Journal of Electrical Engineering and Technology

The Korean Institute of Electrical Engineers (대한전기학회)
권호 표지
DOI QR코드

DOI QR Code

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

  • Lee, Soo-Hyoung (School of Electrical and Electronic Eng., Yonsei University) ;
  • Son, Seo-Eun (School of Electrical and Electronic Eng., Yonsei University) ;
  • Lee, Sung-Moo (System Operation & Control Department, Korea Power Exchange) ;
  • Cho, Jong-Man (System Operation & Control Department, Korea Power Exchange) ;
  • Song, Kyung-Bin (Department of Electrical Engineering, Soongsil University) ;
  • Park, Jung-Wook (School of Electrical and Electronic Engineering, Yonsei University)
  • Received : 2011.05.09
  • Accepted : 2011.12.27
  • Published : 2012.05.01
Download PDF
⟨ Previous Next ⟩

Abstract

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.

Keywords

References

  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. https://doi.org/10.1109/59.466515
  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. https://doi.org/10.1109/59.43196
  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. https://doi.org/10.5370/JEET.2007.2.2.145
  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. https://doi.org/10.5370/JEET.2006.1.2.161
  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. https://doi.org/10.1109/TPWRS.2007.913206
  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. https://doi.org/10.1109/59.962416
  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. https://doi.org/10.1109/TPWRS.2002.804960
  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. https://doi.org/10.1109/TPWRS.2006.873130
  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. https://doi.org/10.1109/TPWRS.2006.876700
  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. https://doi.org/10.1109/TPWRS.2003.821634
  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. https://doi.org/10.1109/TPWRS.2009.2016462
  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. https://doi.org/10.1109/TPWRS.2009.2022984
  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. https://doi.org/10.1109/TPWRS.2009.2016540
  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. https://doi.org/10.1109/TPWRS.2007.907529

Cited by

  1. Evaluation of the Effects of Nationwide Conservation Voltage Reduction on Peak-Load Shaving Using SOMAS Data vol.6, pp.12, 2013, https://doi.org/10.3390/en6126322
  2. Centralized Adaptive Under Frequency Load Shedding Schemes for Smart Grid Using Synchronous Phase Measurement Unit vol.8, pp.3, 2013, https://doi.org/10.5370/JEET.2013.8.3.446
  3. Improvement of Composite Load Modeling Based on Parameter Sensitivity and Dependency Analyses vol.29, pp.1, 2014, https://doi.org/10.1109/TPWRS.2013.2281455
  4. A Target Tracking Based on Bearing and Range Measurement With Unknown Noise Statistics vol.8, pp.6, 2013, https://doi.org/10.5370/JEET.2013.8.6.1520
  5. EMS-Data-Based Load Modeling to Evaluate the Effect of Conservation Voltage Reduction at a National Level vol.6, pp.12, 2013, https://doi.org/10.3390/en6083692
  6. Analysis on Special Protection Scheme of Korea Electric Power System by Fully Utilizing STATCOM in a Generation Side vol.32, pp.3, 2017, https://doi.org/10.1109/TPWRS.2016.2597307
  7. Development of the automatic load modelling system using PQM data on industry site vol.7, pp.1, 2017, https://doi.org/10.1080/22348972.2016.1158350
  8. Bayesian Estimation on Load Model Coefficients of ZIP and Induction Motor Model vol.12, pp.3, 2019, https://doi.org/10.3390/en12030547