配电网自适应负荷估计方法

为增强配电网运行的安全性和经济性,提出一种可系统解决配电网在线节点负荷估计的新方法。该方法包含粗略负荷估计、负荷预测和抗差负荷估计3个阶段。粗略负荷估计阶段可使用3种方法来提供粗略的节点负荷估计值;负荷预测阶段使用基于事例模糊神经网络的方法提供节点负荷预测值;抗差负荷估计同时实现了结构空间和量测空间的抗差估计。3个阶段密切配合,形成闭环信息流。该方法可实现长期自适应在线运行,能够为配电系统的监视、控制和管理提供可靠一致的负荷数据集。

Self-adaptive Load Estimation Method for Distribution Networks

In order to enhance the secure and economical operation of distribution network,a novel method is proposed for solving online nodal load estimation of distribution networks systematically.The proposed method consists of three phases that are crude load estimation,load forecasting and robust load estimation.Three load allocation methods are offered in curde load estimation phase which provide crude load values.A case-based fuzzy-neural network is utilized in load forecasting phase for supplying nodal load forecasting values.Robust load estimation is robustified synthetically in both structure space and measurement space.The three phases cooperate closely and form a closed-cycle information flow.The proposed method can run online and self-adaptively,and it can provide reliable and consistent load data set for monitoring,control and management of distribution systems.