The popularization of electric vehicles raises concerns about their negative impact on the electrical grid. Extracting electric vehicle charging load patterns is a key factor that allows smart grid operators to make intelligent and informed decisions about conserving energy and promoting the stability of the electrical grid. This paper presents an unsupervised algorithm to extract electric vehicle charging load patterns nonintrusively from the smart meter data. Furthermore, a method to define flexibility for the collective electric vehicle charging demand by analyzing the time-variable patterns of the aggregated electric vehicle charging behaviors is presented. Validation results on real residential loads have shown that the proposed approach is a promising solution to extract electric vehicle charging loads and that the approach can effectively mitigate the interference of other appliances that have similar load behaviors as electric vehicles. Furthermore, a case study on real residential data to analyze electric vehicle charging trends and quantify the flexibility achievable from the aggregated electric vehicle load in different time periods is presented.

中文翻译：

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提取并定义住宅电动汽车充电负载的灵活性


电动汽车的普及引发了人们对其对电网负面影响的担忧。提取电动汽车充电负载模式是智能电网运营商能够就节约能源和促进电网稳定性做出明智且明智的决策的关键因素。本文提出了一种无监督算法，用于从智能电表数据中非侵入式地提取电动汽车充电负载模式。此外，提出了一种通过分析聚合电动汽车充电行为的时变模式来定义集体电动汽车充电需求灵活性的方法。对实际住宅负载的验证结果表明，所提出的方法是提取电动汽车充电负载的一种有前景的解决方案，并且该方法可以有效减轻与电动汽车具有相似负载行为的其他设备的干扰。此外，还介绍了真实住宅数据的案例研究，以分析电动汽车充电趋势并量化不同时间段内聚合电动汽车负载可实现的灵活性。