Large-scale utilization of new energy such as wind and solar is an important way to achieve the goal of dual carbon

but its uncertainties affect the operation stability of power systems and the capability of absorbing new energy. This paper develops a capacity optimization allocation method considering uncertainties for wind-solar pumped storage power generation systems. First

a random distribution function is used to describe the output characteristics and load distributions of wind power and photovoltaic power generation

and a mathematical model of complementary power generation system is developed. Then

we construct a two-layer capacity optimization configuration model based on the information gap decision theory and the entropy weight method. Finally

we use a multiverse optimization algorithm to solve for capacity optimization configuration schemes. Calculations show that investors can adopt different allocation strategies for source-load uncertainty according to their investment intentions

and the operating results obtained can well meet the requirements in different operation modes and multiple operation scenarios. Our method can help reduce the comprehensive cost significantly

improve the capacity of new energy consumption

and maintain the long-term operation of pumped storage power stations.