随机系统辨识在电力系统负荷预报中的应用

本文将随机系统状态模型辨识技术用于电力系统负荷预报。首先根据负荷的一系列历史数据建立负荷的状态空间模型,然后用滤波算法进行次日负荷预报,最后用电网实际数据在 PDP-11/23计算机上进行预报计算,得到比较满意的结果。

Power system load forecasting using stochastic system state model identification technique is proposed.First,a power system load model is presented with a relationanalysis method for determining its order and estimating its parameters.Then KalmanFilter theory is used to obtain one-day-ahead load forecasting in various period.Inthis paper,the data used for modelling,forecasting and error analysis are real loadvalues from the north-east power system during the period of 1982-1984,calculationwas performed on PDP-11/23.