CISEM: Computational Intelligence for Sustainable Energy Management in Microgrids and Renewable Energy Communities 

The proposed workshop, "Computational Intelligence for Sustainable Energy Management in Microgrids and Renewable Energy Communities (CISEM 2026)", aligns seamlessly with the core themes of IJCNN 2026 by addressing the pressing need for intelligent, adaptive solutions to the global challenge of sustainable energy management, also considering the huge investments made by the EU and USA. 

As computational intelligence methods continue to drive innovation in fields requiring robust optimization, complex decision-making, and predictive analytics (i.e., energy time series forecasting), this workshop focuses on their critical application in energy systems. The sustainable integration of renewable resources, the optimization of energy flows in microgrids, and the effective management of energy within communities are not only timely but also resonate deeply with the conference's emphasis on impactful and multidisciplinary research. 

By fostering collaboration among utility executives, practitioners, experts in energy distribution and management, machine learning, evolutionary computation, and soft computing, the workshop aims to catalyze innovative solutions that enhance energy efficiency, reduce environmental impact, and prepare smart grids for future challenges. Topics cover also metering in smart grids, predictive maintenance, forecasting of renewable energy production and demand, battery modelling and Battery Management Systems synthesis, along with cloud computing as driving solutions for Renewable Energy Communities. 

Additionally, the workshop provides a platform for researchers to present cutting-edge advancements, share insights, and explore synergies, ensuring its strong contribution to the vibrancy and relevance of IJCNN 2026. This workshop serves as a focused point for advancing research and fostering collaboration on computational intelligence techniques tailored to smart grids and Renewable Energy Communities, providing a platform to address the pressing challenges and opportunities in optimizing energy management, sustainability, and efficiency

Topics of interest include but are not limited to:

• Energy time series forecasting for smart grids and renewable energy communities.

• Computational intelligence methods for energy flow optimization in microgrids.

• Predictive maintenance in energy systems using machine learning and soft computing techniques.

• Forecasting of renewable energy production and demand.

• Advanced metering infrastructure and data analytics in smart grids.

• Battery modeling and design of Battery Management Systems (BMS).

• Integration of evolutionary computation and swarm intelligence for energy systems.

• Cloud computing solutions for enhancing Renewable Energy Communities.

• Multi-agent systems for distributed energy resource management.

• Optimization of energy storage and hybrid energy systems.

• Adaptive control systems for dynamic energy grid management.

• Explainable AI for decision-making in energy distribution and management.

• Integration of IoT with computational intelligence for real-time energy monitoring.

• Cybersecurity and privacy in smart grids and renewable energy ecosystems.

• Sustainability-driven strategies for reducing environmental impact through intelligent systems.

• Collaborative frameworks for engaging stakeholders in energy community projects.

• Energy market simulation and optimization using computational intelligence.

• Intelligent solutions for grid resilience and stability under renewable energy penetration.

• The role of quantum computing in future energy management systems.

CISEM is part of the International Joint Conference on Neural Networks (IJCNN) at the World Congress on Computational Intelligence (WCCI)

Submission deadline: 31 January 2026