A MATLAB based occupant driven dynamic model for predicting residential power demand

Brandon J. Johnson, M. Starke, Omar A. Abdelaziz, R. Jackson, L. Tolbert
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引用次数: 20

Abstract

This paper presents a MATLAB based dynamic model for predicting residential power demand. Markov chain based occupant behavior models developed using data gathered by the U.S. Census Bureau in the American Time Use Survey (ATUS) are used in conjunction with models of the most common residential loads to predict residential power demand on a one-second time scale. First, the methods utilized for the modeling of each residential load are presented. Next, an explanation of how these load models are combined with occupant behavior models to predict residential power demand is given. Simulation results showing the overall contribution of each load to the overall residential sector power demand are shown for both winter and summer cases. Finally, future work will involve the use of this high-resolution dynamic residential model to estimate the potential for demand response from residential loads.
基于MATLAB的居民用电需求动态预测模型
提出了一种基于MATLAB的住宅用电需求动态预测模型。利用美国人口普查局在美国时间使用调查(ATUS)中收集的数据开发的基于马尔可夫链的居住者行为模型,与最常见的住宅负荷模型结合使用,以预测一秒时间尺度上的住宅电力需求。首先,介绍了各种住宅荷载的建模方法。接下来,解释了如何将这些负荷模型与居住者行为模型相结合来预测住宅电力需求。模拟结果显示了冬季和夏季情况下每个负荷对总体住宅部门电力需求的总体贡献。最后,未来的工作将涉及使用这种高分辨率动态住宅模型来估计住宅负荷的需求响应潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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