Review of Site Testing Technologies for Converter Transformers

As a critical component of high-voltage direct current (HVDC) transmission systems, converter transformers provide essential support for AC/DC energy conversion. Typically deployed in ultra-high voltage (UHV) scenarios, these converter transformers feature large capacities, high short-circuit currents, and significant grid impacts during fault-induced tripping, necessitating regular testing and condition diagnostics to ensure grid stability. On-site testing integrates historical operational data, offline testing, and online monitoring to enable intelligent perception of electrical, magnetic, thermal, and acoustic parameters, offering critical insights for comprehensive performance evaluation. This paper synthesizes recent global research to analyze the primary fault types and characteristics of key components, including the core assembly, windings, bushings, tap changers, and leads. A systematic review is conducted on applied/induced voltage withstand tests with partial discharge detection, external interference suppression techniques, and opencircuit/load testing protocols, covering their categories, functions, applicable scenarios, implementation methods, and key considerations. Furthermore, the integration of on-site testing, multi-signal online monitoring, and artificial intelligence (AI) in diagnostics is examined. Emerging trends-such as AI-driven predictive analytics, quantum sensing, and digital twin technologies-are highlighted to guide the large-scale deployment of HVDC infrastructure.