Implicit Finite Control Set Model Predictive current Control for Modular Multilevel Converter based on IPA-SQP algorithm

H. Nademi, L. Norum
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引用次数: 11

Abstract

This paper investigates a Finite-Control-Set Model Predictive Control (FCS-MPC) for the precise control of (un)balanced load currents in Modular Multilevel Converter (MMC). The control objectives are circulating currents minimization inside the converter arms, achieve a capacitors voltage balance and load current control. To achieve the converter constrained optimization and facilitate the implementation on embedded systems, an integrated perturbation analysis and sequential quadratic programming (IPA-SQP) solver is also utilized. As a case study the proposed approach is applied to a grid-connected five-level MMC. The introduced FCS-MPC formulation reduces sensitivity of the converter output voltage to disturbances in grid side and measurement noise with reducing the computational burden. Simulation results reveal the effectiveness of the developed control scheme in cases when operational objectives, e.g., load current reference tracking and disturbance rejection are considered under system model uncertainties.
基于IPA-SQP算法的模块化多电平变换器隐式有限控制集模型预测电流控制
本文研究了模块化多电平变换器(MMC)中精确控制负载电流的有限控制集模型预测控制(FCS-MPC)。控制目标是使变换器臂内循环电流最小,实现电容器电压平衡和负载电流控制。为了实现变换器约束优化并便于在嵌入式系统上实现,还采用了微扰分析和顺序二次规划(IPA-SQP)集成求解器。最后将该方法应用于一个并网的五级MMC系统。引入的FCS-MPC公式降低了变换器输出电压对电网侧干扰和测量噪声的敏感性,同时减少了计算量。仿真结果表明,在系统模型不确定的情况下,考虑负载电流参考跟踪和干扰抑制等运行目标时,所提出的控制方案是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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