Dynamic Voltage Stability Estimation using Particle Filter
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Dynamic Voltage Stability Estimation using Particle Filter

Authors: Osea Zebua, Norikazu Ikoma, Hiroshi Maeda

Abstract:

Estimation of voltage stability based on optimal filtering method is presented. PV curve is used as a tool for voltage stability analysis. Dynamic voltage stability estimation is done by using particle filter method. Optimum value (nose point) of PV curve can be estimated by estimating parameter of PV curve equation optimal value represents critical voltage and condition at specified point of measurement. Voltage stability is then estimated by analyzing loading margin condition c stimating equation. This maximum loading ecified dynamically.

Keywords: normalized PV curve, optimal filtering method particle filter, voltage stability.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1330499

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References:


[1] Carson W Taylor, "Power System Voltage Stability", McGraw-Hill, 1993.
[2] H.K. Clark, "New challenge: voltage stability", IEEE Power Engineering Review, vol.10, no.4, pp.33-37, 1990.
[3] B. Milosevic, M. Begovic, "Voltage stability protection and control using wide-area network of phasor measurements", IEEE Trans. on Power System, vol.18, no.1, pp.121-127, February, 2003.
[4] S. Corsi, G. Taranto, "A real-time voltage instability identification algorithm based on local phasor measurements", IEEE Trans. on Power System, vol.23, no.3, pp.1271-1280, August, 2008.
[5] K.Vu, M.M. Begovic, D.Novosel, M.M. Saha, "Use of local measurement to estimate voltage stability margin", IEEE Trans. on Power System, vol.14, no.3, pp.1029-1036, 1999.
[6] M. Larsson, C. Rehtanz, J. Bertsch, "Real-time voltage stability assessment of transmission corridors," IFAC Symp. Power Plants and Power Systems Control, Seoul, Korea, 2002.
[7] M.H. Haque, "On-line monitoring of maximum permissible loading of a power system within voltage stability limits", IEE Proc. Generation, Transmission and Distribution, vol.150, no.1, pp.107-112, January 2003.
[8] E.A. Wan, R. van der Merwe, "The Unscented Kalman Filter for Nonlinear Estimation", Proc. of IEEE Symp.2000 on Adaptive Systems for Signal Processing, Communication and Control (AS-SPCC), October 2000.
[9] N. J. Gordon, D.J. Salmond, and A.F.M. Smith, "Novel approach to Non-linear/Non-Gaussian Bayesian State Estimation", IEEE Proceedings F on Radar and Signal Processing, vol. 140, no.2, pp.107-113, 1993.
[10] J. Machowski, J. W. Bialek, J. Bumby, "Power System Dynamic: Stability and Control", 2nd edition, John-Wiley and Sons, 2008, pp.300-303.
[11] K. Madsen, N.B. Nielsen, and O.Tingleff, "Methods for Non-linear Least Squares Problems", Technical Report. Informatics and Mathematical Modeling, Technical University of Denmark, 2004.
[12] A. Doucet, N. De Freitas, and N.J. Gordon, "Sequential Monte Carlo Methods in Practice", Springer Verlag, 2001.
[13] M.S. Arulampalam, S. Maskell, N. Gordon and T. Clapp, "A Tutorial on Particle Filters for On-line Non-linear/Non-Gaussian Bayesian Tracking", IEEE Trans. on Signal Processing, vol.50, no.2, pp.174-188, February 2002.