Title :
Design of Transformer Substation Fault Prediction Algorithm Based on Modified ESN
Author :
Si Gang-quan ; Zhang Hong-ying ; Hu Luona
Author_Institution :
State Key Lab. of Electr. Insulation & Power Equip., Xi´an Jiaotong Univ., Xi´an, China
Abstract :
Temperature variation of some important nodes in the substation can reflect the danger operation of substation equipment. By predicting the temperature we can discover the potential hidden fault in the substation. An improved algorithm for predicting the temperature of the substation in this article is presented in this paper, which combines Echo State Network (ESN) and Local Average Denoising Method (LADM) in the phase space of time series. Simulation results show that this new algorithm acts well in predicting both noise-free time series and time series with high-level noise collected in the field.
Keywords :
power transformer testing; prediction theory; time series; transformer substations; danger operation; echo state network; high-level noise; local average denoising method; modified ESN; noise-free time series; phase space; potential hidden fault; substation equipment; temperature variation; transformer substation fault prediction algorithm; Delay; Noise; Prediction algorithms; Predictive models; Substations; Temperature measurement; Time series analysis;
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.2012.6307690
