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Online end-use energy disaggregation via jump linear models

机译:在线最终使用能源通过跳跃线性模型进行分类

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This paper presents two iterative algorithms for non-intrusive appliance load monitoring, which aims to decompose the aggregate power consumption only measured at the household level into the contributions of the individual electric appliances. The approaches are based on modelling the total power consumption as a combination of jump linear sub-models, each of them describing the behaviour of the individual appliance. Dynamic-programming and multi-model Kalman filtering techniques are used to reconstruct the power consumptions at the single-appliance level from the aggregate power in an iterative way.
机译:本文介绍了非侵入式设备负荷监测的两个迭代算法,旨在将其分解在家庭水平仅测量到各个电器的贡献中的总功耗。该方法基于将总功耗建模为跳跃线性子模型的组合,它们中的每一个描述各个设备的行为。动态编程和多模型卡尔曼滤波技术用于以迭代方式从聚合功率重建单个设备电平的功耗。

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