摘要
钢铁企业配电网中大量的非线性和冲击性负荷严重影响企业电网的电能质量及相关设备的使用寿命.充分考虑了冲击性负荷的特点,在带时变噪声统计估值器的Sage-Husa自适应滤波算的基础上,提出了一种改进Sage-Husa自适应滤波超短期预测算法.改进后的算法可以正确估计系统的输入噪声方差Q和测量噪声方差R,提高了预测准确度,同时继承了原算法的优点,计算速度快,存储量小,适合于在线应用.某钢铁企业轧钢车间部分供电母线的实际预测结果表明:该算法预测精度较高,计算速度快,可用于指导无功动态补偿,提高电压合格率和电气节能效果.
The impact loads with no definite period in iron and steel enterprise seriously affect the power quality in the company power supply system and the working life of relevant equipment. Considering the special characteristics of impact loads and based on Sage-Husa adaptive filtering algorithm with estimator of time-variant variation noise, an improved Sage- Husa adaptive filtering algorithm is proposed in this paper. This new algorithm can estimate the system input noise variance and output noise variance correctly, and effectively improve forecasting accuracy. Meanwhile, the improved algorithm inherits the advantages of the original algorithm, with rapid computing speed and high storage capacity small. The new algorithm is perfectly suitable for online applications. The reactive power forecasting results of some substation buses in an iron and steel enterprise show that the high accuracy and rapid computing rate of the algorithm.
出处
《系统科学与数学》
CSCD
北大核心
2012年第4期429-437,共9页
Journal of Systems Science and Mathematical Sciences
基金
国家高技术研究计划(863)(2009AA052213)资助课题
