Optimization of thermal storage capacity of solar tower power considering peak regulation

Solar thermal power generation technology is an environment-friendly power generation technology that can make full use of solar energy. The power generating model and economical model of the concentrating solar power (CSP) station are established in this paper. The reliability of the power generation system is calculated based on the sequential Monte-Carlo method, and then the influences of solar multiple and thermal storage time on expected not supplied energy (EENS), internal rate of return (IRR), and Levelized cost of energy (LCOE) of CSP station are studied. Taking EENS, IRR, and LCOE as the optimization goal, the multi-objective optimization algorithm based on genetic algorithm was used to obtain the Pareto optimal solution. Results show that EENS decreases, and the LCOE decreases first and then increases with the increase of SM. The IRR is in contrast with LCOE. At last, a Pareto front is obtained to decide the parameters with different LCOE, IRR, and EENS.