Title :
STLS algorithm for power quality indices estimation
Author :
Terzija, Vladimir ; Stanojevic, Vladimir
Author_Institution :
Manchester Univ., Manchester
Abstract :
Summary form only given. This paper introduces a new two-stage, self-tuning least squares (STLS) digital signal processing algorithm for power quality indices estimation according to the power components and power quality indices definitions given in the IEEE Standard 1459-2000. The algorithm is based on the non-recursive least error square technique accompanied with an tuning procedure, which generally improves the algorithm properties: the measurement range, the immunity to a random noise, convergence and the accuracy. The presented algorithm models typical signal distortions and it can be used for the real-time power quality indices estimation. In order to estimate signal spectra and fundamental frequency, current and voltage signals are processed in the first algorithm stage, whereas in the second stage the power components and power quality indices are calculated based on the results obtained from the first stage. To demonstrate the efficiency of the proposed algorithm, the results of computer simulated and laboratory tests are presented.
Keywords :
least squares approximations; power supply quality; power system analysis computing; power system parameter estimation; random noise; signal processing; IEEE Standard 1459-2000; digital signal processing algorithm; nonrecursive least error square technique; power components; random noise; real-time power quality indices estimation; signal distortion; two-stage self-tuning least squares algorithm; Convergence; Digital signal processing; Distortion measurement; Frequency estimation; Least squares approximation; Noise measurement; Power quality; Signal processing; Signal processing algorithms; Tuning;
Conference_Titel :
Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century, 2008 IEEE
Conference_Location :
Pittsburgh, PA
Print_ISBN :
978-1-4244-1905-0
Electronic_ISBN :
1932-5517
DOI :
10.1109/PES.2008.4596952