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Poster abstract: state of operation recognition for heat pumps from smart grid monitoring data

机译：海报摘要：根据智能电网监控数据识别热泵的运行状态

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摘要

Coordinated (de)activation of heat pumps in residential heating systems can support the balance between energy production and consumption in a smart grid. Stopping the heat pump in an inappropriate operation state may result in users' discomfort or damages to the system. In this contribution, a procedure to split domestic hot water provision (DHW) cycles from space heating cycles in the power consumption time series of heat pumps in residential heating systems is presented. The procedure bases on a support vector machine (SVM) classifier applied on statistical properties of the cycles after principal component transformation. The procedure is tested on real-world power consumption time series with 1 s resolution from three different buildings monitored over 1 year. Due to the absence of ground truth validation data, training data for the SVM algorithm are distilled from the measurement data by outlier removal and subsequent K-means classification. The dependence of energy demand for space heating (heating curve) and DHW provision on the ambient temperature are investigated for validation and agrees with Swiss building standards.
机译：住宅供暖系统中热泵的协调（停用）可以支持智能电网中能量生产和能耗之间的平衡。将热泵停止在不适当的运行状态下可能会导致用户不舒服或损坏系统。在此贡献中，提出了一种在住宅供暖系统中将生活热水供应（DHW）循环与空间供暖循环从热泵功耗时间序列中分开的过程。该过程基于支持向量机（SVM）分类器，该分类器应用于主成分变换后的循环统计属性。该程序在1年内对来自3个不同建筑物的1年分辨率的真实世界功耗时间序列进行了测试。由于缺乏地面真实性验证数据，因此通过离群值移除和随后的K均值分类从测量数据中提取了SVM算法的训练数据。对空间供暖（加热曲线）和DHW提供的能量需求与环境温度之间的关系进行了研究，以进行验证并符合瑞士建筑标准。

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