自适应卡尔曼滤波在电力系统短期负荷预测中的应用APPLICATION OF ADAPTIVE KALMAN FILTER IN POWER SYSTEM SHORT-TERM LOAD FORECASTING
马静波,杨洪耕
摘要(Abstract)：
将卡尔曼滤波原理运用于电力系统负荷预测通常是针对线性定常系统,并在定常噪声协方差的前提下进行,模型的灵敏度差和预报精度不高。作者考虑了电力系统负荷自身的变化特点,根据不同日期同一时刻的负荷历史数据建立了含有时变系数的负荷系统模型、观测模型和系统参数模型,采用两段自适应卡尔曼滤波方法,同时考虑噪声协方差对预测精度的影响,运用时变噪声统计估值器对噪声协方差进行自适应估计,用预测方程预测次日的负荷。结合实际电网数据进行的预测计算取得了较好的结果。
关键词(KeyWords)： 负荷预测;卡尔曼滤波;时变噪声统计估值器;自适应滤波;电力系统
基金项目(Foundation):
作者(Author): 马静波,杨洪耕
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