{"title":"A current optimization model predictive control with common-mode voltage reduction for three-level T-type inverters","authors":"Zhikang Guo, Zhaoxun Li, Weifeng Zhang, Yizhan Jiang, Yu Tian, Xiang Wu, Guojun Tan","doi":"10.1016/j.compeleceng.2025.110151","DOIUrl":null,"url":null,"abstract":"<div><div>This paper proposes a current optimization model predictive control with common-mode voltage (CMV) reduction (COMPC-CMVR) for three-level T-type inverters to suppress CMV and improve current quality without increasing the losses. The CMV is restricted within <em>u<sub>dc</sub></em>/6 by excluding voltage vectors (VVs) with high CMV. However, the reduction in VVs reduces the current quality. The neutral point (NP) voltage optimization interval is proposed in the COMPC-CMVR to improve the current control performance, where the grid current is the only control objective when the NP voltage is within the voltage optimization interval. The small and medium VVs are divided into P-type and N-type VVs to balance the NP voltage without weighting factors. On this basis, two novel candidate VVs sets are proposed. The COMPC-CMVR considers only four to seven feasible VVs in each control cycle, which reduces the computational burden. Finally, simulation and experimental results show that COMPC-CMVR performs well in terms of steady-state and transient responses. The COMPC-CMVR can effectively suppress the CMV and improve current quality without increasing the losses.</div></div>","PeriodicalId":50630,"journal":{"name":"Computers & Electrical Engineering","volume":"123 ","pages":"Article 110151"},"PeriodicalIF":4.0000,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers & Electrical Engineering","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0045790625000941","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
引用次数: 0
Abstract
This paper proposes a current optimization model predictive control with common-mode voltage (CMV) reduction (COMPC-CMVR) for three-level T-type inverters to suppress CMV and improve current quality without increasing the losses. The CMV is restricted within udc/6 by excluding voltage vectors (VVs) with high CMV. However, the reduction in VVs reduces the current quality. The neutral point (NP) voltage optimization interval is proposed in the COMPC-CMVR to improve the current control performance, where the grid current is the only control objective when the NP voltage is within the voltage optimization interval. The small and medium VVs are divided into P-type and N-type VVs to balance the NP voltage without weighting factors. On this basis, two novel candidate VVs sets are proposed. The COMPC-CMVR considers only four to seven feasible VVs in each control cycle, which reduces the computational burden. Finally, simulation and experimental results show that COMPC-CMVR performs well in terms of steady-state and transient responses. The COMPC-CMVR can effectively suppress the CMV and improve current quality without increasing the losses.
期刊介绍:
The impact of computers has nowhere been more revolutionary than in electrical engineering. The design, analysis, and operation of electrical and electronic systems are now dominated by computers, a transformation that has been motivated by the natural ease of interface between computers and electrical systems, and the promise of spectacular improvements in speed and efficiency.
Published since 1973, Computers & Electrical Engineering provides rapid publication of topical research into the integration of computer technology and computational techniques with electrical and electronic systems. The journal publishes papers featuring novel implementations of computers and computational techniques in areas like signal and image processing, high-performance computing, parallel processing, and communications. Special attention will be paid to papers describing innovative architectures, algorithms, and software tools.