Optimizing green hydrogen production: a comparative analysis of MPPT control strategies for PV-powered PEM...

Area of Science:

• Renewable Energy Systems
• Electrochemical Engineering
• Sustainable Energy Solutions

Background:

• Hydrogen is a promising clean energy carrier for addressing energy scarcity and environmental concerns.
• Conventional hydrogen production methods, often reliant on fossil fuels, contribute to greenhouse gas emissions.
• There is a critical need for cost-effective, zero-emission hydrogen generation technologies.

Purpose of the Study:

• To analyze hydrogen generation from solar energy using a Proton Exchange Membrane (PEM) electrolyzer.
• To optimize the power output of photovoltaic (PV) systems feeding the electrolyzer.
• To compare the performance of different Maximum Power Point Tracking (MPPT) controllers for enhanced efficiency.

Main Methods:

• Utilized the Perturb and Observe (P&O) MPPT technique to maximize PV power output.
• Implemented and compared Fuzzy Logic (FL), Proportional-Integral (PI), and Fraction-Order PI (FOPI) controllers.
• Applied the Differentiated Creative Search Optimization (DCSO) algorithm for optimal tuning of PI and FOPI controllers, comparing it with Particle Swarm Optimization (PSO) and Grey Wolf Optimizer (GWO).

Main Results:

• The PI controller tuned by DCSO (PI-DCSO) yielded the highest power output at 6987 W.
• FOPI-DCSO achieved a power output of 6767 W, outperforming the Fuzzy Logic Controller (FLC) which produced 6296 W.
• Detailed comparisons of PV production and PEM electrolyzer performance under various conditions are presented.

Conclusions:

• The PI-DCSO controller demonstrates superior performance for solar-powered hydrogen generation via PEM electrolysis.
• Optimized MPPT control is crucial for maximizing energy conversion efficiency in such systems.
• This research contributes to the development of sustainable and efficient hydrogen production technologies.