Data Collection and Transmission of Wireless Sensor Networks in Smart Grid Monitoring

This study investigates the data acquisition and transmission technology based on wireless sensor networks to address the requirements of smart grid monitoring systems. A novel method is proposed to enhance the security and stability of data transmission, which incorporates a data transmission channel model, as well as techniques such as segment balancing adjustment, steady-state power quality fusion compensation, and channel attenuation suppression. Specifically, a diversity interval balance matching strategy is employed to optimize channel segmentation, in conjunction with steady-state power quality compensation and channel attenuation suppression techniques. Data grouping and collaborative adjustment are conducted using the fuzzy clustering and feature matching principles of the smart grid monitoring model. During the transmission process, adaptive control is implemented based on the steady-state power quality characteristics to reduce the imbalance caused by voltage fluctuations. The experimental results demonstrate that this method significantly enhances the anti-interference capability of the smart grid monitoring system, reducing the error rate to an average of 0.0515. Concurrently, the end-to-end delay is optimized, and the average transmission rate attains 65.03 bits s −1 , effectively improving the stability and accuracy of data acquisition and transmission.