基于配电大数据的配电网故障停电影响因素灵敏度分析

Sensitivity Analysis of Influencing Factors of Power Failure in Distribution Network Based on Big Data

在新一轮配电网投资改造的背景下,如何优化投资对配电网的影响,最大程度地提升配电网供电可靠性尤为重要。文章以现有配电业务历史数据为基础,依据历史运行数据,考虑网架结构、运维管理水平、装备水平等影响配电网故障停电等主要因素,构造了输入特征变量与故障停电可靠性指标值间的非线性映射关系,建立基于BP神经网络的配电网故障停电可靠性指标预测模型。依据所提模型,对各影响因素进行灵敏度分析,获取了某市配电网薄弱环节,为其可靠性提升方向提供参考。

Under the background of the new round of distribution network investment transformation,how to optimize the influence of investment on distribution network and maximize the reliability of distribution network power supply is particularly important.Considering the main factors affecting the fault outage of distribution network,such as grid structure,operation and maintenance management level and equipment level,the non-linear mapping relationship between input characteristic variables and fault outage reliability index value is constructed,and the prediction model of distribution network fault outage reliability index based on BP neural network is established.According to the proposed model,sensitivity analysis of each influencing factor is carried out,and the weak links of a city's distribution network are obtained,which can provide a reference for the direction of reliability improvement.