Enabling Clean Energy Resilience with Machine Learning-Empowered Underground Hydrogen Storage

arXiv:2404.03222v1 Announce Type: new
Abstract: To address the urgent challenge of climate change, there is a critical need to transition away from fossil fuels towards sustainable energy systems, with renewable energy sources playing a pivotal role. However, the inherent variability of renewable energy, without effective storage solutions, often leads to imbalances between energy supply and demand. Underground Hydrogen Storage (UHS) emerges as a promising long-term storage solution to bridge this gap, yet its widespread implementation is impeded by the high …

abstract arxiv challenge change clean energy climate climate change cs.lg cs.sy eess.sy enabling energy fossil fuels however hydrogen leads machine machine learning pivotal playing renewable resilience role solutions storage sustainable sustainable energy systems transition type