A Special Session on "Computational Intelligence in power electrical engineering" has been approved to take place within the 2026 IEEE World Congress on Computational Intelligence (WCCI), June 21 - 26, 2026, Maastricht, The Netherlands. Power electrical engineering is relevant to all the process of electrification of our society, both on the generation and on the consumer sides. Within the “electrical” research communities, the adoption of Computational Intelligence is becoming more and more widespread and it is thus a “cross-cut” topic where different applications share similar ideas and approaches. The Special Session wants to bring together academic and industrial researchers currently working on these topics.

The main topics are:

    Optimized design of electrical and EM devices
    Multi-Objective Optimization of electrical machines
    Multi-Objective Grid optimization
    Optimal control of renewable power generation and use
    Optimized battery design for EVs
    Optimal charging station location
    Use of ML/AI/LLM techniques to electrical and power applications
    Competition and Bench of optimization and meta-model methods.

Submission Guideline:

Papers for IEEE WCCI 2026 should be submitted electronically through the Congress submission portal, and will be refereed by experts in the fields and ranked based on the criteria of originality, significance, quality and clarity.

Please follow the IEEE WCCI 2026 Submission Website to prepare and submit the paper. Special session papers are treated the same as regular conference papers. All papers accepted and presented at IEEE WCCI 2026 will be included in the conference proceedings published by IEEE Explore. To submit your papers to the special session, please select this Special Session name in the Main Research topic

The Special Session is organised together by:

 Maurizio Repetto is a professor of Electrical Engineering at the "G. Ferraris" Energy Department of the Politecnico di Torino. His research interests include the analysis of electromagnetic fields in industrial devices and the optimization of electrical components and systems. He has coordinated research activities in the application of computational intelligence techniques to the optimal management of energy systems and the multi-physics design of electric traction motors.

Kalyanmoy Deb is a University Distinguished Professor at Michigan State University, known for his pioneering work in evolutionary multi-objective optimization (EMO). He holds the Koenig Endowed Chair in Electrical and Computer Engineering and has received numerous awards, including the IEEE Evolutionary Computation Pioneer Award and the Infosys Prize. His research focuses on multi-criterion optimization, machine learning, and their applications to industrial and societal problems, developing advanced genetic algorithms like NSGA-II and NSGA-III.

Marco Mussetta is a full professor of Electrical Engineering at the Department of Energy and Head of the PhD Program in Electrical Engineering at Politecnico di Milano, Italy. His research interests include global evolutionary optimization techniques applied to design of EM devices, and modeling and optimization of renewable energy systems by means of advanced soft computing techniques.