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Sustainability 2018, 10(2), 437; doi:10.3390/su10020437

Multiple Model Predictive Hybrid Feedforward Control of Fuel Cell Power Generation System

Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education, School of Energy and Environment, Southeast University, Sipailou 2, Nanjing 210096, China
School of Mechanical and Electrical Engineering, Qingdao University, Ningxia Road 308, Qingdao 266071, China
Author to whom correspondence should be addressed.
Received: 6 January 2018 / Revised: 1 February 2018 / Accepted: 4 February 2018 / Published: 8 February 2018
(This article belongs to the Special Issue Hydrogen Production and Utilization)
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Solid 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
Keywords: solid oxide fuel cell; constant output voltage; multiple model predictive control solid oxide fuel cell; constant output voltage; multiple model predictive control

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Wu, L.; Sun, L.; Shen, J.; Hua, Q. Multiple Model Predictive Hybrid Feedforward Control of Fuel Cell Power Generation System. Sustainability 2018, 10, 437.

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