Power Grid Harmonic Source Tracing Technology Based on Massive Monitoring Data Correlation Analysis

Power quality includes various pollution phenomena in the power system, and its time-frequency characteristics vary greatly. Most transient phenomena require high-frequency sampling of signals, while harmonic distortion levels and voltage variations require long-term continuous and stable sampling. Extensive tracking and measurement of all different types of power quality phenomena at numerous monitoring points may result in excessive hardware investment, communication costs, and data management costs. Therefore, currently, monitoring points are generally selected based on the current status and development of the power grid, and coverage monitoring of the power grid area has not yet been achieved. This article is based on big data technology and focuses on “analysis of power quality characteristics and state research of regional power grids”. Starting from the study of harmonic characteristics in the context of new source-grid-load environments, we first analyze the harmonic emission characteristics of major harmonic sources, and study the propagation and correlation characteristics of harmonics through hierarchical data feature extraction techniques. Secondly, through the results of various data correlation analyses, research and analysis are conducted on massive power quality data to achieve harmonic traceability technology for regional power grid power quality. The calculation example shows that the proposed method of locating harmonic sources in the power grid according to different voltage levels and topology connection relationships, identifies the main source bus and key suspected lines of harmonics, and achieves harmonic traceability at the grid level.