成果報告書詳細
管理番号20160000000594
タイトル*平成27年度中間年報 風力等自然エネルギー技術研究開発 風力発電高度実用化研究開発 スマートメンテナンス技術研究開発(分析)(リスク解析等)
公開日2016/7/7
報告書年度2015 - 2015
委託先名国立大学法人東京大学  国立研究開発法人産業技術総合研究所
プロジェクト番号P13010
部署名新エネルギー部
和文要約
英文要約The aim of this project is to develop maintenance technology that will enable a target availability of 95% in the wind power sector. This project will also focus on insurance and certification applicability in order to solve issues caused by inappropriate wind turbine maintenance or technical deficiencies, including decreases in availability, increases in the number of malfunctions, and increases in the amount of time that a wind turbine is shut down. As part of this project, it is developing that high efficiency maintenance technology that will contribute to improving the equipment usage rate of wind turbine in Japan. With this proposal, maintenance technology that will make it possible to achieve an availability of 95% will be developed in close collaboration with the development of smart maintenance technology organized as a separately subsidized project, and effective schemes for the appropriate use thereof in wind energy projects will be examined. The maintenance of wind turbines includes periodic maintenance to confirm their soundness and detect abnormalities at an early stage and maintenance that is implemented when a problem occurs, which involves identifying the location of the problem and implementing appropriate measures. To improve the efficiency of these types of maintenance and prevent a malfunction before it occurs, this project will be developing the analysis method of a Condition Monitoring System (CMS) that monitors the conditions of wind turbine components for detecting a malfunction. With the commissioned project, the content of operation logs and work logs for wind turbines and wind farms in Japan will be carefully examined through efforts that will include questionnaires and interviews. A database of maintenance conditions, operation conditions, and troubleshooting for various types of SCADA errors will also be designed and analyzed. In addition, the various sensor waveform data that represents data on wind turbine conditions obtained in a separately subsidized project will be analyzed (analysis of high order local autocorrelation characteristics, invariant analysis), and a maintenance information platform that will contribute to the early detection of wind turbine problems and to improving maintenance efficiency will be designed. In order to promote the development of effective maintenance technology, a close examination of the maintenance technology and the project impact will be conducted, the improvement effect on wind power generation projects will be quantified, and applicability in insurance and the like will be examined.
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