Phasor state estimation from PMU measurements with bad data

2011 4th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2011

Volumn , Issue , 2011, Pages 121-124

  Duan, Dongliang ^a   Yang, Liuqing ^a   Scharf, Louis L ^b  

^a Department of Chemical and Biological Engineering and School of Biomedical Engineering   (United States)

^b Department of Ecosystem Science and Sustainability   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BAD DATA; COMMUNICATION ERRORS; DATA REDUNDANCY; EQUIPMENT FAILURES; PHASOR MEASUREMENT UNIT; POWER GRIDS;

ALGORITHMS; COMMUNICATION; SENSORS;

STATE ESTIMATION;

EID: 84863139773     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CAMSAP.2011.6135902     Document Type: Conference Paper

References (14)

1. A. G. Phadke, "Synchronized phasor measurements in power systems," IEEE Computer Applications in Power, vol. 6, no. 2, pp. 10-15, April 1993. (Pubitemid 23638773)
2. A. Gomez-Exposito, A. Abur, A. de la Villa Jaen, and C. Gomez-Quiles, "A multilevel state estimation paradigm for smart grids," Proceeding of the IEEE, vol. 99, no. 6, pp. 952-976, June 2011.
3. F. F. Wu, "Power system state estimation: A survey," International Journal of Electrical Power & Energy Systems, vol. 12, no. 2, pp. 80-87, April 1990.
4. A. G. Phadke, J. S. Thorp, R. F. Nuqui, and M. Zhou, "Recent developments in state estimation with phasor measurements," in Proc. of Power Systems Conference and Exposition, Seattle, WA, March. 15-18, 2009.
5. A. G. Phadke and J. S. Thorp, Synchronized Phasor Measurements and Their Applications. Springer, 2010.
6. Rice University, Compressive Sensing Resources. [Online]. Available: http://dsp.rice.edu/cs
7. A. Abur and A. Gomez-Exposito, Power System State Estimation: Theory and Implementaion. CRC Press, 2004.
8. R. T. Behrens and L. L. Scharf, "Signal processing applications of oblique projection operators," IEEE Trans. on Signal Processing, vol. 42, no. 6, pp. 1413-1424, June 1994.
9. D. A. Harville, Matrix Algebra From a Statistican's Perspective. Springer, 2008.
10. L. L. Scharf, P. Mathys, and R. T. Behrens, "Rank reduction for decoding linear block-codes over the complex field," in Proceedings of the 21st Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, November 1987.
11. R. Baraniuk, "Compressive sensing," IEEE Signal Processing Magazine, vol. 24, no. 4, pp. 118-121, July 2007.
12. University of Washington, Power System Test Case Archive. [Online]. Available: http://www.ee.washington.edu/research/pstca/
13. Stanford University, SparseLab: Seeking Sparse Solutions to Linear Systems of Equations. [Online]. Available: http://sparselab.stanford.edu/
14. H. Mohimani, M. Babaie-Zadeh, and C. Jutten, "A fast approach for overcomplete sparse decomposition based on smoothed L-0 norm," IEEE Trans. on Signal Processing, vol. 57, no. 1, pp. 289-301, January 2009.