考虑数据不均衡的居民用户负荷曲线分类方法
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

TM73

基金项目:

河北省重点研发计划资助项目(20312102D)


Residential user load curve classification method considering data imbalance
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    由于用户用电行为的多样性和随机性,负荷数据存在分布不均衡的问题,传统负荷曲线分类方法在处理不均衡数据时性能较差。为此,提出一种改进K-means与长短期记忆(LSTM)神经网络-卷积神经网络(CNN)分类模型结合的负荷曲线分类方法。首先,为提升K-means算法对不均衡数据的聚类效果,基于密度峰值聚类(DPC)算法思想,提出一种相对k近邻密度峰值(RKDP)初始聚类中心选取方法,将其作为K-means算法的初始中心进行聚类;然后,为提高RKDP-K-means处理高维负荷数据的性能,采用LSTM自编码器进行特征降维后再聚类获得精准类别标签;最后,基于LSTM神经网络和CNN分别提取负荷特征构建负荷曲线分类模型,实现对大规模负荷曲线的分类。算例选取了爱尔兰智能电表数据集和伦敦负荷数据集进行实验,验证了所提算法在大规模负荷曲线分类时的有效性和实用性。

    Abstract:

    Due to the diversity and randomness of users' electricity consumption behaviors,the imbalance of load data classes is increasingly obvious. Traditional load curve classification technologies have become ineffective to deal with the im-balanced class problem of data. Therefore,an algorithm combing improved K-means with long short term memory (LSTM) neural network and convolutional neural network (CNN) classification model is proposed. Firstly,to improve the classifica-tion accuracy of the K-means on imbalanced data,a method of relative k-nearest neighbor density peaks (RKDP) based on the density peak clustering algorithm (DPC) is proposed to select the initial clustering centre of K-means. Secondly,in order to improve the performance of RKDP-K-means in processing high-dimensional load data,an au-to-encoder based on LSTM is used to extract load characteristics from high dimensional data,and com-bined with RKDP-K-means to obtain accurate load profiles labels. Finally,based on LSTM neural network and CNN,load characteristics were extracted to construct load curve classification model to realize the classification of large-scale load curve. Different algorithms are employed to classify Ireland smart meter data set and London load data set. The results show the proposed algorithm is more effective and practicable in large-scale load curve classification.

    参考文献
    相似文献
    引证文献
引用本文

张慧波,王守相,赵倩宇,任杰,王海.考虑数据不均衡的居民用户负荷曲线分类方法[J].电力工程技术,2022,41(3):186-193

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2021-12-19
  • 最后修改日期:2022-02-25
  • 录用日期:2021-08-20
  • 在线发布日期: 2022-05-24
  • 出版日期: 2022-05-28