{"id":1587,"date":"2025-11-28T17:38:52","date_gmt":"2025-11-28T17:38:52","guid":{"rendered":"https:\/\/www.gecad.isep.ipp.pt\/ERM-competitions\/?page_id=1587"},"modified":"2025-12-19T11:05:30","modified_gmt":"2025-12-19T11:05:30","slug":"ss2026electrimacs","status":"publish","type":"page","link":"https:\/\/www.gecad.isep.ipp.pt\/ERM-competitions\/ss2026electrimacs\/","title":{"rendered":"Call for special session – ELECTRIMACS 2026"},"content":{"rendered":"\n

AI-Driven Methods and Solutions for Intelligent Distribution Networks<\/strong><\/h4>\n\n\n\n

Parlermo, Italy, <\/strong>May 18-21, 2026<\/h4>\n\n\n\n

Organized<\/strong> by Jo\u00e3o Soares (jan@isep.ipp.pt), Bruno Francois, Dhaker Abbes, Zita Vale<\/p>\n\n\n\n

The accelerating digitalization and decentralization of power systems demand new paradigms for managing electricity distribution networks. Artificial Intelligence (AI) is a transformative enabler, reshaping how we plan, operate, and optimize distribution systems toward efficiency, resilience, and sustainability.<\/p>\n\n\n\n

This special session convenes cutting-edge research and real-world applications that harness AI, data analytics, and machine learning for the next generation of distribution grids. We welcome work spanning from AI algorithmic innovations to field deployments, addressing the operational, technical, and economic challenges faced by modern electricity networks.<\/p>\n\n\n\n

Recent advances in deep learning, reinforcement learning, and physics-informed data-driven modeling enable predictive maintenance, estimation, adaptive control, and self-healing capabilities. AI-based optimization and decision-making are facilitating the secure integration of distributed energy resources (DERs), electric mobility, and active customer participation.<\/p>\n\n\n\n

Contributions are especially encouraged that demonstrate how AI enhances: (i) grid planning and operation under uncertainty with high shares of renewables and prosumers; (ii) resilience and self-healing via intelligent monitoring, fault diagnosis, and restoration; (iii) real-time decision support using digital twins, edge analytics, and federated learning; (iv) decarbonization strategies and multi-energy coupling with predictive\/prescriptive analytics; and (v) market and flexibility mechanisms enabled by transactive energy systems and AI-driven trading.<\/p>\n\n\n

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Topics of Interest:<\/strong><\/p>\n\n\n\n