Fuzzy classification based identification of voltage sag via wavelets

Abstract

Increasing awareness of power quality issues, deregulation, use of consumer devices sensitive to power system disturbance and possibility of making up some of the inherent design limitations through monitoring based operational strategies have created a need for extensive monitoring of the power system operation. Voltage disturbance is a common phenomenon in electric power distribution system operation.A fuzzy diagnostic procedure is proposed for detecting cause of voltage disturbance, so that appropriate remedial procedures could be initiated during system operation. Th method uses indices like PN factor, characteristic voltage, and zero sequence voltage and also proposes an index termed frequency jump index, extracted from zero sequence voltage using wavelets.

A survey on voltage dip events in power systems

“…A review about the methods used to extract knowledge from dips registers is performed in this paper. These methods differ according the power quality monitoring goal but all of them follow data mining principles and steps [32]: (1) definition of the objectives for analysis, (2) selection, organisation and pre-treatment of data, (3) exploratory Analysis of data and subsequent transformation, (4) specification of the methods to be used in the analysis phase, (5) analysis of the data based on the chosen methods, (6) evaluation and comparison of the methods used and the choice of the final model for analysis, (7) interpretation of the chosen model and its subsequent use in the decision processes.…”

“…These two features contain information about the type and unbalance grade of the voltage dip, respectively [28][6] [7]. These features are calculated with two algorithms: Six-phase and Symmetrical component.…”

A survey on voltage sag events in power systems

“…2) RCV and PN factor F: These features containing information about the type and unbalance grade of the voltage sag, respectively [11][2] [36].…”

Técnicas para a detecção, classificação e localização no tempo das variações de tensão de curta e longa duração

“…Uma técnica para detectar as causas de afundamentos de tensão utilizando TW e SF é proposta por Mukerjee et al em [24] e [25]. Utiliza-se da TW para extração das característi- Zhu et al [28] propõem um sistema de reconhecimento e identificação para seis tipos de distúrbios relacionados à QEE utilizando a TW e SF.…”