A modeling technique for generalized power quality data

Abstract

Power quality data mining is of great potential in both supply-side and demand-side energy management system. In recent decades, with the wide application of flexible AC/DC power grid and grid-connected renewable energy generation, power quality data has been unified as a generalized model for improving power quality. Meanwhile, power quality monitoring system has also been deployed on a large scale. In order to further highlight the availability and usability of power quality data, the paper integrates various types of information to support power quality analysis. A multimodal data system is constructed to process information collected in different forms into a multi-dimensional data model, which can be pretrained to provide integrated features for various power quality analysis tasks. Firstly, the three data types of voltage waveforms, texts and images are embedded through feature extraction, low-dimensional spatial representation and CNNbased representation, respectively. Then all information is fused with the interaction model based on Attention mechanism. The output of the data model can be sent to networks specific to certain downstream tasks.