| 电力系统超短期负荷预报的一种有效方法 |
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| 引用本文： | 王正欧,张建平.电力系统超短期负荷预报的一种有效方法[J].天津大学学报(自然科学与工程技术版),1992(2):125-130. |
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| 作者姓名： | 王正欧 张建平 |
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| 作者单位： | 天津大学
(王正欧)，北京化工学院(张建平) |
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| 摘 要： | 针对电力系统超短期负荷预报的特点提出了自校正移动窗卡尔曼滤波—最小二乘算法(SMWKL)。首先用带移动窗的卡尔曼滤波算法减少负荷数据的噪声,然后通过自校正移动窗最小二乘算法得到较精确的参数估计,再进行一步预测就可得到较好的结果。实例表明了这一点。
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| 关 键 词： | 电力系统 电力负荷预报 SMWKL |
AN EFFECTIVE METHOD FOR EXTRA SHORT TERM LOAD FORECASTING OF ELECTRICITY SYSTEM |
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| Wang Zhengou.AN EFFECTIVE METHOD FOR EXTRA SHORT TERM LOAD FORECASTING OF ELECTRICITY SYSTEM[J].Journal of Tianjin University(Science and Technology),1992(2):125-130. |
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| Authors: | Wang Zhengou |
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| Institution: | Wang Zhengou (Tianjin University) Zhang Jianping (Beijing Chemical Engineering College) |
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| Abstract: | This paper describes an algorithm of self-adjusting moving window Kalman filter-least square (SMWKL). It is based on the characteristics of the forecast of extra short term load of electricity system. First, the noises in the data of load are reduced with Kalman filter by using moving window. Then the better precise parameter estimation of the model is obtained through the least square method with self-adjusting moving window. Finally, the better effect of the forecast can be obtained through one-step prediction. This is illustrated by a real example. |
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| Keywords: | forecasting of electricity load parameter estimation Kalman filter moving window |
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