A highly resolved modeling technique to simulate residential power demand
A highly resolved modeling technique to simulate residential power demand
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DOI：
10.1016/j.apenergy.2013.02.057
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发表时间：
2013-07
期刊：
影响因子：
11.2
通讯作者：
M. Muratori;M. C. Roberts;R. Sioshansi;V. Marano;G. Rizzoni
中科院分区：
文献类型：
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作者：
M. Muratori;M. C. Roberts;R. Sioshansi;V. Marano;G. Rizzoni
本文提出了一个模型来模拟由多个人组成的单个家庭的电力需求。总消耗量分为四大类，即冷家电、供暖、通风和空调、照明以及家庭成员活动消耗的能源。前三个组件使用工程物理为基础的模型建模，而个人的活动模式使用异构马尔可夫链建模。利用美国劳工统计局收集的数据，对一个普通美国家庭进行了案例研究。这些数据用于进行建模活动的样本验证，并提供了对计量数据的预测电力需求的严格统计验证。结果表明，捕捉年度和日变化，负载波动，家庭配置，位置和大小之间的多样性高度现实的模式。
This paper presents a model to simulate the electricity demand of a single household consisting of multiple individuals. The total consumption is divided into four main categories, namely cold appliances, heating, ventilation, and air conditioning, lighting, and energy consumed by household members’ activities. The first three components are modeled using engineering physically-based models, while the activity patterns of individuals are modeled using a heterogeneous Markov chain. Using data collected by the U.S. Bureau of Labor Statistics, a case study for an average American household is developed. The data are used to conduct an in-sample validation of the modeled activities and a rigorous statistical validation of the predicted electricity demand against metered data is provided. The results show highly realistic patterns that capture annual and diurnal variations, load fluctuations, and diversity between household configuration, location, and size.