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基于故障诱导状态方程建模的三电平T型变换器容错模型预测控制

Fault-Tolerant Model Predictive Control for Three-Level T-Type Converters Based on Fault-Induced State Equation Modeling

作者 Tianxu Cao · Dehao Kong · Chaohui Zhang · Bo Long · Marcelo Lobo Heldwein
期刊 IEEE Transactions on Industrial Electronics
出版日期 2025年10月
卷/期 第 73 卷 第 2 期
技术分类 控制与算法
技术标签 三电平 模型预测控制MPC 故障诊断 可靠性分析
相关度评分 ★★★★★ 5.0 / 5.0
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中文摘要

本文提出一种面向三电平T型变换器的容错模型预测控制方法,构建统一的故障诱导状态空间模型,融合电网侧电流与中点电压成本函数,并采用双环结构提升故障下系统可靠性与电能质量。

English Abstract

Three-level T-type converters (3LT${}^{\mathbf{2}}$Cs) provide inherent redundancies that can be used to improve system-level reliability, where fault-tolerant control (FTC) techniques are the enabling algorithms. Existing FTC methods primarily focus on compensating redundant vectors and adjusting dwell times, while neglecting the impact on modeling and control of grid-side currents and neutral-point (NP) voltage under fault conditions. This work formulates a unified fault-induced state space model that facilitates the construction of cost functions in finite-control-set model predictive control (FCS-MPC). The modeling is based on the investigation of the possible cases of single-switch and double-switch open-circuit faults, and the analysis of additional terms introduced by the faults. The proposed FTC method adopts a dual-loop control structure, i.e., the outer loop uses a proportional integral (PI) controller to automatically increase the reference value of the dc bus voltage during vertical faults and converts it into the grid current reference, while the inner loop combines fault-induced grid-side current and NP voltage cost functions in FCS-MPC, adjusting weighting factors based on fault conditions to prioritize grid-side current quality. Experimental results demonstrate the proposed FTC under various open-circuit fault scenarios.
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SunView 深度解读

该研究直接支撑阳光电源ST系列储能变流器(PCS)及PowerTitan液冷储能系统的高可靠性运行需求。三电平T型拓扑广泛应用于其1500V高压PCS产品,而开路故障容错能力对电站级储能系统长期免维护运行至关重要。建议将该MPC容错算法集成至iSolarCloud智能运维平台的实时控制层,优先在PowerTitan新一代液冷系统中开展硬件在环(HIL)验证,提升组串式光储系统在恶劣工况下的故障自愈能力。