Guest Editorial: Special issue on computational methods and artificial intelligence applications in low‐carbon energy systems

Climate change has raised serious concerns prompting urgent and broad actions that extend current operation techniques. Computational methods and artificial intelligence have already shown promising results in power systems applications, including analysis, forecasting and equipment inspection. Nevertheless, the urgency required in the clean energy shift will substantially increase operation uncertainty, as well as control and planning complexity. Leveraging the capabilities of faster computation, better accuracy and stronger decision-making from cutting-edge computational methods and artificial intelligence can be a promising approach to avoid most impacts in the clean energy transition, while improving system reliability, economics and sustainability. This special issue is focused on inviting original research, reviews and experimental evaluations to promote new computational methods and artificial intelligence applications in low-carbon energy systems. In this special issue, there are a total of 19 original research articles to present the state-of-the-art in energy forecasting, situational awareness, multi-energy system dispatch and power system operation. We would like to thank all participating authors for submitting their works to this special section. We really appreciate the anonymous reviewers' valuable efforts. We are thankful to Prof. David Infield, Prof. Tricoli Peitro and Prof. Panos Moutis, who suggested and supported the creation of this special section and nurtured its initial steps, and to Sophie Robinson, Nageen Matlub and Vinay Kumar Nim, Brianna Cooper, and Bhanuchandar Shanthakumar from IET for their administrative and editorial help. Yishen Wang: Conceptualization; writing—original draft. Fei Zhou: writing-review and editing. Josep M. Guerrero: writing-review and editing. Kyri Baker: investigation. Yize Chen: investigation; writing-review and editing. Hao Wang: investigation; writing-review and editing. Bolun Xu: investigation; writing-review and editing. Qianwen Xu: investigation; writing-review and editing. Hong Zhu: investigation. Utkarsha Agwan: investigation.