Open AccessDetecting Power Voltage Dips using Tracking Filters - A Comparison against Kalman
Author(s) -
R. Stanciu,
Florin Molnar-Matei
Publication year - 2012
Publication title -
advances in electrical and computer engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 23
eISSN - 1844-7600
pISSN - 1582-7445
DOI - 10.4316/aece.2012.04012
Subject(s) - kalman filter , tracking (education) , voltage , control theory (sociology) , power (physics) , computer science , engineering , artificial intelligence , electrical engineering , psychology , physics , control (management) , pedagogy , quantum mechanics
Due of its significant economical impact, Power-Quality (PQ) analysis is an important domain today. Severe voltage distortions affect the consumers and disturb their activity. They may be caused by short circuits (in this case the voltage drops significantly) or by varying loads (with a smaller drop). These two types are the PQ currently issues. Monitoring these phenomena (called dips or sags) require powerful techniques. Digital Signal Processing (DSP) algorithms are currently employed to fulfill this task. Discrete Wavelet Transforms, (and variants), Kalman filters, and S-Transform are currently proposed by researchers to detect voltage dips. This paper introduces and examines a new tool to detect voltage dips: the so-called tracking filters. Discovered and tested during the cold war, they can estimate a parameter of interest one-step-ahead based on the previously observed values. Two filters are implemented. Their performance is assessed by comparison against the Kalman filter?s results