裘 星,尹仕红,张之涵,潘深琛,江敏丰,杨建明,郑建勇.基于DTW的多状态负荷的非侵入式负荷分解[J].电力需求侧管理,2022,24(6):84-90 |
基于DTW的多状态负荷的非侵入式负荷分解 |
Non-intrusive load decomposition of multi-state load based on DTW |
投稿时间:2022-08-07 修订日期:2022-09-03 |
DOI:10. 3969 / j. issn. 1009-1831. 2022. 06. 014 |
中文关键词: 多状态负荷 非侵入式负荷监测 动态时间规整 稳态特征 滑动时间窗 |
英文关键词: multi-state load NILM DTW steady state characteristics sliding time window |
基金项目:深圳供电局有限公司科技项目(090000KK52190185) |
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中文摘要: |
非侵入式负荷监测(NILM)是大数据和人工智能的重要应用领域,能够显著提升电网的智能化水平和节能效果。长期以来在NILM中采用稳态特征进行负荷分解时,优点是可识别功率近似的负荷,但是不能处理多状态负荷。为此,采用滑动时间窗作为事件探测算法,提出一种基于动态时间规整(DTW)的多状态特征的NILM模型。该模型首先对多状态负荷进行特征提取,并建立多状态特征的稳态波形模板库;然后利用滑动时间窗算法提取待分解负荷的稳态波形特征,将提取的稳态波形运用DTW算法与稳态波形模板库中的负荷特征计算最小距离进行辨识。该方法能够显著提升稳态条件下多状态负荷的辨识效果。最后采用公共数据集REDD进行测试验证,证明了所提方法的有效性。 |
英文摘要: |
Nonintrusive load monitoring(NILM)is an important application area of big data and artificial intelligence, which can significantly improve the intelligence level and energy-saving effect of the power grid. For a long time in NILM, the advantage when using steady-state characteristics for load decomposition is that it can identify loads with similar power, but it cannot handle multi-state loads. To this end, a sliding time window is used as an event detection algorithm, and a NILM model based on dynamic time warping(DTW)with multi-state features is proposed. Firstly,the model extracts the characteristics of the multi-state load, and establishes a steady-state waveform template library of the multistate characteristics. Then, it uses the sliding time window algorithm to extract the steady- state waveform characteristics of the load to be decomposed, and applies the DTW algorithm to the steady-state waveforms. The load characteristics in the state waveform template library calculate the minimum distance for identification. The proposed load decomposition model can significantly improve the decomposition ability of multi-state loads under steadystate characteristics. Lastly, the test based on the REDD dataset verifies the effectiveness of the method. |
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