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A Two-Dimensional Cloud Model for Condition Assessment of HVDC Converter Transformers
State Key Laboratory of Power Transmission Equipment & System Security and New Technology, College of Electrical Engineering, Chongqing University, Chongqing 400030, China
HVDC Technology Research Department, Electric Power Research Institute, China Southern Power Grid, Guangzhou 510623, China
* Author to whom correspondence should be addressed.
Received: 18 November 2011; in revised form: 17 January 2012 / Accepted: 17 January 2012 / Published: 23 January 2012
Abstract: Converter transformers are the key and the most important components in high voltage direct current (HVDC) power transmission systems. Statistics show that the failure rate of HVDC converter transformers is approximately twice of that of transformers in AC power systems. This paper presents an approach integrated with a two-dimensional cloud model and an entropy-based weight model to evaluate the condition of HVDC converter transformers. The integrated approach can describe the complexity of HVDC converter transformers and achieve an effective assessment of their condition. Data from electrical testing, DGA, oil testing, and visual inspection were chosen to form the double-level assessment index system. Analysis results show that the integrated approach is capable of providing a relevant and effective assessment which in turn, provides valuable information for the maintenance of HVDC converter transformers.
Keywords: HVDC converter transformer; condition assessment; cloud model; entropy weight
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MDPI and ACS Style
Li, J.; He, Z.; Wang, Y.; Lv, J.; Zhao, L. A Two-Dimensional Cloud Model for Condition Assessment of HVDC Converter Transformers. Energies 2012, 5, 157-167.
Li J, He Z, Wang Y, Lv J, Zhao L. A Two-Dimensional Cloud Model for Condition Assessment of HVDC Converter Transformers. Energies. 2012; 5(1):157-167.
Li, Jian; He, Zhiman; Wang, Youyuan; Lv, Jinzhuang; Zhao, Linjie. 2012. "A Two-Dimensional Cloud Model for Condition Assessment of HVDC Converter Transformers." Energies 5, no. 1: 157-167.