| Title |
A New Algorithm for Recursive Short-term Load Forecasting |
| Authors |
Young-Moon Park(Young-Moon Park) ; Sung-Chul Oh(Sung-Chul Oh) |
| Abstract |
This paper deals with short-term load forecasting. The load model is represented by the state variable form to exploit the Kalman filter technique. The load model is derived from Taylor series expansion and remainder term is considered as noise term. In order to solve recursive filter form, among various algorithm of solving Kalman filter, this paper uses exponential data weighting technique. This paper also deals with the asymptotic stability of filter. Case studies are carried out for the hourly power demand forecasting of the Korea electrical system. |