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Smart Grid 2021
基于周期性多态洗衣机运行的混合事件检测算法
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Abstract:
事件检测是非侵入式负荷监测与识别的重要环节。针对洗衣机运行时存在多事件无法识别的问题，本文提出了基于周期性多态洗衣机运行的混合事件检测算法，先采用CUSUM算法捕捉启停波形，引入shapeDTW算法对其中的周期性波形进行匹配识别，并将其从总负荷数据中剥离，避免周期性波形对其他电器事件检测的影响，该方法能具有很高的识别未知周期性波形的自适应能力。在多态洗衣机参与运行的情况下，投切各种特性负荷进行仿真分析、方法对比，该算法保证了特征提取的准确性，具有很高的检测精度，为事件检测算法的优化提供了借鉴意义。
Event detection is an important part of non-intrusive load monitoring and identification. Aiming at the problem that multiple events cannot be recognized during the operation of washing machine, this paper proposes a mixed event detection algorithm based on the operation of periodic polymorphic washing machine. Firstly, the start and stop waveform is captured by the CUSUM algorithm, and the shapeDTW algorithm is introduced to match and identify the periodic waveform, and it is stripped from the total load data. The method can avoid the influence of periodic waveform on the detection of other electrical events and has high adaptive ability to identify unknown periodic waveform. In the case of multi-state washing machine participating in the operation, the simulation analysis and method comparison of various characteristic loads are carried out. The algorithm ensures the accuracy of feature extraction and has high detection accuracy, which provides a reference for the optimization of event detection algorithm.
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