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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

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

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

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Acknowledgement

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