A high-resolution stochastic model of domestic activity patterns and electricity demand
A high-resolution stochastic model of domestic activity patterns and electricity demand
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DOI：
10.1016/j.apenergy.2009.11.006
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发表时间：
2010-06
期刊：
影响因子：
11.2
通讯作者：
J. Widén;E. Wäckelgård
中科院分区：
文献类型：
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作者：
J. Widén;E. Wäckelgård
关于居住者行为、存在和能源使用的真实时间分辨数据是各种类型模拟的重要输入，包括小规模能源系统的性能和建筑物的室内气候、照明的使用和能源需求。本文提出了一种高分辨率数据序列随机生成的建模框架。该模型生成单个家庭成员的综合活动序列，包括居住状态，以及基于这些模式的家庭电力需求。活动生成模型基于调整到大量经验时间使用数据集的非齐次马尔可夫链，创建了活动随时间的真实分布，精度可达1分钟。根据测量结果进行的详细验证表明，模拟的单个家庭的电力需求数据以及任意数量家庭的总需求在最终用途构成、年度和日变化、家庭之间的多样性、短时间尺度波动和负荷重合方面是高度现实的。模型开发的一个重要目标是在复杂性和输出质量之间保持良好的平衡。虽然该模型的输出质量较高，但与国内现有的负荷模型相比，该模型的结构并不复杂。
Realistic time-resolved data on occupant behaviour, presence and energy use are important inputs to various types of simulations, including performance of small-scale energy systems and buildings’ indoor climate, use of lighting and energy demand. This paper presents a modelling framework for stochastic generation of high-resolution series of such data. The model generates both synthetic activity sequences of individual household members, including occupancy states, and domestic electricity demand based on these patterns. The activity-generating model, based on non-homogeneous Markov chains that are tuned to an extensive empirical time-use data set, creates a realistic spread of activities over time, down to a 1-min resolution. A detailed validation against measurements shows that modelled power demand data for individual households as well as aggregate demand for an arbitrary number of households are highly realistic in terms of end-use composition, annual and diurnal variations, diversity between households, short time-scale fluctuations and load coincidence. An important aim with the model development has been to maintain a sound balance between complexity and output quality. Although the model yields a high-quality output, the proposed model structure is uncomplicated in comparison to other available domestic load models.