Manuscript Topics

The recent development in power and energy fields is highly coupled with the advancement of information technologies. The large volume and availability of data collected from power grids and energy systems have formed unprecedented opportunities for inventing data-driven methods of supporting the power and energy system operations and maintenance. Machine learning and computational intelligence have played individually and jointly to generate novel solutions for emerging application scenarios in power and energy fields. Integrating domain knowledge to govern behaviors of models derived by machine learning and computational intelligence also recently received wide attention. This special issue thus aims to archive emerging development of machine learning and computational intelligence methods specially facing unique mathematical characteristics of power and energy application problems. Topics include:

• Machine learning for solving optimization tasks in power and energy systems;
• Advanced optimization algorithms for power and energy system operations and maintenance;
• Machine learning and computational intelligence methods for system condition monitoring;
• Transfer learning for power and energy applications;
• Privacy-preserving based machine learning for power and energy applications;
• New computational intelligence for data-driven modeling and system optimization;
• Other relevant topics are also highly welcome

Instructions for authors
https://www.aimspress.com/era/news/solo-detail/instructionsforauthors
Please submit your manuscript to online submission system
https://aimspress.jams.pub/