Artificial Intelligence has firmly established itself in the energy sector. It sees a multitude of applications, from seemingly simple and well-defined tasks such as forecasting and optimization to safety-critical applications that aim to increase an energy system’s resilience. It is an active field of research and technical innovation, with scientists being quick to adopt the most up-to-date technologies, such as Large Language Models, while more established approaches, such as traditional agent systems, see continuous improvements towards practical application. However, the energy sector presents its own challenges. Not all aspects of artificial intelligence can be easily transferred from other domains to the energy sector. As critical infrastructure and a lifeline for modern society, the energy sector must guarantee the highest levels of reliability. Here, we present a survey on the current state of the art in artificial intelligence in the energy sector, highlighting current developments and major research and technology gaps.
Veith et al. (Wed,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: