Abstract: The operation of 5G communication base stations in remote areas requires a lot of power. The base

station power supply system composed of wind and solar new energy can well solve the problem of difficult access

to the power grid in remote areas. The selection of the component capacity of the new energy base station power

supply system has a significant impact on the stability and economy of the system. In order to realize the

comprehensive planning of stability and economy，the objective function was established as the total cost of

equivalent annuity and the load shortage rate and the capacity allocation optimization model was established with

the constraints of battery state of charge and annual pollutant emissions，the optimization algorithm NSGA-Ⅱ was

proposed to find the solution of Pareto front. Corresponding improvements were made to the random and crowded

comparison methods of the initial group selection of the original algorithm，which greatly improves the convergence of the improved algorithm and the uniformity of the Pareto front. Finally，the improved hybrid NSGA-Ⅱ algorithm was used to optimize the configuration of an exemplary communication base station power supply system in Sichuan Province. The effectiveness of the hybrid NSGA-Ⅱ algorithm was verified with the results of the calculation examples.

      Key words: 5G communication base station；hybrid NSGA-Ⅱ algorithm；optimal sizing；diversity of Pareto front