AI for Energy Security

Composite image of virus background and power lines in the foreground, photo by vectorfusionart/Adobe Stock

Photo by vectorfusionart/Adobe Stock

What is the issue?

The world is in the grip of the largest energy crisis in fifty years. Countries around the world have seen a decrease in energy security, resulting in fuel poverty and economic hardship for billions of people. While the Russian war in Ukraine plays an important role in the current energy crisis, the underlying issues are structural. The energy forward markets already show that prices are likely to remain high for several years to come.

Given these enormous impacts, governments are looking for structural ways to improve energy security, which means ensuring the availability of adequate, cheap, and reliable supplies of energy to meet the needs of a nation. The increased deployment of artificial intelligence (AI) applications throughout the energy system could be a low-visibility, high-impact way to reduce consumption and increase the efficient use of energy, while limiting the impact on customers.

However, the use of AI applications in energy systems can hold significant security risks. For example, their use can create cybersecurity risks, data management risks, loss of human oversight, and technological lock-in. While the potential benefits of AI enabled energy systems may be large, policymakers should keep these risks in mind when deciding on their deployment.

How are we helping?

There is an urgent need for research into tools and techniques that can be employed to help lessen the effects of the current and future energy crises. AI applications could play a significant role, but the risks and benefits of their deployment in the energy sector are not well understood. This project aims to:

  1. Review the maturity of AI applications in this field, and to scan the horizon for new developments.
  2. Assess the extent to which AI applications can help in current and future energy crises.
  3. Evaluate the potential security risks that flow from the use of AI in energy systems, and to determine if and how these security risks can be managed and mitigated.