摘要：Recently the optimal design of the solar power tower (SPT) plants have attracted increasing attention. In this paper, an improved algorithm combing the successive response surface methodology (SRSM) and simulated annealing (SA) global algorithm was proposed to achieve the efficient optimization design of the molten salt SPT plant with 2650 heliostats in Sevilla, Spain. Based on the traditional response surface methodology (RSM) and the adaptive domain reduction method, the SRSM was established to surrogate the complex thermo-economic model of the SPT plant to the updated approximation function, which was a high-order polynomial form to define the relationship between the objective parameter of the levelized cost of energy (LCOE) and 12 design variables related to the 4 subsystems of the SPT plant. After that, the SPT plant optimization design was performed by the SA global algorithm on the basis of SRSM. According to a comparison between the results obtained by the proposed method and the actual model-based global algorithm, the high accuracy and low computation time of the proposed strategy was proved.
