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Finite control set model predictive control integrated with disturbance observer for battery energy storage power conversion system

机译:有限控制集模型预测控制与电池储能电力转换系统干扰观测器集成

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摘要

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.
机译:典型的电池储能系统包括电池组的组合和电网绑定电源转换系统。电力转换系统的控制算法在利用传统的AC网格将存储在电池组中的DC能量接口时发挥着重要作用,以产生具有顺从的双向动力流量。有限控制集模型预测控制被认为是控制电力转换系统最有效的选择之一。然而,这种控制策略的性能大大取决于预测模型的准确性。模型中的参数不匹配导致预测误差,这会降低电源转换系统的整体功率质量性能。因此,本文研究了一种基于离散扰动观测器的稳健的有限控制装置模型预测控制方法,以消除模型不准确和不确定性引起的负面影响。从闭环杆的角度讨论了附加观察者的稳定性问题。执行参数扫描以在设计反馈矩阵时提供帮助。最后,从4.2 kVA额定额定的较低的原型获得的模拟和实验结果作为所提出的控制算法的验证进行。

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