Title :
A Comprehensive Assessment on the Online Monitoring Condition for Transformer Based on the Extension Theory
Author :
Long, Peng ; Sheng, Gehao ; Liu, Yadong ; Lv, Ming ; Jiang, Xiuchen ; Chen, Jing ; Cui, Ronghua
Author_Institution :
Dept. of Electr. Eng., Shanghai Jiaotong Univ., Shanghai, China
Abstract :
The effective assessment on the operation condition of power transformer is an important means to conduct the condition maintenance for transformer and to improve the reliability of power system. Based on the amount of information of all kinds of online monitoring conditions obtained from the transformer intelligent components, the assessment model for comprehensive condition of transformer is established in this study through the introduction of extension theory. First, with respect to the disadvantage that there is considerable subjectivity in constructing judgment matrix by the traditional analytic hierarchy process (AHP), a new method is adopted to construct the judgment matrix. The orthogonal experimental design method, finite element simulation as well as AHP are adopted to determine the weighting of condition information index with scientific and objective attitude; next, the framework for comprehensive assessment of transformer condition is established with the extension-based comprehensive assessment method to achieve the qualitative and quantitative assessment on the transformer condition. The method is proved to be correct and valid through analysis of examples.
Keywords :
condition monitoring; decision making; finite element analysis; maintenance engineering; matrix algebra; power system reliability; power transformers; AHP; comprehensive condition; condition information index; condition maintenance; extension theory; extension-based comprehensive assessment method; finite element simulation; judgment matrix; online monitoring condition; orthogonal experimental design method; power system reliability; power transformer operation condition; traditional analytic hierarchy process; transformer intelligent components; Correlation; Indexes; Maintenance engineering; Monitoring; Oil insulation; Power system stability; Power transformers;
Conference_Titel :
Power and Energy Engineering Conference (APPEEC), 2012 Asia-Pacific
Conference_Location :
Shanghai
Print_ISBN :
978-1-4577-0545-8
DOI :
10.1109/APPEEC.2012.6307630