Energy infrastructure faces transformation from grid software to space-based AI computing

The global energy landscape is facing significant shifts driven by grid modernization and the massive electricity demands of artificial intelligence. A market study by ABI Research projects that the core Grid Management software market will reach $77.2 billion by 2035. This growth is fueled by a transition from centralized generation to dynamic, bidirectional networks. Investment is increasingly moving toward Distributed Energy Resource Management Systems (DERMS) to manage decentralized inputs like rooftop solar and commercial battery storage.

Simultaneously, the rise of AI-focused data centres is placing unprecedented pressure on power grids. The International Energy Agency notes that a 100-megawatt hyperscale AI facility consumes roughly as much electricity as 100,000 households, with global data-centre demand expected to rise from 415 terawatt-hours in 2024 to 945 terawatt-hours by 2030.

To address grid queues and cooling challenges, companies are exploring space-based computing. Google’s ‘Project Suncatcher’ proposes using satellite constellations to leverage near-continuous sunlight and utilize radiators to reject heat into space. A two-satellite learning mission with Planet is planned for early 2027 to explore the technical and economic viability of these orbital data centres.