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dc.contributor.authorChang, Wen-Yeauen_US
dc.contributor.authorChang, Po-Chuanen_US
dc.contributor.authorMiao, Ho-Chianen_US
dc.date.accessioned2017-04-21T06:48:33Z-
dc.date.available2017-04-21T06:48:33Z-
dc.date.issued2015en_US
dc.identifier.isbn978-1-5090-0076-0en_US
dc.identifier.issn2375-8244en_US
dc.identifier.urihttp://dx.doi.org/10.1109/CICN.2015.249en_US
dc.identifier.urihttp://hdl.handle.net/11536/136486-
dc.description.abstractThis paper proposes an adaptive network-based fuzzy inference system (ANFIS) based forecasting method for short-term wind power forecasting. An accurate forecasting method for power generation of the wind energy conversion system (WECS) is urgent needed under the relevant issues associated with the high penetration of wind power in the electricity system. To demonstrate the effectiveness of the proposed method, the method is tested on the practical information of wind power generation of a WECS installed on the Taichung coast of Taiwan. Good agreements between the realistic values and forecasting values are obtained; the test results show the proposed forecasting method is accurate and reliable.en_US
dc.language.isoen_USen_US
dc.subjectWind energy conversion systemen_US
dc.subjectWind power generation forecastingen_US
dc.subjectAdaptive network-based fuzzy inference systemen_US
dc.titleShort Term Wind Power Generation Forecasting Using Adaptive Network-Based Fuzzy Inference Systemen_US
dc.typeProceedings Paperen_US
dc.identifier.doi10.1109/CICN.2015.249en_US
dc.identifier.journal2015 INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND COMMUNICATION NETWORKS (CICN)en_US
dc.citation.spage1299en_US
dc.citation.epage1302en_US
dc.contributor.department電子工程學系及電子研究所zh_TW
dc.contributor.departmentDepartment of Electronics Engineering and Institute of Electronicsen_US
dc.identifier.wosnumberWOS:000387128200263en_US
dc.citation.woscount0en_US
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