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Due to nonlinear loads and other reasons, the power quality gets deteriorated and is of a major significance in recent times. In order to mitigate the problems due to power quality events such as sag, swell, interrupt, etc., good estimation of the parameters of the power quality events is required. Invariably, the power system waveforms get corrupted due to noise also. The estimation of the parameters and the removal of noise requires a time-frequency analysis. The discrete wavelet transform is highly suitable for time-frequency analysis due to its suitability for the analysis of nonstationary signals. In this paper, a method is proposed for the effective removal of the noise and the estimation of the parameters of the power quality events. Simulation results confirm the effectiveness of the proposed approach.

In recent times, due to the increased use of the reactive power, it is important to bill the electrical power consumption based on both the active and reactive power components. Reactive power is a very significant factor in electric power systems since it affects the efficiency of these systems. For this reason, the measurement of reactive energy is also important. Several methods are used to measure reactive power. Reactive energy meters provide accurate measurement only if the input is fundamental, because meters are constructed for operating under sinusoidal conditions. Due to the widespread use of nonlinear loads and natural disturbances such as lightning, the power quality of the waveforms is considerably deteriorated. As the corrupted waveforms are composed of nonstationary components also, in order to estimate the true reactive power of the power system fundamental component, a time-frequency analysis is required. Therefore, in this paper, a DWT based algorithm is proposed to effectively estimate the reactive power component of the power system.