Signal Processing for Improving Power Quality

The wide spread use of power electronic equipment causes serious current harmonics in electrical power system. Harmonic currents that flow in the electrical power system would cause extra copper loss and immature operation of over current protection devices. Voltage distortion due to harmonic voltage drop in the electrical power distribution system impairs the operation of voltage-sensitive equipment. To improve the electrical power quality and reduce energy wastage in the electrical power distribution system, especially under the deregulated environment, the nature of the harmonics must be identified so that the causes and effects of the harmonics would be studied. Moreover, corrective measures cannot be easily implemented without knowing the characteristics of the harmonics existing in the electrical power system. The chapter presents investigation results obtained from the harmonics analysis and modeling of load forecast and consists of three main sections. The first presents an algorithm based on continuous wavelet transform (CWT) to identify harmonics in a power signal. The new algorithm is able to identify the frequencies, amplitudes, and phase information of all distortion harmonic components, including integer harmonics, sub-harmonics, and inter-harmonics. The second section describes a wavelet transform-based algorithm for reconstructing the harmonic waveforms from the complex CWT coefficients. This is useful for identifying the amplitude variations of the nonstationary harmonics over the estimation period. The third section presents wavelet-genetic algorithm-neural network-based hybrid model for accurate prediction of short-term load forecast. Examples and case study will be used to demonstrate the benefits derived from these approaches.