Fengkun Ji and researchers modeled a high-capacity energy system featuring 130 megawatts of wind and 50 megawatts of solar power, supported by proton exchange membrane electrolyzers and fuel cells. By converting excess electricity into hydrogen for storage and capturing waste heat from fuel cells, the system optimizes energy consumption across hourly shifts. The model highlights the necessity of accounting for nonlinear equipment efficiency—how electrolyzers and fuel cells lose energy differently depending on their load—to achieve accurate results.
Optimization in Xinjiang
The simulation compared five operational setups, revealing that the most effective strategy utilized both hydrogen storage and thermal recovery. This configuration achieved zero renewable curtailment, meaning all available wind and solar power was put to use. During the modeled 24-hour window, recovered fuel-cell heat supplied roughly a quarter of the park's thermal demand. While the system still relies on grid electricity and natural-gas boilers for peak loads, the coordinated schedule significantly minimizes reliance on carbon-intensive sources. Beyond daily operations, a 20-year financial analysis suggests such retrofits could raise the project's internal rate of return from 5.8% to 8.3%, offering a viable pathway for industrial decarbonization despite the need for further equipment calibration and process-temperature verification.





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