Hybrid GA-PSO Power Allocation for Wireless Energy Transmission: Optimization and Simulation Study

Abstract

This project intends to use a combination of genetic algorithm and particle swarm optimization (GAPSO) to reasonably allocate energy between nodes in the wireless energy transmission system. First, considering the influence of channel attenuation and transmission distance on energy distribution, a mathematical model of the energy transmission system is established. Secondly, the genetic algorithm is used to optimize the system globally, PSO is used to speed up the local optimization speed, and finally, the optimal power allocation is achieved. Simulation experiments show that compared with the traditional single optimization method, the GA-PSO method has obvious advantages in energy transmission efficiency, node energy consumption and stability performance. The algorithm can effectively improve the system's transmission performance and reduce the system's energy consumption under different network topologies and channel conditions. At the same time, the GA-PSO algorithm has good convergence and computational complexity.