Multiple Model Predictive Hybrid Feedforward Control of Fuel Cell Power Generation System
AbstractSolid oxide fuel cell (SOFC) is widely considered as an alternative solution among the family of the sustainable distributed generation. Its load flexibility enables it adjusting the power output to meet the requirements from power grid balance. Although promising, its control is challenging when faced with load changes, during which the output voltage is required to be maintained as constant and fuel utilization rate kept within a safe range. Moreover, it makes the control even more intractable because of the multivariable coupling and strong nonlinearity within the wide-range operating conditions. To this end, this paper developed a multiple model predictive control strategy for reliable SOFC operation. The resistance load is regarded as a measurable disturbance, which is an input to the model predictive control as feedforward compensation. The coupling is accommodated by the receding horizon optimization. The nonlinearity is mitigated by the multiple linear models, the weighted sum of which serves as the final control execution. The merits of the proposed control structure are demonstrated by the simulation results. View Full-Text
- Supplementary File 1:
ZIP-Document (ZIP, 1400 KB)
Externally hosted supplementary file 1
Description: The MATLAB/SIMULINK files are available online at www.mdpi.com/link.
Share & Cite This Article
Wu, L.; Sun, L.; Shen, J.; Hua, Q. Multiple Model Predictive Hybrid Feedforward Control of Fuel Cell Power Generation System. Sustainability 2018, 10, 437.
Wu L, Sun L, Shen J, Hua Q. Multiple Model Predictive Hybrid Feedforward Control of Fuel Cell Power Generation System. Sustainability. 2018; 10(2):437.Chicago/Turabian Style
Wu, Long; Sun, Li; Shen, Jiong; Hua, Qingsong. 2018. "Multiple Model Predictive Hybrid Feedforward Control of Fuel Cell Power Generation System." Sustainability 10, no. 2: 437.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.