Abstract

This paper shows control approaches for managing a pressurized Solid Oxide Fuel Cell (SOFC) system fuelled by biogas. This is an advanced solution to integrate the high efficiency benefits of a pressurized SOFC with a renewable source. The operative conditions of these analyses are based on the matching with an emulator rig including a T100 machine for tests in cyber-physical mode (a real-time model including components emulated in the rig, operating in parallel with the experimental facility and used to manage some properties in the plant, such as the turbine outlet temperature set-point and the air flow injected in the anodic circuit). The T100 machine is a microturbine able to produce a nominal electric power output of 100 kW. So, the paper presents a real-time model including the fuel cell, the off-gas burner, and the recirculation lines. Although the microturbine components are planned to be evaluated with the hardware devices, the model includes also the T100 expander for machine control reasons, as detailed presented in the devoted section. The simulations shown in this paper regard the assessment of an innovative control tool based on the Model Predictive Control (MPC) technology. This controller and an additional tool based on the coupling of MPC and PID approaches were assessed against the application of Proportional Integral Derivative (PID) controllers. The control targets consider both steady-state (e.g. high efficiency solutions) and dynamic aspects (stress smoothing in the cell). Moreover, different control solutions are presented to operate the system during fuel cell degradation. The results include the system response to load variations, and SOFC voltage decrease. Special attention is devoted to the fuel cell system constraints, such as temperature and time-dependent thermal gradient. Considering the simulations including SOFC degradation, the MPC was able to decrease the thermal stress, but it was not able to compensate the degradation. On the other hand, the tool based on the coupling of the MPC and the PID approaches produced the best results in terms of set-point matching, and SOFC thermal stress containment.

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