Power-Rating Balance Control and Reliability Enhancement in Mismatched Photovoltaic Differential Power Processing Systems

Yinxiao Zhu, Huiqing Wen*, Guanying Chu, Xue Wang, Qilin Peng, Yihua Hu, Lin Jiang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

With the increase of the component number, the power stress distribution among differential power processing (DPP) converters, control implementation, system cost, and reliability become the most challenging issues for a practical photovoltaic (PV) DPP system. This article introduces an improved power-rating balance (IPRB) control for the PV-to-bus based DPP architecture that ensures each PV submodule operate at its true maximum power point (MPP) while achieving more balanced power stress distribution and higher reliability. Specifically, a submodule-level finite-state-machine-based MPP tracking is implemented to guarantee always maximum power yield, whereas a string-level power-rating balancing (PRB) control is adopted to balance the unit-maximum proceeded power by DPP converters based on the built power flow model with respect to the string current. A comprehensive comparison of advanced control strategies for PV-to-bus DPP architectures, including least power point tracking, voltage equalization (VE) based PRB control, and the proposed IPRB, has been carried out with the mission-profile-based reliability assessment under different partial shading scenarios. Component-failure-rate-based reliability analysis shows that the PV-to-bus DPP architecture with the proposed IPRB control can significantly improve the system reliability. Main simulation and experimental evaluations are carried out to verify the effectiveness of the proposed control.

Original languageEnglish
Pages (from-to)879-895
Number of pages17
JournalIEEE Transactions on Power Electronics
Volume37
Issue number1
Early online date1 Jul 2021
DOIs
Publication statusPublished - Jan 2022

Bibliographical note

Funding Information:
Manuscript received February 8, 2021; revised May 12, 2021; accepted June 24, 2021. Date of publication July 1, 2021; date of current version September 16, 2021. This work was supported in part by the Research Development Fund of XJTLU under Grant RDF-17-01-28, in part by the Research Enhancement Fund of XJTLU under Grant REF-17-01-02, in part by the Suzhou Prospective Application Programme under Grant SYG202016, and in part by the XJTLU Key Programme Special Fund under Grants KSF-A-08, KSF-E-13, and KSF-T-04. Recommended for publication by Associate Editor F. Gao. (Corresponding author: Huiqing Wen.) Yinxiao Zhu, Huiqing Wen, Guanying Chu, Xue Wang, and Qilin Peng are with the School of Advanced Technology, Xi’an Jiaotong-Liverpool University, Suzhou 215123, China (e-mail: Yinxiao.Zhu19@ student.xjtlu.edu.cn; Huiqing.Wen@xjtlu.edu.cn; Guanying.Chu@xjtlu.edu.cn; Xue.Wang19@student.xjtlu.edu.cn; qilinpeng6@gmail.com).

Keywords

  • Differential power processing (DPP)
  • maximum power point (MPP) tracking
  • mismatched photovoltaic (PV)
  • power-rating balancing (PRB)

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