摘要
公众气象预报信息存在偏差 ,导致电力负荷短期预测中出现相应不可预计的误差 .基于随机事件的分布理论 ,说明卡尔曼滤波器的叠代算法 .并运用卡尔曼滤波技术开发气象信息估计器 ,为电力负荷预测提供具备统计方差最小意义的待测日气象数据 。
Noises existing in the public weather reports always results in unpredictable errors in short_term load forecasting. A weather estimator based on Kalman filter is developed to achieve the minimum variance. A deduction procedure for Kalman filter is also presented from the perspective of statistics application. The weather information estimator helps improve the accuracy of load forecasting.
出处
《华南理工大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2002年第6期36-39,共4页
Journal of South China University of Technology(Natural Science Edition)
关键词
电力系统
短期负荷预测
气象估计
卡尔曼滤波
power system
load short_term forecasting
weather estimation
Kalman filter
