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为实现非侵入式电力负荷监测与识别过程中,负荷投切时间的精确辨识以及负荷类型的准确识别,有效地实现电网动态分析、诊断和优化,提高电力利用率,本文提出一种家用非侵入式电力负荷监测与识别算法。首先,提出一种基于改进滑动窗的负荷投切检测算法,准确判断负荷投切时间和稳态时间,实现稳态负荷特征的高精度提取,提高投切检测辨识灵敏度和抗干扰能力。然后,利用Adaboost算法实现家用电力负荷识别。实验结果表明,本文提出的负荷投切事件检测算法和负荷识别算法准确率较高,可以满足实际应用需求。
Abstract：Non-intrusive load monitoring, known as one of the key technologies for smart grid, has been studied extensively. The identification of load switching time and load type are the two main research directions. In such a way, the power efficiency can be improved according to dynamic analysis, diagnosis and optimization of the power grid. In this paper, a new method for non-instrusive load monitoring and identification of household electric appliances is proposed. First, the load switching event detection algorithm is constructed based on an improved sliding window. Hence, the detection sensitivity and anti-interference ability can be improved because of the high precision extraction of steady state features. Then, the load identification is carried out through Adaboost algorithm. Finally, the high precision load recognition performance of the proposed method is verified by experiments.
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基本信息:
DOI：10.16441/j.cnki.hdxb.20180182
中图分类号:TM76
引用信息:
[1]殷波,张帅.家用非侵入式电力负荷监测与识别算法研究[J],2020,50(06):149-156.DOI:10.16441/j.cnki.hdxb.20180182.
基金信息:
国际科技合作计划项目(2015DFR10490)资助~~
2018-04-26
2018
2020-06-17
2020
2018-12-13
3