In this research work, a two-layer optimization model is established for the energy storage arrangement and the economical operation of the wind-solar combined power generation system. The goal of this model is to describe the mutual connection between the planning and the running of the energy storage system in the process of its capacity configuration optimization. The top layer of the model owns one single optimization goal, which is to cut down the overall whole life-circle cost of the energy storage system.At the same time, the goal of the lower-layer optimization is to cause the overall daily economic income in the process of system operation to reach maximum. For solving the two-layer optimization model, we hence put forward one enhanced self-adaptive forbidden annealing particle swarm algorithm. The viability of this algorithm is through the carrying out of tests on several famous test functions to be assessed.After this, the behavior result of the promoted algorithm is made comparison with that of the Particle Swarm Optimization (PSO) method, therefore, the algorithm’s better performance is confirmed. At last, through choosing the X large-scale new-energy base to be the research object, an evaluation is carried out on the optimized operation of the energy-storage battery. This evaluation is conducted in the situation that the configured energy-storage volume is 10 megawatts (MW) and the stored energy is 20 megawatt-hours (MWh).Furthermore, we have carried out an inquiry regarding the connection between the pure incomes obtained from energy-storage investment and the change in the rated capability of the energy storage. After we have completed the evaluation of the results, it is very clear that a bigger energy-storage volume arrangement is not certainly better. When the optimal disposition capacity of the new-energy base is 50 megawatt-hours and the ratio of energy-storage disposition takes up 11.47% of the new-energy installed capacity, hence the benefits reach their maximum.
