考虑负荷预测不确定性的快充站储能鲁棒实时控制策略

Robust Real-time Control Strategy for Energy Storage in Fast Charging Station Considering Load Forecasting Uncertainty

当电动汽车快速充电站配置电池储能系统时,合理的能量管理策略对控制充电负荷峰值功率、减小功率波动具有重要意义。然而,能量管理策略的有效性依赖于准确的负荷预测,但实际上由于环境影响和预测模型的原因负荷预测无法完全准确。基于以上问题,为应对充电站储能能量管理策略中充电负荷不确定造成的影响,提出了考虑负荷预测不确定性的储能鲁棒实时控制策略。首先,分析了现有的负荷预测方法,并对负荷预测结果进行建模;然后,运用鲁棒预测控制方法,分别以充电站电费最小和储能系统荷电状态波动最小为目标构建系统模型和设计控制策略,并通过鲁棒对等转化将不确定性模型消除,有效应对负荷预测不确定性的影响。算例研究表明,通过对比模型预测控制和逻辑门限控制的结果,所提的鲁棒控制策略能够有效降低充电负荷峰值,验证了策略的有效性。

Reasonable energy management strategy is of great significance to control the peak power of charging load and reduce the power fluctuation when the battery energy storage system is configured in the electric vehicle fast charging station.However,the effectiveness of the energy management strategy depends on the accurate load forecasting,which cannot be completely accurate due to environmental influences and forecasting models.Based on the above problems,in order to cope with the impact of charging load uncertainty in the energy storage management strategy of charging stations,this paper proposes a robust real-time control strategy for energy storage considering the load forecasting uncertainty.First,current load forecasting methods are analyzed and load forecasting results are modelled.Then,the robust predictive control method is used to establish the system model and design the control strategy respectively with the objective of minimizing the electricity charge of charging stations and the state of charge(SOC)fluctuation of the energy storage system.The uncertainty model is eliminated through robust counterpart transformation to effectively cope with the impact of the load forecasting uncertainty.Case studies show that the proposed robust control strategy can effectively reduce the peak charging load by comparing the results of model predictive control and logical threshold control,which verifies the effectiveness of the strategy.