Implementation of advanced control and optimization algorithms on integrated Photovoltaic (PV) and Electrolysers system for sustainability

Abstract

The European Union (EU) has set an ambitious target to reach carbon neutrality by 2050, prompting industries to develop roadmaps to achieve this goal. In this context, hydrogen and hydrogen-based fuels play a crucial role in achieving net-zero emissions. Instead of relying on hydrogen production from steam reforming natural gas systems, electrolysers offer a sustainable alternative to address climate and energy challenges although they have higher production cost at the moment.

The integration of solar energy systems with electrolysers can further diminish carbon emissions and enhance sustainability. Typically, these processes are simulated using process simulation software platforms that employ first-principle models based on the mass and energy balances within the system. The adoption of Model Predictive Control (MPC) algorithms not only benefit from improves advance control methods and optimization but also facilitates the automation and efficient operation of these processes.

This study aims to mathematically model and simulate an integrated photovoltaic (PV) and Proton Exchange Membrane (PEM) water electrolyser system for hydrogen production. A detailed model of the PEM electrolyser has been presented based on the mass balance equation of anode, cathode and membrane part in addition to overpotential simulation. Additionally, energy balance equation has been derived to be able to model and simulate MPC algorithm. Finally, the study identifies the successful temperature tracking of the PEM electrolyser using MPC algorithms which designed based on linear state space form model.