Parameter Estimation of Power System Signals Based on Cosine Self-Convolution Window With Desirable Side-Lobe Behaviors

Parameter estimation is an important topic in power system signal-processing tasks. A new class of windows, the cosine self-convolution window (CSCW), is proposed. The main-lobe and side-lobe behaviors of the first to the third order CSCWs are studied. A CSCW-based improved fast Fourier transform algorithm (FFT) for estimating power system signal parameters, such as frequency, phase, and amplitude, is given. The CSCW has a low peak side-lobe level, a high side-lobe decaying rate, and a simple spectral representation. Leakage errors and harmonic interferences are thus reduced considerably by weighting samples with the CSCW. The CSCW-based improved FFT algorithm can be easily implemented in embedded systems. The effectiveness of the proposed method was analyzed by means of computer simulations and practical experiments for multifrequency signals with the variations of the power system frequency as well as the presence of white noise and interhamonics.