基于数据驱动技术的配电网拓扑结构及线路参数识别方法

Distribution network topology and line parameter identification method based on data-driven technology

针对传统配电网线路参数识别过程中,未考虑线路中的附加损耗对识别精度的影响,导致参数识别精度较低的问题,提出基于数据驱动技术的配电网拓扑结构及线路参数识别方法。通过配电网等效拓扑结构提取数据驱动参数,构建配电网伴随电路模型并提取线路参数融合结果。利用诺顿定理优化识别配电网的线路参数融合结果,构建配电网的线路参数识别的规划模型,实现数据驱动下的配电网拓扑结构及线路参数识别。实验结果表明,采用该方法进行配电网拓扑结构及线路参数识别的精度较高,有效提高了配电网的拓扑稳定性。

Aiming at the problem that the line parameter identification process of traditional distribution network does not consider the influence of the additional loss in the line on the identification accuracy, which leads to the problem of low parameter identification accuracy, this paper proposes a data-driven technology-based distribution network topology and line parameter identification method.The data-driven parameters are extracted through the equivalent topology of the distribution network, the accompanying circuit model of the distribution network is constructed, and the line parameter fusion result is extracted.Using Norton’s theorem to optimize and identify the line parameter fusion results of the distribution network, construct the planning model of the line parameter identification of the distribution network, and realize the data-driven distribution network topology and line parameter identification.The experimental results show that the method is used to identify the topological structure and line parameters of the distribution network with high accuracy, which effectively improves the topology stability of the distribution network.