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Thermal management is vital for the efficient and safe operation of alkalineelectrolysis systems. Traditional alkaline electrolysis systems use simpleproportional-integral-differentiation (PID) controllers to maintain the stacktemperature near the rated value. However, in renewable-to-hydrogen scenarios,the stack temperature is disturbed by load fluctuations, and the temperatureovershoot phenomenon occurs which can exceed the upper limit and harm thestack. This paper focuses on the thermal modelling and controller design of analkaline electrolysis system under dynamic operating conditions. Acontrol-oriented thermal model is established in the form of a third-ordertime-delay process, which is used for simulation and controller design. Basedon this model, we propose two novel controllers to reduce temperatureovershoot: one is a current feed-forward PID controller (PID-I), the other is amodel predictive controller (MPC). Their performances are tested on a lab-scalesystem and the experimental results are satisfying: the temperature overshootis reduced by 2.2 degree with the PID-I controller, and no obvious overshoot isobserved with the MPC controller. Furthermore, the thermal dynamic performanceof an MW-scale alkaline electrolysis system is analyzed by simulation, whichshows that the temperature overshoot phenomenon is more general in largesystems. The proposed method allows for higher temperature set points which canimprove system efficiency by 1%.

Thermal Modelling and Controller Design of an Alkaline Electrolysis System under Dynamic Operating Conditions