Statistical approach for detection of fault and stable and unstable power swings based on signal energy

Abstract

Distance relays, as the main protection of the transmission lines, are prone to maloperation during power swings. Therefore, the detection of faults and stable and unstable power swings is vital in the proper operation of distance protection. The existence of a method that detects all of them with the same input and calculation can considerably reduce the computational burden of relays and accelerate the performance speed. Therefore, this paper proposes a new statistical approach for the detection of these disturbances based on the voltage energy signal as input. Three indices, including the proposed shape index (PSI) based on the kurtosis and skewness, the proposed dispersion index (PDI) based on the coefficient of variation, and the swing detection index (SDI), are presented to achieve this aim. The method is unaffected by current transformer saturation due to using only voltage signals. Moreover, the method has dynamic thresholds, whose equation coefficients are constant for any system with any voltage level. The method is tested on WSCC 9-bus and New England IEEE 39-bus test systems, considering challenging situations such as noise, high resistance faults, and different swing frequencies. The results of all cases of both test systems show that the method has 100% accuracy in the detection of faults with an average detection time of 0.69 ms in noise-free conditions, while, in noisy conditions, the fault detection accuracy and the average detection time are about 99.37%, and 1.75 ms, respectively. Furthermore, the detection accuracy of stable and unstable power swings is 100% with or without noise.