From capacity transition to intelligent integration: Emerging trends and systemic risks in the global energy transformation

 The global energy system is undergoing a profound structural transition, characterized by an unprecedented acceleration in the deployment of renewable power and the convergence of digital intelligence with energy infrastructures. Recent developments across major economies suggest that the transformation is no longer incremental but systemic, reshaping both the supply composition and the governance logic of modern power systems.

 

A landmark shift can be observed in China’s power sector, where the combined installed capacity of solar and wind energy has, for the first time, surpassed that of coal-fired power. This transition signifies that non-fossil energy sources have evolved from supplementary contributors to dominant pillars of electricity supply. With projections indicating that non-fossil generation could account for approximately 63% of total electricity production, the Chinese case exemplifies a large-scale, rapid transition toward a low-carbon energy structure.

 

At the global level, the International Energy Agency has emphasized in its latest innovation outlook that energy security and industrial competitiveness are emerging as dual drivers of technological advancement. A new generation of breakthrough technologies—including perovskite photovoltaics, sodium-ion batteries, and enhanced geothermal systems—is gaining momentum. Notably, artificial intelligence is increasingly embedded in energy systems, enabling real-time demand forecasting, grid flexibility optimization, and lifecycle carbon management, thereby redefining the operational paradigm of energy networks.

 

In parallel, Europe is entering a critical phase in the industrialization of hydrogen technologies. The Clean Hydrogen Partnership has initiated substantial funding programs targeting next-generation electrochemical systems and solar-driven hydrogen production. Simultaneously, large-scale electrolyzer deployments in industrial sectors such as refining indicate that green hydrogen is transitioning from experimental validation to commercial-scale application, marking a pivotal step toward decarbonizing hard-to-abate industries.

 

The United Kingdom, meanwhile, is advancing an integrated strategy that combines nuclear fusion research with artificial intelligence. By leveraging AI-enabled supercomputing platforms to manage plasma dynamics and facilitate autonomous maintenance, the country aims to accelerate the commercialization pathway of fusion energy. This approach reflects a broader trend in which frontier energy technologies increasingly rely on digital intelligence to overcome physical and engineering constraints.

 

Despite these advancements, a critical future risk lies in the systemic integration of high shares of variable renewable energy with emerging storage and hydrogen infrastructures. In particular, the coordination between long-duration energy storage technologies—such as iron–air batteries and hybrid hydrogen–lithium systems—and AI-driven grid management remains insufficiently understood. This raises an important research direction: the development of multi-scale, AI-coordinated energy system architectures capable of ensuring stability, resilience, and economic efficiency under conditions of extreme renewable penetration. Addressing this challenge will be essential for translating technological breakthroughs into reliable and scalable energy transitions.