Deep Learning Based Environmental Prediction of High Voltage Converter Valve Hall for Converter Valve Operation Risk Assessment

High voltage direct current (HVDC)transmission system plays a crucial character in today's electric power system, converter station is a very crucial part of the system, high voltage converter valve hall is core of the converter station building, temperature and humidity in the valve hall must be controlled within the specified range. When the equipment fails, temperature will rise sharply, temperature and humidity of the whole valve hall will change. Therefore, it is indispensable to accurately monitor them so that faults can be detected. In this paper, Elman model is used to accurately predict temperature and humidity of the high voltage converter valve hall, which is of great significance to accurately monitor temperature and humidity of the valve hall.