机构地区: 华南理工大学电力学院
出 处: 《华南理工大学学报(自然科学版)》 2002年第6期36-39,共4页
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.
领 域: [电气工程]