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A Novel Method for Online Nodal Load Estimation of Middle Voltage Distribution Networks

机译:一种新的中压分配网络在线节点负荷估计的新方法

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摘要

A novel method is proposed for solving online nodal load estimation of middle voltage distribution networks systematically. Firstly the solution strategies are introduced, and then the algorithm is presented. 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 crude load estimation phase which can 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 has been robustified synthetically in both structure space and measurement space, which can effectively withstand the influence of gross errors and many small errors. The three phases of load estimation cooperate closely and form a closed-cycle information flow. The proposed method can run online and can provide reliable and consistent load data set for control and management of distribution networks.
机译:提出了一种用于系统地解决中压配电网的在线节点载荷估计的新方法。首先,引入了解决方案策略,然后提出了算法。所提出的方法包括三个阶段,该阶段是粗载估计,负载预测和鲁棒负载估计。在原油负载估计阶段提供三种负载分配方法,其可以提供粗载值。基于案例的模糊神经网络用于负载预测阶段,用于提供节点负荷预测值。在结构空间和测量空间中,鲁棒负载估计已经在合成中易于强调,这可以有效地承受粗略误差和许多小错误的影响。负载估计的三个阶段紧密协作并形成闭环信息流。所提出的方法可以在线运行,可以提供可靠和一致的负载数据集,用于控制和管理分发网络。

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