A typical battery energy storage system consists of a combination of battery packs and a grid-tied power conversion system. The control algorithm of the power conversion system plays an important role when interfacing the DC energy stored in battery packs with the conventional AC grid to generate an obedient bidirectional power flow. Finite control set model predictive control is believed to be one of the most effective choices for controlling power conversion systems. However, the performance of such a control strategy heavily depends on the accuracy of the predictive model. Parameter mismatch in the model leads to prediction error, which deteriorates the overall power quality performance of the power conversion system. Therefore, this paper studies a robust finite control set model predictive control method based on a discrete disturbance observer to eliminate the negative effects caused by model inaccuracy and uncertainty. The stability issue of the additional observer is discussed from the perspective of closed-loop poles. Parameter scan is performed to provide assistance in designing the feedback matrix. Finally, simulations and experimental results obtained from a downscaled prototype rated at 4.2 kVA are conducted as a validation of the presented control algorithm.

典型的电池能量存储系统由电池组和并网电源转换系统的组合组成。当将电池组中存储的DC能量与常规AC电网连接以产生顺从的双向功率流时，功率转换系统的控制算法起着重要作用。有限控制集模型预测控制被认为是控制功率转换系统的最有效选择之一。但是，这种控制策略的性能在很大程度上取决于预测模型的准确性。模型中的参数不匹配会导致预测误差，从而使电源转换系统的整体电源质量性能下降。因此，本文研究了一种基于离散干扰观测器的鲁棒有限控制集模型预测控制方法，以消除模型不准确和不确定性引起的负面影响。从闭环极点的角度讨论了额外观察者的稳定性问题。执行参数扫描以帮助设计反馈矩阵。最后，从额定值为4.2 kVA的缩小原型获得的仿真和实验结果作为对所提出控制算法的验证。