Kalman-Filter Based Static Load Modeling of Real Power System Using K-EMS Data

  • Lee, Soo-Hyoung ;
  • Son, Seo-Eun ;
  • Lee, Sung-Moo ;
  • Cho, Jong-Man ;
  • Song, Kyung-Bin ;
  • Park, Jung-Wook
  • Received : 2011.05.09
  • Accepted : 2011.12.27
  • Published : 2012.05.01


So far, the importance for an accurate load model has been constantly raised and its necessity would be further more emphasized. Currently used load model for analysis of power system in Korea was developed 10 years ago, which is aggregated by applying the statistically estimated load compositions to load models based on individual appliances. As modern appliances have diversified and rapidly changed, the existing load model is no longer compatible with current loads in the Korean power system. Therefore, a measurement based load model is more suitable for modern power system analysis because it can accurately include the load characteristics by directly measuring target load. This paper proposes a ZIP model employing a Kalman-filter as the estimation algorithm for the model parameters. The Kamlan-filter based parameter identification offers an advantage of fast parameter determination by removing iterative calculation. To verify the proposed load model, the four-second-interval real data from the Korea Energy Management System (K-EMS) is used.


Kalman-filter;K-EMS;Measurement base;Parameter estimation;ZIP model


  1. C. S. Chen, T. -H. Wu, C. -C. Lee, and Y. -M. TzengJoseph, "The Application of Load Models of Electric Appliances to Distribution System Analysis," IEEE Trans. on Power Systems, vol. 10, No. 3, pp. 1376-1382, August 1995.
  2. W. W. Price, K. A. Wirgau, A, Murdoch, J. V. Mitsche, E. Vaahedi, and M. El-Kady, "Load Modeling for Power Flow and Transient Stability Computer Studies," IEEE Trans. on Power Systems, vol. 3, No. 1, pp. 180-187, February 1988.
  3. J. Kim, K. -B. Shim, and J. -H. Kim, "Load Modeling of Electric Locomotive Using Parameter Identification," Journal of Electrical Engineering & Technology, Vol. 2. No. 2, pp. 145-151, June 2007.
  4. B. K. Choi, H. -D. Chiang, Y. Li, Y. -T. Chen, D. -H. Huang, and M. G. Lauby, "Development of Composite Load Models of Power Systems Using On-Line Measurement Data," Journal of Electrical Engineering & Technology, Vol. 1, No. 2, pp. 161- 169, June 2006.
  5. J. Ma, D. Han, R. -M. He, Z. -Y. Dong, and D. J. Hill, "Reducing Identified Parameters of Measurement- Based Composite Load Model," IEEE Trans. on Power Systems, Vol. 23, No. 1, pp. 76-83, February 2008.
  6. I. A. Hiskens, "Nonlinear Dynamic Model Evaluation from Disturbance Measurements," IEEE Trans. on Power Systems, Vol. 16, No. 4, pp. 702-710, November 2001.
  7. L. Pereira, D. Kosterev, P. Mackin, D. Davies, J. Undrill, and W. Zhu, "An Interim Dynamic Induction Motor Model for Stability Studies in the WSCC," IEEE Trans. on Power Systems, Vol. 17, No. 4, pp. 1108-1115, November 2002.
  8. H. Renmu, M. Jin, and D. J. Hill, "Composite Load Modeling via Measurement Approach," IEEE Trans. on Power Systems, Vol. 21, No. 2, pp. 663-672, May 2006.
  9. B. K. Choi, H. -D. Chiang, Y. Li, H. Li, Y. -T. Chen, D. -H. Huang, and M. G. Lauby, "Measurement- Based Dynamic Load Models: Derivation, Comparison, and Validation," IEEE Trans. on Power Systems, Vol. 21, No. 3, pp. 1276-1283, August 2006.
  10. V. Knyazkin, C. A. Canizares, and L. H. Soder, "On the Parameter Estimation and Modeling of Aggregate Power System Loads," IEEE Trans. on Power Systems, Vol. 19, No. 2, pp. 1023-1031, May 2004.
  11. B. -K. Choi, and H. -D. Chiang, "Multiple Solutions and Plateau Phenomenon in Measurement-Based Load Model Development: Issues and Suggestions," IEEE Trans. on Power Systems, Vol. 24, No. 2, pp. 824-831, May 2009.
  12. H. Bai, P. Zhang, and V. Ajjarapu, "A Novel Parameter Identification Approach via Hybrid Learning for Aggregate Load Modeling," IEEE Trans. on Power Systems, Vol. 24, No. 3, pp. 1145-1154, August 2009.
  13. J. Ma, Z. -Y. Dong, R. -M. He, D. J. Hill, "Measurement-based Load Modeling Using Genetic Algorithms," in proc. of IEEE Congress on Evolutionary Computation, pp. 2909-2916, September 2007.
  14. S. H. Lee and J. W. Park, "Selection of Optimal Location and Size of Multiple Distributed Generations by Using Kalman-Filter Algorithm," IEEE Trans. on Power Systems, Vol. 24, No. 3, pp. 1393-1400, August 2009.
  15. Wiltshire, R.A., Ledwich, G., and O'Shea, P., "A Kalman Filtering Approach to Rapidly Detecting Modal Changes in Power Systems," IEEE Trans. on Power Systems, Vol. 22, No. 4, pp. 1698-1706, Nov. 2007.

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Supported by : Korea Institute of Energy Technology Evaluation and Planning (KETEP)