Aside from the consumption for domestic cooling and heating, the energy consumption of appliances in a household is a large amount. This energy use by appliances is highly dependent on the activities of the occupants in a building. Occupant behavior in residential buildings possesses the characteristic of randomness, variety, and complexity. More specifically, the profiles of energy consumption and appliance use are highly dependent on the timing of residents’ activities. Thus, it is necessary to model the domestic energy use profile with high temporal resolution. For example, in the context of energy demand response analysis, it is crucial to take occupant behavior into consideration. This article presents a thorough and detailed method for generating an appliance use pattern based on measured power data in real households, taking the television as a case study. The study develops a stochastic model based on appliance use data at one-minute temporal resolution. The proposed model firstly extracts feature parameters to depict the use behavior of the appliance. Then, one stochastic simulation model is established with the input of feature parameters. An evaluation method for this appliance behavior model is also proposed. As a result of one case study simulating appliance consumption at a variety of scales of households, it was concluded that the model can enable applicability to further household energy profile simulation.

中文翻译：

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住宅建筑中的家电使用行为建模和评估：以电视能源使用为例

除了家用制冷和供暖的消耗外，家庭中家用电器的能源消耗也很大。电器的能源消耗高度依赖于建筑物中居住者的活动。居住建筑中的居住者行为具有随机性，多样性和复杂性。更具体地说，能源消耗和设备使用情况在很大程度上取决于居民活动的时间安排。因此，有必要以高的时间分辨率对家庭能源使用状况进行建模。例如，在能源需求响应分析的背景下，至关重要的是要考虑乘员的行为。本文介绍了一种基于真实家庭中测得的功率数据生成电器使用模式的彻底而详细的方法，以电视为例。该研究基于一分钟时间分辨率的设备使用数据开发了一个随机模型。所提出的模型首先提取特征参数以描述设备的使用行为。然后，利用特征参数的输入建立一个随机的仿真模型。还提出了针对该设备行为模型的评估方法。作为一个案例研究的结果，该案例模拟了各种规模的家庭的电器消耗，因此得出的结论是，该模型可以应用于进一步的家庭能源分布模拟。在输入特征参数的基础上建立了一种随机仿真模型。还提出了针对该设备行为模型的评估方法。作为一个案例研究的结果，该案例模拟了各种规模的家庭的电器消耗，因此得出的结论是，该模型可以应用于进一步的家庭能源分布模拟。通过输入特征参数，建立了一种随机仿真模型。还提出了针对该设备行为模型的评估方法。作为一个案例研究的结果，该案例模拟了各种规模的家庭的电器消耗，因此得出的结论是，该模型可以应用于进一步的家庭能源分布模拟。