Special Sessions

Session organizers

• Alfredo Vaccaro, Italy
• Silvia Iuliano, Italy
• Gian Marco Paldino, Belgium

Brief Description of the session thematic

Modern power systems are currently undergoing a paradigm shift driven by decarbonization policies and the large-scale integration of renewable energy sources. This transition is characterized by the progressive replacement of conventional large-scale synchronous generators with geographically dispersed, converter-based renewable power generators. Although this process is expected to substantially reduce greenhouse gas emissions and contribute to climate change mitigation, it also introduces significant technical challenges for power system operation and control. In particular, the inherent variability and stochastic nature of renewable generation profiles, combined with the high degree of spatial dispersion of generation assets, the limited availability of flexibility resources for real-time balancing, and the substantial reduction of system inertia, profoundly perturb the dynamic behavior of power systems. These factors increase the complexity of system operation, reduce the natural damping of electromechanical oscillations, and raise the vulnerability of power networks to dynamic perturbations.

In this context, enhancing the resilience and security of modern power systems has become a central objective, fostering the development of advanced, AI-based decision support systems for system operation. Such tools aim to enable predictive, diagnostic, and pro-active functionalities by supporting the early detection, classification, and assessment of contingencies and dynamic events that may compromise system security. The effective implementation of these solutions requires robust data-driven methodologies capable of efficiently exploring, managing, and analyzing large-scale, high-dimensional datasets. Moreover, these methodologies must support semantic and ontological information modeling, as well as real-time or near real-time reasoning over heterogeneous data streams acquired from geographically distributed sensing infrastructures. Addressing these issues represents a key research challenge for ensuring the secure, reliable, and resilient operation of future low-inertia power systems.

To address these challenges, this Special Session aims to foster discussion on advanced methodologies and enabling technologies for data mining and data analytics in power system applications. Particular emphasis is placed on techniques for real-time and near-real-time processing of data streams acquired from heterogeneous sensor networks, as well as on methods for the extraction, integration, and analysis of both semantic and content-based information derived from high-resolution measurement infrastructures, including supervisory control and data acquisition (SCADA) systems and phasor measurement units (PMUs).

Topics and Keywords

• AI in Power Systems: Advanced modeling, operation, and control techniques
• Proactive Management Systems: Enhancing security assessment in power systems
• AI-Driven Monitoring and Fault Diagnosis: Real-time detection and diagnosis for transmission and distribution grids
• Outage Risk Prediction: Assessing operational risks in transmission and distribution systems
• Smart Meter Data Analytics: Leveraging AI for optimized energy storage systems

All regular contributions to IEEE ICAIGE26 & S4IoT26 must be submitted online, in electronic format to :

https://confcomm.ieee-ies.org/app/general/conferences/ICAIGE-S4IoT26/initial-submission