Dynamic Electricity Demand Prediction for UK Households
Dynamic Electricity Demand Prediction for UK Households
复制标题
英国家庭的动态电力需求预测
DOI：
10.1016/j.egypro.2014.11.1095
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发表时间：
2014
期刊：
影响因子：
--
通讯作者：
Li Y
中科院分区：
文献类型：
--
作者：
Li Y
家庭用电负荷的性质很大程度上取决于居住者的需求。家庭能源使用，特别是电力，不仅与居民活动有关，还与电器类型和天气条件有关。为了管理和优化发电以及储能的有效利用，准确预测电力需求非常重要。本文提供了英国三栋住宅全年的高分辨率实际负载能源数据。我们为每个住宅制作了季节性模型，并分析特定时间的电器使用情况，以预测活跃居住者的数量。通过马尔可夫链技术随机生成每三十秒活跃占用的可能性，并使用马尔可夫链蒙特卡罗方法动态预测活跃占用者概况和相关电力需求。该方法可用于任何其他家庭住宅类型，以生成相应的活跃居住者档案。预测的电力概况可用于有效的需求侧管理。
The nature of domestic electricity load is highly dependent on the demand of occupants. Domestic energy use, especially for electricity, is not only based on residents activities, also related with the type of electrical appliances and weather conditions. To manage and optimise electricity generation and the effective use of energy storage, it is important to be able to accurately predict electricity demand. This paper presents high-resolution real load energy data for three UK dwellings throughout the year. Seasonal models have been produced for each dwelling and the use of electrical appliances at certain times are analysed to predict the number of active occupants. The possibility of active occupancy at each thirty seconds is generated stochastically by Markov-Chain technique and Markov-Chain Monte Carlo method is used to predict the active occupant profiles and the related electricity demand dynamically. The methodology can be used for any other domestic dwelling type to generate corresponding active occupant profile. The predicted electricity profile can be used for effective demand side management.