熵在典型负荷曲线分类中的应用

D. Hock, Martin Kappes
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引用次数: 0

摘要

可以利用能源消费者集群来提高负荷预测的准确性,或者根据消费者的能源需求引入差异化和个性化的电价。在本文中,我们的目标是根据其与其他家庭的相似度对能源负荷曲线进行分类。将熵作为典型负荷曲线分类和聚类的定量度量。此外,我们提出了时间段的可能性,以唯一区分居民家庭的负荷曲线,并近似分类任务所需的最小时间分辨率。结果,使用真实世界的数据集,我们证实了我们的方法的实际相关性和可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using the Entropy for Typical Load Curve Classification
Clusters of energy consumers can be utilized to improve the accuracy of load forecasting or to introduce differentiated and personalized tariffs according to the consumers energy demand. In this paper, we aim to classify energy load curves according to their similarity with other households. We present the entropy as quantitative metric for Typical Load Curve Classification and clustering. Furthermore, we present the likelihood of time periods to uniquely distinguish load curves of residential households and approximate the minimal required time resolution for classification tasks. Results, using a real world data set, we confirm the practical relevance and feasibility of our approach.
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