多节点超短期负荷预测方法  

Method for Ultra-short Term Multi-node Load Forecasting

作　　者：韩力[1] 韩学山[1] 贠志皓[1] 耿艳[1] 

机构地区：[1]山东大学电气工程学院,山东省济南市250061

出　　处：《电力系统自动化》2007年第21期30-34,共5页Automation of Electric Power Systems

基　　金：国家自然科学基金资助项目(50677036)~~

摘　　要：对多节点有功和无功负荷变化规律的动态自适应超短期预测进行了深入的研究和分析,提出将负荷数据分层分区的处理方法,建立它们之间相互牵制和联系的表达,在由递推最小二乘支持向量机(RLS-SVM)算法实现顶层预测的基础上,建立输电系统多节点负荷动态行为特征的描述模型,构建了自适应动态模型的超短期负荷预测总体构架。以山东电网为例的现场测试效果验证了所述方法的可行性和有效性。In power systems, in order to implement on-line optimal dispatching, preventative control, security assessment and potential transmitting capacity decision-making, it is fundamental and crucial to grasp the load variation regularity of each node. Based on previous researches, this paper makes a further study and analysis on adaptive dynamic ultra-short term forecasting used for multi-node active and reactive load variation regularity. This paper proposes a load data hierarchical and partitioned processing method, establishes a formula to reflect their mutual restraint and relation, creates a model to describe transmission system multi-node load dynamic characteristic on the basis of top layer forecasting using recursive least square support vector machines （RLS-SVM） algorithm, and constructs an ultra-short term load forecasting overall frame of adaptive dynamic model, The application in an actual power system control center of Shandong Province has been verified with satisfactory results,

关 键 词：超短期负荷预测 多节点 支持向量机 卡尔曼滤波 

分 类 号：TM715[电气工程—电力系统及自动化]