Application of Artificial Intelligence in Energy Systems: Toward Low-Carbon and Economic Sustainability

Submission Deadline: 10 August 2026 View: 35 Submit to Special Issue

Guest Editors

Prof. Dr. Bo Yang

Email: yangbo_ac@outlook.com

Affiliation: Faculty of Electric Power Engineering, Kunming University of Science and Technology, Kunming, China

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Research Interests: AI-based optimization and control of renewable energy systems

Dr. Shuai Zhou

Email: zoey.zhou@aut.ac.nz

Affiliation: School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand

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Research Interests: power system control, integration of renewable energy (wind energy and PV systems), smart grids, artificial intelligence applied to power systems

Dr. Ning Yang

Email: ning.yang@strath.ac.uk

Affiliation: Department of Electronic & Electrical Engineering, University of Strathclyde, Glasgow, United Kingdom

Homepage:

Research Interests: vehicle-to-grid (V2G) interaction, artificial intelligence, collaborative optimization, electric vehicles, grid scheduling

Summary

In the context of global efforts to address climate change and advance the energy transition, Artificial Intelligence (AI) has emerged as a critical driver for building low-carbon, economical, and sustainable energy systems.

This Special Issue aims to explore cutting-edge applications of AI across energy generation, transmission, distribution, consumption, and market mechanisms, with a focus on how intelligent algorithms can enhance system efficiency, optimize renewable energy integration, and reduce operational costs. Topics of interest include, but are not limited to, AI-empowered smart grids, low-carbon solutions for AI infrastructure, intelligent energy storage and management, AI-driven demand response, carbon trading mechanisms, and the integration of advanced low-carbon technologies such as hydrogen systems and carbon capture.

We cordially invite scholars and engineers worldwide to contribute original research or review articles that advance the understanding and implementation of AI-driven energy systems, supporting the dual pathway toward net-zero emissions and economic optimization.

Potential topics aim at covering themes including, but not limited to:
· AI-Empowered Energy Systems and Smart Grids;
· Low-Carbon Energy Solutions for AI Infrastructure;
· Innovations in Intelligent Low-Carbon Technologies and System Integration;
· Energy Storage Technologies and Intelligent Energy Management;
· AI-Driven Energy Economics and Carbon Trading Mechanisms;
· Demand Response and Intelligent Load Management;
· Key Technologies and Synergies at the Energy-AI Nexus;
· Sustainability Assessment and Policy Research for Energy Systems.

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