论文标题
数据驱动的模型，以预测电源系统中的关键电压事件
Data-driven Models to Anticipate Critical Voltage Events in Power Systems
论文作者
论文摘要
本文探讨了数据驱动模型使用简单的分类标签预测电源系统中电压偏移事件的有效性。通过将预测视为一项分类分类任务，工作流程的特征是计算负担低。关于意大利150 kV子跨传输网络的一部分的概念验证案例研究，该网络拥有大量的风能发电，证明了该提案的一般有效性，并深入了解了该应用程序的几种广泛使用预测模型的优势和劣势。
This paper explores the effectiveness of data-driven models to predict voltage excursion events in power systems using simple categorical labels. By treating the prediction as a categorical classification task, the workflow is characterized by a low computational and data burden. A proof-of-concept case study on a real portion of the Italian 150 kV sub-transmission network, which hosts a significant amount of wind power generation, demonstrates the general validity of the proposal and offers insight into the strengths and weaknesses of several widely utilized prediction models for this application.
