TY - GEN
T1 - An effective principal component regression method for transformer life management based on indirect parameters
AU - Li, Shiiun
AU - Yang, Liuqing
AU - Yan, Wei
AU - Cui, Huize
AU - Ge, Zhao
AU - Li, Shengtao
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/11/14
Y1 - 2018/11/14
N2 - Transformer life management has gained remarkable recognition due to its crucial role for safe operation of the power grid. Since transformer life is dominated by insulating state of its oil-paper insulation, the DP value has been traditionally regarded as the primary indicator. However, the DP sampling procedure is destructible and inconvenient. In this paper, we present an effective principal component regression method to assess the insulating state of oil-paper through indirectly estimating the degree of polymerization based on the aging characteristic parameter in oil. Thermal aging experiments were firstly conducted on palm oil and mineral oil impregnated paper, respectively. After aging experiments, aging characteristic parameters of oil were tested, including moisture, acidity, 2-furan, surface tension, dissolved gas-in-oil analysis, methanol, and ethanol. Principal component regression method was then performed to find the principal component and build a relationship between the degree of polymerization and the aging characteristic parameters of oil. After computation, the estimation of degree of polymerization value can be obtained with a high goodness of fitting, which is 0.92 and 0.78 for mineral oil and palm oil impregnated paper respectively. The estimation could be improved by data processing.
AB - Transformer life management has gained remarkable recognition due to its crucial role for safe operation of the power grid. Since transformer life is dominated by insulating state of its oil-paper insulation, the DP value has been traditionally regarded as the primary indicator. However, the DP sampling procedure is destructible and inconvenient. In this paper, we present an effective principal component regression method to assess the insulating state of oil-paper through indirectly estimating the degree of polymerization based on the aging characteristic parameter in oil. Thermal aging experiments were firstly conducted on palm oil and mineral oil impregnated paper, respectively. After aging experiments, aging characteristic parameters of oil were tested, including moisture, acidity, 2-furan, surface tension, dissolved gas-in-oil analysis, methanol, and ethanol. Principal component regression method was then performed to find the principal component and build a relationship between the degree of polymerization and the aging characteristic parameters of oil. After computation, the estimation of degree of polymerization value can be obtained with a high goodness of fitting, which is 0.92 and 0.78 for mineral oil and palm oil impregnated paper respectively. The estimation could be improved by data processing.
KW - degree of polymerization
KW - oilpaper insulation
KW - principal component regression method
KW - transformer life management
UR - https://www.scopus.com/pages/publications/85059083894
U2 - 10.1109/CMD.2018.8535897
DO - 10.1109/CMD.2018.8535897
M3 - 会议稿件
AN - SCOPUS:85059083894
T3 - 2018 Condition Monitoring and Diagnosis, CMD 2018 - Proceedings
BT - 2018 Condition Monitoring and Diagnosis, CMD 2018 - Proceedings
A2 - Abu-Siada, Ahmed
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th International Conference on Condition Monitoring and Diagnosis, CMD 2018
Y2 - 23 September 2018 through 26 September 2018
ER -