Research on Optimization Algorithm of Resource Allocation in Power Communication Network

With the rapid development of Smart Grid, modern power communication networks need to support more complex and dynamic functions, such as real-time monitoring, fault detection, demand response and distributed generation management. These functions put forward higher requirements on the structure of power communication networks and reasonable resource allocation. In view of the fact that existing algorithms cannot adapt well to the optimization of power communication network structure and reasonable resource allocation, this paper proposes an improved hybrid algorithm EAGO (Enhanced Ant Genetic Optimization) based on ACO (Ant Colony Optimization) algorithm and GA (Genetic Algorithm). Through simulation in the topology diagram of power communication network, relevant evaluation indicators are selected and compared with existing algorithms. The experimental results show that the EAGO algorithm in this paper is better than the comparison algorithm in reliability, packet loss rate, robustness and other indicators. Because it is a hybrid algorithm, the network load at different scales increases slightly.