More action is urgently needed to avoid catastrophic long-term climate impacts, according to the new IPCC assessment. Because fossil fuels still provide more than 80% of worldwide energy, the energy industry must be at the forefront of this effort.
Luckily, the energy system already is changing: renewable energy production is fast increasing, thanks to dropping costs and increased investor interest. The scope and price of decarbonizing the worldwide energy system, on the other hand, remain enormous, and time is running out.
To date, most of the energy sector’s transition efforts have been concentrated on hardware: new low-carbon facilities to replace aging carbon-intensive systems. Another crucial tool for the transition has received relatively little attention and investment: next-generation digital technologies, particularly artificial intelligence (AI). These sophisticated technologies can be used at greater scales more quickly than new hardware alternatives, and they could become a critical facilitator for the energy transition.
AI’s potential to accelerate the energy transition is being driven by three important trends:
1. Energy-intensive industries such as power, transportation, heavy industry, and buildings are undergoing historic decarbonization processes, fuelled by rising government and customer needs for rapid CO2 emission reductions. These transitions are massive in scope: According to BloombergNEF, reaching net-zero emissions in the energy sector alone will require $92 trillion to $173 trillion in infrastructure investments by the year 2050. In the green energy and low-carbon industries, even tiny advances in flexibility, efficiency, or capacity can result in trillions of dollars in value and savings.
2. The power industry is becoming the primary pillar of the global energy supply as electricity feeds more sectors and applications. As the worldwide power industry continues to decarbonize, more power will be provided by intermittent sources (like solar and wind), developing new demands for coordination, forecasting, and flexible usage to guarantee that power grids can operate safely and reliably.
3. The shift to low-carbon energy systems is accelerating the development of power generation, distributed storage, and sophisticated demand-response capabilities, all of which must be orchestrated and incorporated via additional networked, transactional power grids.
The energy system and energy-intensive sectors face enormous strategic and operational difficulties in navigating these trends. AI can assist energy-system interested parties to identify trends and correlations in data, learn from experience to improve overall system performance, and anticipate and model possible results of complex, multivariate situations by establishing an intelligent collaboration layer across the generation, transmission, and use of energy.