Adaptive detection and classificaion system for power quality disturbances

Abstract

This paper describes an intelligent measurement system for Power Quality (PQ) assessment. Computational guts are based in Higher Order Statistics (HOS) and the intelligent decision system is based in the Case-Base Reasoning (CBR) paradigm, which could re-configure its parameter according to the power net conditions. The power signal characterization is done using a sliding window procedure, and calculating the variance, the skewness and the kurtosis over the points inside the window. Those values are introduced in the CBR system and the signal state is returned. If the signal is healthy, the system study the current HOS values for substitute the normal considerations of the CBR system. This procedure returns a precision over the 90%.