ICIEA 2026 Special Session
SS07: Artificial Intelligence for Smart Power and Energy Conversion
Organized by:
Organizer 1: Sheng Wang
Email: sheng.wang@glasgow.ac.uk
Affiliation: University of Glasgow, United Kingdom
Organizer 2: Xin Yuan
Email: xin.yuan@strath.ac.uk
Affiliation: University of Strathclyde, United Kingdom
Organizer 3: Zhenghua Chen
Email: zhenghua.chen@glasgow.ac.uk
Affiliation: University of Glasgow, United Kingdom
Organizer 4: Xiaoguang Zhang
Email: zxg@ncut.edu.cn
Affiliation: North China University of Technology, China
Organizer 5: Boyang Shen
Email: shenboyang@tongji.edu.cn
Affiliation: Tongji University, China
Organizer 6: Chuanyue Li
Email: lic23@scut.edu.cn
Affiliation: South China University of Technology, China
Organizer 7: Lu Zhang
Email: zhanglu1@cau.edu.cn
Affiliation: China Agricultural University, China
Artificial Intelligence (AI) has emerged as a transformative technology for modern power and energy conversion systems, offering new opportunities to enhance efficiency, reliability, and intelligence in industrial electronics. By integrating AI with advanced power converters, drives, and control architectures, the next generation of energy systems can achieve self-sensing, self-optimizing, and self-healing capabilities.
AI techniques enable power electronic systems to adapt dynamically to varying operating conditions, predict component degradation, and optimize performance across applications such as renewable energy integration, electric mobility, and smart grids. Leveraging data-driven modeling, intelligent control, and digital twins, AI empowers both hardware and software layers of power conversion systems to operate more efficiently and sustainably. This invited session intends to promote emerging technologies and methodologies in the application of artificial intelligence for smart power and energy conversion. Original and innovative research papers addressing the following technology areas and their potential applications are invited: