Validity Evaluation Method of DGA Monitoring Sensor in Power Transformer Based on Chaos Theory

Power transformer is one of the key electrical apparatus in power system, whose reliability has a directly correlation on the safety of power system. The concentration of dissolved gas in oil can be got by DGA online monitoring technology, and then the latent fault of transformer could be found in time. However, with the widespread use of on-line monitoring technology, the scale of monitoring data is also expanding, which is up to TB magnitude, forming on-line monitoring large data. At the same time, complex operating environment results in the emergence of a large number of invalid monitoring devices, which reduces the reliability of the monitoring system. Therefore, how to extract valid data from massive data and evaluate the monitoring device is an urgent problem to be solved. A validity assess method of DGA sensors in power transformer oil based on chaos theory is proposed in this paper. Firstly, the chaotic characteristics of oil chromatographic monitoring time series are qualitatively demonstrated. And the Lyapunov exponent is used as quantitative judgment. Then, according to the contraction characteristics of the chaotic phase space, the selection method of the optimal analysis data is given to solve the problem of excessive data. Finally, an assess method of DGA monitoring devices based on Lyapunov exponent and the optimal length selection is proposed. Verification test over a real case in the field shows that the method proposed in this paper is able to accurately evaluate the validity of DGA monitoring devices, whose detection rate of the failure monitoring device is up to 100%. Relative to traditional methods, the optimal length selection method proposed in this paper can effectively reduce the computational data, improve calculation efficiency and the efficiency of DGA monitoring devices validity assess method.