ZigBee wireless network for transformer load monitoring and temperature sensitivity analysis

This paper applies a ZigBee wireless network to monitor load conditions of transformers and analyze their temperature sensitivity. The developed approach can effectively monitor the operating states of transformers, thereby protecting transformers from burning by overloading via an early overloading warning system. The proposed method is suitable for many underground distribution transformers using a ZigBee wireless sensor network with minimal power consumption and good communication quality. Transformer load current and temperature are captured via a temperature and current sensing interface and transmitted to the ZigBee wireless network control center via the ZigBee wireless network. A transformer load database is complied. The relationship between load current and temperature is determined using a statistical regression method. The regression model of transformer load current and temperature is derived for temperature sensitivity analysis of transformer loading. The transformer load current variation following a temperature increase is then derived to construct an early warning mechanism for overloading, such that maintenance personnel can take the necessary actions to avoid power interruption and improve power quality.