To explore the capacity value of a concentrating solar power (CSP) station,a method to optimize the thermal collection area and thermal storage capacity of a CSP station based on the credible capacity and levelized cost of energy (LCOE) is proposed in this paper. Firstly,generating efficiency model and economical model of CSP station are established in this paper. Secondly,the generation reliability of power generation system is calculated based on sequential Monte-Carlo method,and the particle swarm optimization (PSO) is utilized to search the credible capacity of the CSP station. Tthen the influences of solar multiple and thermal storage time on capacity credibility and LCOE of CSP station are studied. With credible capacity and levelized cost of energy as the optimization goal,weighted ideal point solution and entropy weight method are utilized to create a single objective optimization function and to determine the index weight respectively. Taking a CSP planning in the northwest as an example,using the region's real solar irradiation data,a model is established. The results show that the capacity credibility of CSP station increases monotonically with the increase of solar multiple and thermal storage time. At the same time,the levelized cost of energy decreases at the first stage and then increases at the second stage. The optimal solar multiple and thermal storage time is obtained under the constraints.