Research on dynamic temporal and spatial distribution characteristics of electrical power system voltage based on random forest algorithm

Jiaqi Fan, Tongjun Shang, Tianyu Yang
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Abstract

The theme of this study is to find a method that can more accurately classify the spatiotemporal distribution characteristics of power system voltage dynamics. As more and more new energy power generation devices are added to the power network, the accuracy of traditional methods for classifying the spatiotemporal distribution characteristics of power system voltage dynamics has gradually decreased. It is significant to reduce the power loss caused by error in identifying voltage dynamic spatiotemporal distribution characteristics. Hence it is necessary to design methods that can more accurately classify power system voltage dynamic spatiotemporal distribution characteristics data. This study proposes a method for studying the spatiotemporal distribution characteristics of power system voltage dynamics based on an improved random forest algorithm. The information entropy calculation method of decision tree in random forest algorithm is improved. According to the experimental results, the classification accuracy of the method for voltage dynamic spatiotemporal distribution characteristics is 99.55%. It can effectively achieve the dynamic spatiotemporal distribution of power system voltage.

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基于随机森林算法的电力系统电压动态时空分布特征研究
本研究的主题是寻找一种能够更准确地对电力系统电压动态时空分布特征进行分类的方法。随着越来越多的新能源发电设备加入电网,传统的电力系统电压动态时空分布特征分类方法的准确性逐渐下降。减少因电压动态时空分布特征识别错误而造成的电能损失意义重大。因此,有必要设计能更准确地对电力系统电压动态时空分布特征数据进行分类的方法。本研究提出了一种基于改进的随机森林算法研究电力系统电压动态时空分布特征的方法。改进了随机森林算法中决策树的信息熵计算方法。实验结果表明,该方法对电压动态时空分布特征的分类准确率为 99.55%。可以有效地实现电力系统电压的动态时空分布。
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