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Assessment of typical residential customers load profiles by using clustering techniques

机译:使用聚类技术评估典型的住宅客户负载配置文件

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This paper proposes a methodology for finding typical load profiles for residential customers by using clustering techniques. Such task is particularly challenging due to the great diversity of electricity use by residential customers. Specific characteristics of this kind of customers, as number of inhabitants or house surface, may help the clustering, but such features are often, maybe always, unknowable. In the paper, geographic information of customers, always known, has been used as first discriminant for grouping homogeneous daily profiles. Then, different clustering algorithms have been applied to a database of real customers and compared to verify their effectiveness. Finally, to validate the proposed approach ad hoc validation tests has been performed by considering a new database not used for clustering.
机译:本文提出了一种通过使用聚类技术来查找住宅客户的典型负载配置文件的方法。由于住宅客户的电力多样性,此类任务特别具有挑战性。这种客户的具体特征,居民或房屋表面的数量,可能有助于聚类,但这些功能通常是,也许总是不可知的。在论文中,客户的地理信息始终知道,已被用作分组均匀日常概况的第一判别。然后,不同的聚类算法已应用于真实客户的数据库,并与验证其有效性相比。最后,为了验证所提出的方法,通过考虑未用于群集的新数据库来执行ad hoc验证测试。

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