power system
- Citation
- EXPERT SYSTEMS WITH APPLICATIONS, v.81, pp.244 - 250
- Indexed
- SCIE
SCOPUS
- Journal Title
- EXPERT SYSTEMS WITH APPLICATIONS
- Volume
- 81
- Start Page
- 244
- End Page
- 250
- ISSN
- 0957-4174
- Abstract
- A wind power system has diverse operating characteristics as its operations depend on many factors such as wind power, machinery ageing and breakdowns, etc. Knowledge of the operating behavior of the wind power system is helpful for monitoring its status and for isolating harmful elements when malfunctions occur, To investigate the operating status and behavior of the system, the fuzzy clustering method is introduced to classify the system's operating points. Relative distance indices of the cluster centers are defined to describe the operating behavior. With those, the location and operating behavior of the operating point are identified in relation to the cluster centers. (C) 2017 Elsevier Ltd. All rights reserved.
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Related Researcher
- Choi, Seong jin
- College of Science and Technology (Department of Electronics and Information Engineering)