Harmonics load signature recognition by wavelets transforms

Abstract

Power quality has become an important concern both to the utilities and their customers. End user equipment is often more sensitive to disturbances that exist both on the supplying power system and within the customer facilities. Power quality embraces problems caused by harmonics, over or under-voltages, or supply discontinuities. Harmonics are caused by all sorts of nonlinear loads. In order to fully understand the problems caused by harmonics pollution, an effective means of identifying sources of power harmonics is important. The authors used fuzzy numbers for harmonics signature recognition. In this paper, the authors have made use of new developments in wavelets so that each type of current waveform polluted with power harmonics can well be represented by a normalised energy vector consisting of five elements. Furthermore, a mixture of harmonics load can also be represented by a corresponding vector. This paper describes the mathematics and algorithms for arriving at the vectors, forming a strong foundation for real-time harmonics signature recognition, in particular useful to the re-structuring of the whole electric power industry.