(439e) Harnessing Excess Renewable Electricity for Green Hydrogen Production: Innovative Strategies from Three Continents

The quest for a net-zero future has positioned green hydrogen production at the forefront of sustainable energy solutions¹. However, the widespread adoption of green hydrogen faces significant barriers, primarily due to its high production costs and reliance on electricity and fresh water resources². This challenge is further exacerbated by the inefficiencies in the current energy systems, where substantial amounts of electricity generated from renewable sources are wasted due to the inherent mismatch between supply and demand³. This mismatch represents an opportunity for harnessing this renewable energy for the production of energy-intensive products like green hydrogen within a circular integration framework⁴. Acknowledging the critical role of optimizing the use of excess renewable electricity, this study introduces an innovative approach aimed at reshaping energy demand through the strategic use of media platforms. This method seeks to maximize green hydrogen production by effectively managing and utilizing surplus electricity. Our research focuses on three geographically and demographically diverse case studies: Hawaii, USA; Incheon, South Korea; and Melbourne, Australia. These locations are chosen due to their distinct electricity demand profiles, influenced by local weather patterns, demographic factors, and regional policies⁵. To explore the potential of media in influencing energy consumption behaviors, we conducted a comprehensive intercontinental field survey. The survey aimed to assess the impact of both traditional and social media on consumer energy use, particularly during peak demand periods. We collected responses from 640 participants regarding their household energy consumption following exposure to energy-saving content through popular media platforms. The data gathered enabled us to model various demand patterns, including cut-and-save, flattened-by-consumers, and flattened-by-AI strategies. These patterns illustrate different approaches to reducing and shifting energy demand, either directly by consumers or through AI-driven interventions^6,7. By integrating these demand patterns with simulations of renewable energy production systems—comprising solar photovoltaics, wind turbines, and battery storage—we evaluated the potential for annually recovering excess electricity. This surplus electricity was then allocated to power electrolyzers for green hydrogen production⁸. Our findings reveal that media-driven demand control can significantly enhance the efficiency of green hydrogen production by optimizing electricity consumption patterns. The effectiveness of these strategies, however, varies across the studied regions, highlighting the complex dynamics between renewable energy supply and demand. By expanding this study to include additional regions, we can further refine and adapt this model, offering a scalable and efficient strategy for leveraging excess renewable electricity.

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