Research on Strategies to Improve the Dynamic Response Capability of Photovoltaic Inverters Based on Model Predictive Systems

Authors

  • Jiyue Jiang
  • Jialu Liu
  • Tianfan Yang

DOI:

https://doi.org/10.54097/zqc4z289

Keywords:

Leakage current, finite set model prediction, virtual voltage, two-step prediction method, parameter correction.

Abstract

While electronic technology has facilitated production and daily life, it has also brought certain issues, with leakage current being one of the most typical problems. Excessive leakage current can damage electrical equipment and even threaten the safety of personnel. Achieving maximum electrical safety has become a research hotspot in recent years. This paper, based on photovoltaic power generation systems, aims to improve the dynamic response capability of photovoltaic inverters through the establishment of predictive systems. The paper first analyzes the working principle and existing problems of model prediction, then lists the principles of three optimization schemes, including the introduction of virtual voltage, the two-step prediction method, and the recursive least squares method. It also analyzes the advantages and disadvantages of these three schemes and finally proposes the future development direction of using model prediction to suppress leakage current issues.

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References

Sun Zhiguo. Research on the Stability of Finite Set Model Predictive Control for Inverters [D]. Hebei University of Technology, 2023.

Li Lixiong, Yang Tongguang, Yuan Yueyang, et al. Maximum Power Point Tracking Algorithm for Photovoltaic Power Generation Systems Based on Improved Finite Set Model Predictive Control Strategy [J]. Power System Protection and Control, 2021, 49(17): 28-37.

Zhang Shisheng. Study on Model Predictive Control of Photovoltaic Systems Based on Single-phase Heric Grid-connected Inverter [D]. Lanzhou Jiaotong University, 2021.

Hua Zijie. Research on Single-phase Non-isolated Common-ground five-level Photovoltaic Grid-connected Inverter Based on Model Predictive Control [D]. Jiangsu University, 2023.

Tang Shengxue, Xing Luming, Li Xia, et al. Research on Mismatch Compensation Method of Finite Set Model Predictive Control for Inverters [J]. Journal of Electric Machines and Control, 2021, 25(11): 46-55.

Xing Luming. Research on Finite Set Model Predictive Control Method for Quasi-Z Source Inverters [D]. Hebei University of Technology, 2023.

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Published

26-03-2024

How to Cite

Jiang, J., Liu, J., & Yang, T. (2024). Research on Strategies to Improve the Dynamic Response Capability of Photovoltaic Inverters Based on Model Predictive Systems. Highlights in Science, Engineering and Technology, 87, 155-160. https://doi.org/10.54097/zqc4z289