【摘要】 针对微电网内可再生能源和负荷的不确定性，提出一种基于动态不确定集和电池损耗模型的两阶段鲁棒优化模型。通过引入对时间依赖的不确定集修正，动态调整风电、光伏和负荷的波动、预测范围，以提高调度计划的灵活性。同时，考虑电池储能系统在充放电过程中的损耗成本，建立基于充放电深度与功率损耗的电池损耗模型，优化储能系统的使用策略。模型采用C&CG算法求解，通过仿真验证方法在经济性和鲁棒性方面的有效性。结果表明，所提模型兼顾了经济性和稳定性，能够在保持低成本运行的基础上有效管理光伏、风电等新能源出力波动及负荷用电变化带来的挑战。更多还原

【Abstract】 This paper proposes a two-stage robust optimization model based on dynamic uncertainty sets and battery degradation model to address the uncertainties of renewable energy resources and loads in microgrids. By introducing time-dependent uncertainty set adjustments, the model dynamically regulates the fluctuation and prediction ranges of wind power, photovoltaic generation, and loads, enhancing scheduling flexibility. Additionally, the model incorporates battery degradation costs during charging and discharging cycles, establishing a degradation model based on depth of discharge and power losses to optimize storage system utilization strategies. The model is solved using a constraint and column generation algorithm, with simulation results validating its effectiveness in terms of economic efficiency and robustness. Results demonstrate that the proposed approach successfully balances cost-effectiveness and operational stability, effectively managing challenges from renewable energy output fluctuations and load variations while maintaining economical operation.更多还原