文章基本信息

标题：Classification of New Active Consumers Performance According to Previous Events Using Decision Trees
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作者：Cátia Silva ; Pedro Faria ; Zita Vale 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2022
卷号：55
期号：9
页码：297-302
DOI：10.1016/j.ifacol.2022.07.052
语种：English
出版社：Elsevier
摘要：AbstractWith the growing concern regarding climate change, solutions such as distributed generation, namely renewable-based, increased in the energy system. However, their volatile behavior needed more flexibility from the demand side to balance – resorting to demand response programs. Active consumers play a critical role in this new paradigm. In this way, the uncertainty of their response to triggered events should be modeled. The authors developed a contextual consumer rate to properly select the participants in a demand response event according to their previous events in similar contexts. The innovation in the present paper lies in the classification of new active consumers with no prior experience. A decision tree method was then used to attribute a trustworthy rate. A sensitivity study on the number of leaf nodes used is explored. The results prove that the use of private information related to active consumer increase the performance of the algorithm.
关键词：KeywordsActive consumerBehaviorDecision TreesDemand ResponseUncertainty