基于自适应滑动平均的模型预测控制策略OA

In view of the problem of charge and discharge imbalance caused by efficiency in the actual operation of the adaptive moving average algorithm's suppression results,this study proposes a control strategy based on model predictive control to optimize and adjust the target power of energy storage.Based on the adaptive window moving av-erage algorithm for solving the energy storage power,a hybrid energy storage system composed of lithium-ion battery and supercapacitors is adopted,and the complementary set empirical mode decomposition method is combined to ob-tain the energy storage target power and the preliminary energy storage capacity.Based on the operational characteris-tics of the wind power generation system and the demand for fluctuation suppression,the state space equation and re-lated constraint conditions are established for model predictive control to optimize the energy storage power.Through the simulated annealing algorithm,with the goal of minimizing the full life cycle cost of energy storage,the optimal capacity of the hybrid energy storage system is calculated.The case study analysis shows that in the hybrid energy storage system with the same capacity,the model predictive control strategy achieves energy balance in the hybrid en-ergy storage system and optimizes the charging and discharging power of the energy storage.In addition,the hybrid energy storage capacity calculated by the simulated annealing algorithm further reduces the life cycle cost.