Rationally optimizing and allocating the wind

solar

and storage capacities at the desert-wasteland-Gobi renewable energy base is a crucial foundation for achieving efficient outbound transmission and reliable power supply support of the base's renewable energy. A multi-objective joint planning method for the capacities of wind

solar

and storage based on a bi-level time-sequential simulation optimization model is proposed

which considers the low-carbon

economic aspect of investment

and the adequacy of power supply. The upper-level optimization model aims to maximize renewable energy generation and minimize the total investment cost of wind

solar

and storage

considering constraints on the installed capacity of these resources. The lower-level optimization model aims to meet the peak evening demand of the receiving grid as its optimization objective

considering the coordinated operation constraints of renewable energy

conventional power sources

storage

and ultra-high voltage direct current

and achieves source-storage-grid coordinated operation optimization through annual 8760-hour sequential production simulation. The upper model uses the NSGA-Ⅱ algorithm for multi-objective optimization solving

and the lower model

based on the input parameters from the upper model

performs operational simulations and feeds the renewable energy absorption back to the upper model. Iterative solving yields the Pareto front

from which the optimal configuration capacity of a large-scale renewable energy base that balances economic

low-carbon

and sufficient power supply considerations is selected using the ideal point method. Based on a simulation test at a renewable energy base in China

the case studies verify the effectiveness of the proposed multi- objective optimization model.