面向政策退坡的长时储能系统多场景经济优化与容量配置研究OA

After the cancellation of the mandatory storage allocation policy in 2025,the energy storage industry is transforming from"policy-driven"to"market-driven"and the economic optimization and multi-scenario capacity allocation of long-term energy storage system have restricted its commercialization.To address this issue,firstly,based on the levelized cost of energy(LCOE)theory,the objective function is determined,and the dynamic parameters such as policy slope coefficient,technical cost and market electricity prices are integrated.The improved particle swarm optimization algorithm is used to solve the high-dimensional optimization problem,constructing a dynamic coupling model of"policy-technology-market"with three factors.Secondly,the single factor disturbance experiment and extreme scenario stress tests are carried out.Finally,the proposed model is compared with the traditional static model,and counterfactual simulation and actual project verification are carried out.The results show that the dynamic coupling model with three factors has passed the actual project test,showing significant advantages over the traditional static model.