Journal of Electrical Engineering and Technology

The Korean Institute of Electrical Engineers (대한전기학회)
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Very Short-term Electric Load Forecasting for Real-time Power System Operation

  • Jung, Hyun-Woo (Economy & Management Research Institute, KEPCO) ;
  • Song, Kyung-Bin (Department of Electrical Engineering, Soongsil University) ;
  • Park, Jeong-Do (Division of Energy & Electrical Engineering, Uiduk University) ;
  • Park, Rae-Jun (Department of Electrical Engineering, Soongsil University)
  • Received : 2017.04.24
  • Accepted : 2018.01.01
  • Published : 2018.07.01
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Abstract

Very short-term electric load forecasting is essential for real-time power system operation. In this paper, a very short-term electric load forecasting technique applying the Kalman filter algorithm is proposed. In order to apply the Kalman filter algorithm to electric load forecasting, an electrical load forecasting algorithm is defined as an observation model and a state space model in a time domain. In addition, in order to precisely reflect the noise characteristics of the Kalman filter algorithm, the optimal error covariance matrixes Q and R are selected from several experiments. The proposed algorithm is expected to contribute to stable real-time power system operation by providing a precise electric load forecasting result in the next six hours.

Keywords

References

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