A huge area of technological development, AI will likely impact all of the above areas of the energy transition – a factor recognised by the UAE National Strategy for AI 2031, which makes resources and energy one of its priority targets. [1] In essence, this technology can accelerate technological change, while also measuring, predicting and optimising complex systems of all kinds. In the energy transition, this includes using AI to plan grid expansion, find optimal transport routes, integrate variable renewable energy (VRE) and balance distributed energy grids. It also means improving transmission and distribution efficiency, building grid resilience, while using predictive capacities to cut down time and tackle disruptions – even to changes in demand and supply due to the weather. AI technology can also help accelerate the interpretation of geological data, smart metre data, the capacity and stability of differing CCSU systems and materials, and boost the detection of methane emissions by analysing much more data than is currently possible and pro-actively responding to it.
Natural selection
Not all the emerging clean energy tech of today will make it past the development stage. Indeed, the so-called ‘valley of death’ awaits innovators all along the path to commercial adoption and success.
Yet, the energy sector is already full of technologies from earlier transitions that had to go through a similar process. Oil and gas themselves – resources pioneered in the Arabian peninsula – were once costly and loss-making, yet are now key to the entire global economy. So too, for producers, today’s innovations may one day power their greener, more energy-efficient futures.
