摘要
互感器状态因受多种因素影响,导致评估指标权重重要程度的计算难度较大,因此,本文提出基于随机森林算法的电力电子互感器状态评估模型。通过提取电力电子互感器状态评估指标,利用随机森林算法精准计算评估指标的权重重要程度。综合指标的权重值,构建电力电子互感器状态评估模型。实验结果表明,利用随机森林算法设计的评估模型评估互感器的4种运行状态,其评估正确率均高于传统评估模型,达到了99%以上。由此可见,利用基于随机森林算法的互感器状态评估模型在评估互感器运行状态领域中具有很高的评估正确率,完全可以满足实际应用需求。
A state evaluation model for power electronic transformers based on random forest algorithm is proposed in view of the difficulty in calculating the weight of evaluation index,given that the state of a transformer is affected by various factors.The model accurately calculates the weight importance by extracting the state evaluation index of power electronic transformers via the random forest algorithm.Based on the weight value of the comprehensive index,the power electronic transformer state evaluation model is then constructed.The experimental results demonstrate that the proposed model has a higher accuracy rate than that of the traditional model,exceeding 99%,thereby proving that the random forest algorithm is capable of providing a high-accuracy evaluation of transformer operation state,which meets practical application needs.
作者
阮志峰
RUAN Zhifeng(Red Phase Co.,Ltd.,Xiamen,Fujian 361100,China)
出处
《自动化应用》
2023年第7期159-161,165,共4页
Automation Application
关键词
随机森林算法
电力电子互感器
状态评估模型
评估正确率
random forest algorithm
power electronic transformer
state assessment model
assessment accuracy
