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Finite Control Set Model Predictive Control with Model Parameter Correction for Power Conversion System in Battery Energy Storage Applications
IEEJ Transactions on Electrical and Electronic Engineering ( IF 1 ) Pub Date : 2020-05-12 , DOI: 10.1002/tee.23156
Ning Gao 1 , Xiaotao Chen 1 , Weimin Wu 1 , Xiangkun Li 1 , Frede Blaabjerg 2
Affiliation  

Adding a Battery Energy Storage System (BESS) in the vicinity of renewable energy sources is a feasible solution to overcome the inherent negative impact caused by their random power fluctuating problems. Power conversion system performs as an interface between the battery packs and grid. The control method of power conversion system is essential to BESS. Finite Control Set Model Predictive Control (FCS‐MPC) is favorable to be chosen as the core control method for grid‐injected current regulation in such a system due to its outstanding benefactions, including fast dynamics, multiobjective optimization and simple implementations. Hence, this paper presents a FCS‐MPC with active damping feature for an Inductor(L) Capacitor(C) Inductor(L) (LCL)‐filter‐based power conversion system first. However, it is also well known that the practical effect of model predictive control significantly relies on the accuracy of mathematical model embedded within the controller. Parametric mismatch of the model tends to generate a prediction error, leading to a deterioration of the power quality of power conversion system or even instability issues furthermore. Therefore, this paper proposes an additional model correction strategy based on a comprehensive on‐line analysis on the difference between predictive and real value of respective voltage or current signals during the ever‐lasting several grid cycles to eliminate the influence of parametric mismatch. Simulation of an LCL‐filter‐based power conversion system is carried out to verify the validity of the theoretical analysis and control method in this paper. Finally, experimental results obtained from a down‐scaled prototype are provided to confirm the feasibility of the overall control strategy. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

中文翻译:

电池储能应用中功率转换系统的有限控制集模型预测控制及模型参数校正

在可再生能源附近添加电池储能系统(BESS)是一种可行的解决方案,可以克服由于其随机功率波动问题而引起的固有负面影响。电源转换系统充当电池组和电网之间的接口。功率转换系统的控制方法对BESS至关重要。有限控制集模型预测控制(FCS-MPC)因其出色的优势(包括快速动态,多目标优化和简单的实现)而被选为此类系统中电网注入电流调节的核心控制方法。因此,本文首先介绍一种具有有源阻尼功能的FCS‐MPC,用于基于电感器(L)电容器(C)电感器(L)(LCL)滤波器的功率转换系统。然而,众所周知,模型预测控制的实际效果很大程度上取决于嵌入控制器中的数学模型的准确性。该模型的参数失配往往会产生预测误差,从而导致功率转换系统的电能质量下降,甚至导致不稳定问题。因此,本文基于持续在线几个电网周期内各个电压或电流信号的预测值与实际值之间的差异的全面在线分析,提出了一种附加的模型校正策略,以消除参数失配的影响。对基于LCL滤波器的功率转换系统进行了仿真,以验证本文理论分析和控制方法的有效性。最后,从缩小的原型获得的实验结果被提供以确认总体控制策略的可行性。©2020日本电气工程师学会。由John Wiley&Sons,Inc.发布
更新日期:2020-05-12
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