How Artificial Intelligence can accelerate the energy transition

A new white paper published by the World Economic Forum explains in detail the immense of potential of Artificial Intelligence in the energy transition. The scenario it describes is exciting, but a lot of work needs to be done.

Last month saw the publication of a white paper by the World Economic Forum, in collaboration with BloombergNEF (“New Energy Finance”) and Deutsche Agenzie-Agenture (dena): “Harnessing Artificial Intelligence to Accelerate the Energy Transition.” As a global leader in renewable energy, the Enel Group was also involved, and Giuseppe Amoroso, Head of Digital Strategy and Governance in Enel, was a member of the Paper’s editorial team.

The White Paper explains that “The global energy system is currently undergoing a massive transformation, and in the decades ahead, it will continue to become more decentralized, digitalized and decarbonized.” Not only that, the average power plant will be far smaller in future: the shrinkage in median size by 2050 is estimated to be 83%.

AI’s enormous potential

In this brave new decentralized and digitalized world, Artificial Intelligence (AI) has a vital role to play but, as the White Paper points out, so far we have only seen a fraction of its potential. In the words of the authors: “Despite its promise, AI’s use in the energy sector is limited, with it primarily deployed in pilot projects for predictive asset maintenance. While it is useful there, a much greater opportunity exists for AI to help accelerate the global energy transition than is currently realized.” They go on to say: “We believe that AI technologies will need to be deployed at a much larger scale and at a much faster pace to speed up the energy transition and lower the associated costs if we are to rapidly, safely and economically transition away from fossil fuels.” And if that doesn’t happen, things could become difficult: “Without realtime data, advanced analytics and automation, the increasingly complex power and energy systems of the future will become impossible to manage.”

In the Enel Green Power perimeter, the areas of the energy transition where AI can play a more active role include: the siting of solar and wind farms; power plant construction; predicting failures and outages, forecasting power production; and planning equipment operations (as well as the aforementioned maintenance activities). “We are embedding AI all across EGP in order to accelerate the energy transition,” says Giuseppe Serrecchia, Head of Enel Green Power Digital Hub, who adds: “AI is proving to be a key factor in making our assets more efficient, smarter, and more capable of boosting the energy transition. Algorithms are making the management of our assets all across their life-cycle much easier and more extensive, in a context where data are clustered in domains, and AI produces actionable insights for our colleagues.”

Guiding principles

The White Paper also sets out a series of principles that should guide the application of AI in the energy transition. These are divided into three categories: governing its use (standards, risk management and responsibility); its design (automation and sustainability) and its deployment at scale (data, education and incentives).

The White Paper naturally contains a number of recommendations and, above all, a call to action. The message is simple: “Companies and policy-makers must play an active role in governing and shaping the use of AI in the energy sector in a responsible way, and creating an enabling environment to unlock AI’s full potential.”