Load Loss Rate Evaluation Method of Sensitive Users Under Voltage Sag Based on Monitoring Data
Ying Wang, Yixuan Yang, Wenxi Hu, Xianyong Xiao, Xiaoyang Ma, Hang Yang
Abstract
Voltage sag can result in extensive losses of sensitive users. However, such losses have yet to be quantified based on power quality monitoring data. The load loss rate (LLR) is a practical index for evaluating the consequences of voltage sag, providing vital information for mitigation decisions. This study proposes a data-driven LLR evaluation method of sensitive users under voltage sag, which can be used as a basis for configuring mitigation devices. First, the LLR calculation index is proposed, based on the sensitive load response characteristics and the active power trajectory under voltage sags. Second, a feature indices system is established for the active power trajectory, based on the basic attributes and load response characteristics of sensitive load, to characterize the change of active power under voltage sag. Furthermore, a voltage sag data augmentation model is constructed to generate sample data, considering the characteristic calculation model of voltage sag and the probability density distribution of characteristics. Finally, LLR evaluation model is proposed, based on random forest regression for sensitive users under voltage sags. The effectiveness and accuracy of the proposed method are verified through a case study.