基于云计算的多因素电力负荷坏数据自动检测方法

电力负荷坏数据对电网具有严重的破坏性,为了提高对电力负荷坏数据的检测能力,提出基于云计算的多因素电力负荷坏数据自动检测方法。采用云计算模型进行多因素电力负荷坏数据的分布式重组和集成运算,构建多因素电力负荷坏数据的云网格分布模型,在云网格空间中采用主成分特征分析方法进行多因素电力负荷坏数据特征检测,在双极型直流配电网中实现对多因素电力负荷坏数据的共模分量计算,提取电力负荷坏数据的能量谱特征量,根据负荷用电特性、潮流分布及其容量等参数,实现对多因素电力负荷坏数据的特征检测。仿真结果表明,采用该方法进行多因素电力负荷坏数据检测的自动性较好,检测准确率较高。

Automatic detection method of multi-factor power load bad data based on cloud computing

The bad data of power load is seriously destructive to the power grid.In order to improve the detection ability of bad data of power load,an automatic detection method of multi-factor power load bad data based on cloud computing is proposed.The cloud computing model is used for the distributed reorganization and integration of multi-factor power load bad data,and the cloud grid distribution model of multi-factor power load bad data is constructed.The principal component feature analysis method is used to detect the characteristics of multi-factor power load bad data in cloud grid space,and the common mode component calculation of multi-factor power load bad data is realized in bipolar DC distribution network.The energy spectrum characteristics of power load bad data are extracted,and the feature detection of multi-factor power load bad data is realized according to the load power consumption characteristics,power flow distribution and capacity and other parameters.The simulation results show that this method is more automatic and accurate in detecting the bad data of multi-factor power load.