Design of Dissolved Gas Analysis System and Application of Data Mining to Transformer Dissolved Gas Analysis

• Main Authors: Tai-li Chen, 陳泰利
• Other Authors: 姚立德
• Format: Others
• Language: zh-TW
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/66bcrv

碩士 === 國立臺北科技大學 === 電機工程系研究所 === 99 === Taiwan Power Company (TPC) has designed and installed a system called Substation Facility Maintenance and Management System (SFMMS). The fundamental data, inspection results and maintenance historical records for all of TPC’s primary substations and distribution substations have been built up and stored in FFMMS. Various data inquiry and management can be easily conducted through SFMMS. Moreover, annual work scheduling can be generated with SFMMS. The facility testing records such as total combustible gases (TCG), SF6 and dissolved gas analysis can be saved and managed in the SSFMS as well. Dissolved gas analysis (DGA) is widely used to detect incipient faults in transformers. It is shown how the accuracy of DGA research results can affect the reliability of DGA diagnosis. The minimum gas levels in service above which diagnoses may be attempted are indicated, as well as the gas levels observed before fault. In order to further improve the effect and efficiency of SSFMS so that the goal of facility condition-based maintenance can be attained, a software system for dissolved gas analyses will be developed in SSFMS. The international standards such as IEC, IEC increments, IEEE and Japanese Electric Association standard will be utilized in the software system to be designed for transformer dissolved gas analyses aiming to improve the effect and efficiency of transformer preventive maintenance. In this paper, we designs data mining decision tree (ID3/C4.5) with the main gases include H2, CH4, C2H2, C2H4 and C2H6 called total combustible gas (TCG). It can be observed a power transformer’s condition. In the further, prevent an unexpected which is unable to avoid.