MPC METHOD BASED ON NSGA WEIGHT CORRECTION AND ITS APPLICATION IN PHOTOHYDROGEN SYSTEM

Liang Yuan; Wang Hongqing

doi:10.19912/j.0254-0096.tynxb.2023-1236

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Acta Energiae Solaris Sinica ›› 2024, Vol. 45 ›› Issue (11) : 131-140. DOI: 10.19912/j.0254-0096.tynxb.2023-1236

MPC METHOD BASED ON NSGA WEIGHT CORRECTION AND ITS APPLICATION IN PHOTOHYDROGEN SYSTEM

Liang Yuan, Wang Hongqing

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Abstract

Addressing the weight adjustment issue in MPC （model predictive control） optimization, a composite model is constructed for NSGA （non-dominated sorting genetic algorithms） based weight modification, taking the photo-hydrogen system as the research background. NSGA is used as the outer function, with the evaluation coefficients of the energy storage battery’s output capability, the total energy of the energy storage battery’s charge/discharge, and the AEL power fluctuation rate as objective functions. The weights are treated as input variables for the NSGA-MPC composite model, where they undergo selection, crossover, and mutation. The MPC optimization control method serves as the inner function, and for different weights, the computed output variables are used as input variables for the NSGA’s objective functions. After traversing and optimizing, the optimal weights are obtained. The optimal weights are compared with the existing research results in MPC optimization control regarding three aspects： objective function values, MPC tracking performance, and power fluctuation of the electrolyzer and energy storage battery. The results indicate that the optimal weights obtained in this study have partially reduced the power fluctuation of the electrolyzer and energy storage battery, thereby optimizing the MPC control tracking performance.

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genetic algorithms / model predictive control / weighing / hydrogen production / photohydrogen system

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Liang Yuan, Wang Hongqing. MPC METHOD BASED ON NSGA WEIGHT CORRECTION AND ITS APPLICATION IN PHOTOHYDROGEN SYSTEM[J]. Acta Energiae Solaris Sinica. 2024, 45(11): 131-140 https://doi.org/10.19912/j.0254-0096.tynxb.2023-1236

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