1.School of Electrical Engineering and Automation, Hefei University of Technology, Hefei 230009, China;2.Shandong Kehui Power Automation Co., Ltd., Zibo 255087, China;3.Electric Power Research Institute of State Grid Anhui Electric Power Company, Hefei 230022, China

In the data acquisition and communication applications of smart grid based on wireless sensor network (WSN) , communication reliability is a key technical indicator of WSN. Increasing the transmit power improves the signal strength and reliability of the communication, but simultaneously degrades the mutual interference between the nodes. To solve this contradiction, this paper studies the optimization of WSN transmit power in the smart grid based on the adaptive model predictive control method. The main factors affecting the signal-to-noise ratio (SNR) of wireless communication in the smart grid are analyzed based on the wireless communication link path loss model, and the system state space model is constructed. By real-time estimation of the lower bound of stochastic fluctuation confidence interval of SNR, the compensation is performed and the algorithm based on the model predictive control is used to optimize the transmit power of the node. Finally, the proposed algorithm is compared with the adaptive transmission power control (ATPC) and potential feedback control (PFC) algorithms by simulation software, and the algorithm is tested by WSN hardware platform. The adaptive model predictive control algorithm can reduce the mutual interference between nodes caused by too high transmit power under the condition of ensuring the reliability of smart grid wireless communication.

This work is supported by National Natural Science Foundation of China (No. 51877060), Fundamental Research Funds for the Central Universities (No. PA2019GDQT0006) and State Grid Corporation of China.