MPPT Strategy of Waterborne Bifacial Photovoltaic Power Generation System Based on Economic Model Predictive Control

Minan Tang (), Jinping Li, Jiandong Qiu, Xi Guo, Bo An, Yaqi Zhang and Wenjuan Wang
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Minan Tang: College of New Energy and Power Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
Jinping Li: College of New Energy and Power Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
Jiandong Qiu: College of Electrical and Mechanical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
Xi Guo: College of New Energy and Power Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
Bo An: College of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730050, China
Yaqi Zhang: College of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730050, China
Wenjuan Wang: College of New Energy and Power Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China

Energies, 2023, vol. 17, issue 1, 1-20

Abstract: At present, the new energy industry represented by photovoltaics has become the main force to realize the optimization of China’s energy structure and the goal of “double carbon”; with the absence of land resources, the waterborne bifacial photovoltaic has ushered in a new opportunity. Therefore, in order to address the problem that the maximum power point tracking (MPPT) of photovoltaics (PV) could not take into account, the dynamic economic performance in the control process, an economic model predictive control (EMPC), is proposed in this work to realize the MPPT of the waterborne bifacial PV power generation system. Firstly, the model of the bifacial PV module is constructed by combining the ray-tracing irradiance model and considering the effect of water surface albedo on the irradiance absorbed by the module. Secondly, the EMPC controller is designed based on the state-space model of the system to maximize the power generation as the economic performance index, and to solve the optimal input variables time by time to achieve a rolling optimization with the operational requirements of the system itself as the constraints. Thirdly, the MATLAB/Simulink (R2022a) simulation experimental results verify that the EMPC strategy could be utilized to achieve MPPT of the waterborne bifacial PV power generation system, according to the changes of environment. Finally, it is also demonstrated that the bifacial PV power generation system that employed the EMPC strategy outperformed the traditional MPPT algorithm, with respect to both output power tracking velocity and accuracy, and the power generation could be improved by about 6% to 14.5%, which significantly enhances the system’s dynamic process economics.

Keywords: economic model predictive control; waterborne bifacial photovoltaics; maximum power point tracking (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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