Intelligent Fault Analysis and Operational Warning of Converter Valve in Offshore Wind Farms

The converter valve of offshore wind farms plays a crucial role in achieving efficient and stable operation of wind farms. With the continuous advancement of offshore wind power technology and the continuous increase in installed capacity, the application of converter valves will become increasingly widespread, making important contributions to the promotion and utilization of renewable energy and the optimization and upgrading of the global energy structure. This paper presents a Transformer-based algorithm for the sequential detection of capacitor values in MMC submodules of converter valves. Our model is trained and tested on a large dataset of real converter valve submodule capacitor values and compared with other recurrent neural network-based algorithms. Experimental results demonstrate that the proposed algorithm effectively detects and classifies faults, providing technical support for risk warning and intelligent operation and maintenance of converter stations.