一种基于改进人工神经网络的配电系统重构方法

K. S. Kumar, K. Rajalakshmi, S. Karthikeyan
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引用次数: 6

摘要

提出了一种确定径向配电系统重构中最佳开关选择的新方法。馈线重新配置是指通过打开和关闭分段和连接开关来改变配电馈线结构的技术。重新配置包括选择要打开的一组分段开关和要关闭的一组tie开关,以使RDS具有所需的性能。在系统优化配置的几种准则中,损耗减少准则的应用非常广泛。本课题提出了一种利用馈线重构作为规划和实时控制工具的新方法,以重构主馈线以实现损耗最小化。给出了该方法的数学表达式;通过实例说明了求解过程。本文提出了RDS最优重构的神经网络方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A modified artificial neural network based Distribution System reconfiguration for loss minimization
In this paper a new method for identifying best switching option in reconfiguration of Radial Distribution Systems (RDS) is presented. Feeder reconfiguration is defined as the technique to alter the structures in the distribution feeder by opening and closing the sectionalizing and tie switches. The reconfiguration includes selecting of set of sectional switches to be opened and tie switch to be closed such that the RDS has desired performance. Among several criteria considered in optimal system configuration, loss reduction criterion is very widely used. In this project a novel method is presented which utilizes feeder reconfiguration as a planning and real time control tool in order to restructure the primary feeders for the loss minimization. The mathematical formulation of the proposed method is given; the solution procedure is illustrated with an example. Here neural network approach for Optimal Reconfiguration of RDS is proposed.
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