The reasonable allocation of energy storage is of great significance for improving the utilization rate of power transmission and ensuring the efficient and stable outbound delivery of renewable energy electricity. This paper first constructs an active output model for new energy power sources

active regulation power sources

and energy storage systems. Then

combined with the cyclical characteristics of local consumption and outbound power

it achieves the time-series production simulation of the renewable energy base. Based on this

it establishes an energy storage optimization configuration model for renewable energy bases with the goal of minimizing system operating costs while considering both local consumption and outbound delivery. An multi-objective Particle Swarm Optimization (MOPSO) was used to solve the model. Based on Fuzzy membership degree

an energy storage satisfaction evaluation index was constructed

and decision-making from optimal Pareto solution set to compromise energy storage configuration was achieved based on. Taking the annual planning scenario a new energy base in China as an example

the optimization configuration and decision-making method proposed in this paper was used to achieve energy storage configuration for the new energy base that balances economics and power supply reliability. The results show that the energy storage capacity obtained by the algorithm in this paper not only significantly reduces system operating costs while meeting domestic and export requirements

but also further increases the power supply guarantee rate of the export channel.