Adaptive Kalman Filtering in fault classification

Details Adaptive Kalman Filtering in fault classification Adaptive Kalman Filtering in fault classification

1987-05-19

1989-03-14

Lall, Parshotam S.

Boots, shoes, and leggings

324512, 361 80, 364483, G06F 1520, G01R 3108

Patent

active

048129950

ABSTRACT:
An Adaptive Kalman Filtering scheme for statistically predicting the occurence and type of a fault on a three phase power transmission line. Additionally, estimations of the steady-state postfault phasor quantities, distance protection and fault location information is provided. Current and voltage data for each phase is processed in two separate Adaptive Kalman Filtering models simultaneously. One model assumes that the phase is unfaulted, while the other model assumes the features of a faulted phase. The condition of the phase, faulted or unfaulted, is then decided from the computed a posteriori probabilities. Upon the secure identification of the condition of the phase, faulted or unfaulted, the corresponding Adaptive Kalman Filtering model continues to obtain the best estimates of the current or voltage state variables. Thus, the Adaptive Kalman Filtering model having the correct initial assumptions adapts itself to the actual condition of the phase faulted or unfaulted. Upon convergence of the computed a posteriori probabilities indicative of a faulted phase to highly accurate values, the type of fault is classified and the appropriate current and voltage pairs are selected to compute fault location and to provide distance protection. The voltage models are two state variable Adaptive Kalman Filtering schemes. The model for the current with no fault condition is two state variable, while the model that assumes that the phase is faulted is a three state variable model. Estimation convergence reached exact values within half a cycle and consequently, in the same time fault location was determined.

REFERENCES:
patent: 4455612 (1984-06-01), Girgis et al.
patent: 4472812 (1984-09-01), Sakaki et al.
patent: 4499417 (1985-02-01), Wright et al.
patent: 4618933 (1986-10-01), Vitins
patent: 4638495 (1987-01-01), Mizoguchi
patent: 4689709 (1987-08-01), Isahaya
A. A. Girgis et al., "Modelling of Fault-Induced Noise Signals . . . ", IEEE Trans Power Apps & Sys, Sep. 1983 (PAS 102, #9), pp. 2831-2841.
A. A. Girgis et al., "Application of Kalman Filtering in Computer Relaxing", IEEE Trans Power Apps & Sys, Jul. 1981 (PAS 100, #7), pp. 3387-3397.
A. A. Girgis, "Concepts in Kalman Filtering . . . ", Proc 17th Se Symp on System Theory, Apr. 1985, pp. 16-20.
M. S. Sachdev, "Technique for Estimating Transmission Line . . . ", Paper #86 SM, IEEE Pes Summer Meeting, pp. 371-379.
M. M. Elkateb et al., "A New Approach to High Speed Selection", 2nd Int. Conf. Powersystems, Jun. 1980, pp. 171-176.
T. Sakaguchi, "A Statistical Decision Theoretical Approach to Digital Relaying", IEEE Trans Power Apparatus & Systems, Sep./Oct. 1980.
A. A. Girgis, "New Kalman Filtering Based Digital Distance Relay", IEEE TransPower Apps & Sys, Sep. 1982 (PAS 101, #9), pp. 3471-3480.
A. A. Girgis, "Application of Kalman Filtering in Computer Relaxing", PhD Dissertation Iowa State Univ (Abst only), May 1981.
D. T. Magill, "Optimal Adaptive Estmation of Sampled Stochastic Processes", IEEE Trans Automatic Control, Oct. 1965 (AC-10), pp. 434-439.
R. G. Brown, "New Look at the Magill Adaptive Filter . . . ", IEEE Trans Circuits & Sys, Oct. 1983 (CAS30, #10), pp. 765-768.
Adly A. Girgis and Elham B. Makram, "Application of Adaptive Kalman Filtering in Fault Classification Distance Protection, and Fault Location Using Microprocessors", Expected Publication Jun. 1987.
A. A. Girgis and R. Grover Brown, "Application of Adaptive Kalman Filtering in Computer Relaying: Fault Classification Using Voltage Models", IEEE Transactions on Power Apparatus and Systems, vol. PAS-104, No. 5, May 1985, pp. 1168-1177.

Affiliated with

Also associated with

Rating

Adaptive Kalman Filtering in fault classification does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Adaptive Kalman Filtering in fault classification, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Adaptive Kalman Filtering in fault classification will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFUS-PAI-O-898554