Study on the Buildup of Big Data Web Platform for the Operation and Maintenance of Taiwan Offshore Wind Farm( II )

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基本資料

Project title

Translated Name/計畫中文名

臺灣離岸風場運維大數據網路平台建置研究( II )

Funding Organization/主管機關

National Science and Technology Council

Co-Investigator(s)/共同執行人

蔡進發(計畫主持人)
陳琪芳
洪鈺中
張瑞益
宋家驥
江允智
欣吳文
王昭男
陳雪如

Department/Unit

Department of Engineering Science and Ocean Engineering, NTU

Website

https://www.grb.gov.tw/search/planDetail?id=13338114

Year

2020

Start date/計畫起

01-01-2020

Expected Completion/計畫迄

31-12-2020

Co-Investigator(s)

Yih-Hwang Lin

Bugetid/研究經費

10250千元

ResearchField/研究領域

能源工程

本研究引用工業4.0的核心架構, 建置一大數據(Big Data)網路平台及離岸風場的虛實融合系統(Cyber Physical System)，蒐集台灣離岸風場運維所需的相關數據，經由虛實融合系統的演算法、AI的深度學習演算法，並實地量測離岸示範風機運作時的水下噪音，發展離岸風機水下噪音數值模式，提供台灣離岸風場運維所需的服務及策略，期望建立國內離岸風場的運維能量，本研究完成後所提供的服務包含： (1) 台灣離岸風場的大數據網路服務平台、 (2) 風機整體與關鍵元件健康指標及剩餘有效壽命預測、 (3) 基樁淘刷風險管理與因應策略、 (4) 風機葉片表面損傷的非接觸早期偵測、 (5) 離岸風機運作的水下噪音評估、 (5) 風場運維KPI(Key Performance Index)、最佳策略建議及運維成本 LCOE(Levelized Cost of Energy)預估。 A big data web platform and cyber physical system of the Taiwan offshore wind farm will be established based on the core framework of the industrial 4.0. The operational and maintenance data of the Taiwan offshore wind farm will be collected. The operational and maintenance service and strategy of the Taiwan wind far will be provided by using the algorithms of prognostic and health management, and artificial intelligent methods to process the collected data. The key performance indicators of the operation and maintenance of Taiwan offshore wind farm are expected to be established in this study. The underwater noise due to operations of wind turbines of The numerical model of the underwater noise due to the operation of the offshore wind turbine will be proposed and validated based on the measured noise. The following services and strategies of the operation and maintenance of Taiwan offshore wind farm will be provided in the big data web platform: (1)The service of the big data web of the Taiwan wind farm will be provided. (2)The prediction of the remaining useful life of whole wind turbine and the key components of the offshore wind turbines. (3)The risk analysis and management of the scouring of the offshore wind turbine foundation. (4)The early damage detection of the wind turbine surface by non-contact acoustic method. (5)The estimation method of the underwater noise due to the operation of the offshore wind farm will be provided. (6)The LCOE(Levelized Cost of Energy) will be estimated based on the (Key Performance Index) and operation and maintenance strategy of the offshore wind farm.

Keyword(s)

人工智慧
大數據網路平台
虛實整合系統
工業4.0
台灣離岸風場
Artificial Intelligence
Big Data Web Platform
Industrial 4.0
Taiwan Offshore Wind Farm

DSpace CRIS

Study on the Buildup of Big Data Web Platform for the Operation and Maintenance of Taiwan Offshore Wind Farm( II )

基本資料

Description