Fuzzy Metrology-Sound Approach to the Identification of Sources Injecting Periodic Disturbances in Electric Networks

The identification of sources injecting periodic disturbances in electric systems is a critical point in the assessment of the electric power quality. The available methods, based on a deterministic approach, do not always provide correct results. Methods based on heuristic approaches, such as those based on a fuzzy inference system (FIS), provide better results but do not allow measurement uncertainty to be evaluated in a straightforward way. This paper applies a modified FIS to the identification of the sources producing periodic distortion in power systems. The method associates an index, provided together with its measurement uncertainty, to each load connected to a point of common coupling capable of assessing whether the load is injecting or suffering distortion and quantifying the severity of the injected or suffered distortion.

I. Introduction

A general increment of the level of distortion of currents and voltages is nowadays contributing to the general deterioration of the electric power quality (PQ). This problem becomes even more critical in deregulated electricity markets, since any disturbance injected in the electric system propagates in the system, thus causing other loads to draw a distorted current. If the source injecting disturbances is not correctly identified, then this may cause disturbed loads to appear as if they were disturbing, thus also opening legal issues in addition to the technical and economical issues [1].