基于馈线特征数据挖掘的配电自动化优化规划

配电自动化建设模式的选择是开展配电自动化规划必须解决的关键问题，但目前主要依赖规划人员的主观经验。为此，文章提出了基于馈线特征数据挖掘的配电自动化优化规划方法，通过挖掘馈线拓扑结构、负荷分布、可靠性现状和需求等特征与其最佳配电自动化模式之间的关联规则，建立线路特征-结构模式-配电自动化建设模式的对应关系，突破了由于配电网的庞大规模导致的传统方法的应用局限，为形成兼顾针对性和通用性的配电自动化规划技术原则，实现可靠性和经济性的综合最优奠定理论基础。基于实际配电网的算例分析证明了本文所提方法的正确性和有效性。

Optimal Distribution Automation Planning Method Based on Data Mining on Structure Features of Distribution Feeders

Construction mode selection is a key but subjective experience relayed problem to be solved in distribution automation planning. In this paper, an optimal planning method, based on the data mining on association rules between the features of a feeder and its construction mode of distribution automation, is proposed. In this method, the network topology, load distribution and reliability status of a feeder are considered, and thus the corresponding relationship between the line features and construction mode of distribution automation can be established. Therefore, the limitation of traditional method caused by the large scale of the distribution network can be broken through, and the formation of distribution automation planning technique principle can be established on optimum in both reliability and economy. The analysis result based on the actual distribution network indicates the proposed method to be effective.