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SPECIAL SESSIONS

SPECIAL SESSION 1 (SS1)

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ENERGY STORAGE SYSTEMS: ADVANCED MODELING, SIMULATION, POWER CONVERSION, CONTROL, AND DIAGNOSTICS

 

Co-Chairs

  • Walter Zamboni, Dipartimento di Ingegneria dell'Informazione ed Elettrica e Matematica Applicata (DIEM), Università degli Studi di Salerno (UNISA), Italy, email: wzamboni@unisa.it

  • Andrea Trovò, Dipartimento di Ingegneria Industriale (DII), Università degli Studi di Padova (UNIPD), Italy, email: andrea.trovo@unipd.it

  • Emilio Pérez Soler, Departament d'Enginyeria de Sistemes Industrials i Disseny (ESID), Universitat Jaume I (UJI), Spain, email: pereze@uji.es

  • Brian Ospina Agudelo, École Supérieure d'Ingénieurs en Électrotechnique et Électronique (ESIEE), Université Gustave Eiffel (UGE), France, e-mail: brian.ospina-agudelo@univ-eiffel.fr

 

Theme

Energy Storage Systems (ESSs) are crucial for applications in e-mobility, robotics, drones, renewable energy, and micro/nanogrids. ESSs are complex and costly, integrating Battery Management Systems (BMSs) for optimal operation and AC/DC or DC/DC converters to process power flow. One of the main research challenges in ESSs is the identification of battery models that reach a balance between accuracy and ease of implementation in real control systems. Such models are often used in online algorithms for diagnostics and estimation of State of Charge/Health (SOC/SOH) and play a pivotal role in understanding and predicting the behavior of ESSs at short, medium, and long timescales. Furthermore, battery models are fundamental to devise suitable control systems for BMSs and power converters to ensure adequate ESS performance in terms of efficiency, autonomy, reliability, and safety.

This special session is aimed at presenting the latest advances and developments in ESS technologies of different kind (batteries, supercapacitors, hydrogen storage, flywheels, etc.) with particular reference to advanced modeling, accurate simulation, high-performance power electronic converters, high-performance linear and nonlinear control systems, accurate SOC/SOH estimation methods, and advanced ESS diagnostics.

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Topics of Interest

  • Advanced electrical and thermal models for batteries, supercapacitors, and ESSs and related state estimation and parameter identification techniques

  • Aging prediction for batteries based on data-driven models or physical electrochemical models

  • Battery Management Systems (BMS)

  • High-performance power electronic converters for ESSs

  • Advanced control techniques for BMSs and power converters to ensure high-performance ESS operation

  • Hardware in the Loop simulation and emulation of ESSs

  • Hybrid generation/storage and Long Duration Energy Storage (LDES) systems

  • Supercapacitor and hybrid supercapacitor modeling

  • Electrolyzers supply and control, and hydrogen storage technologies

  • Applications of flywheel ESSs

  • Advanced algorithms and sensors for diagnostics and SOC/SOH estimation

  • Electrochemical impedance spectroscopy for batteries and ESSs.​

SPECIAL SESSION 2 (SS2)

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PERFORMANCE, AGEING, AND DIAGNOSTICS OF HYDROGEN SYSTEMS

 

Co-Chairs

 

Theme

Hydrogen production and utilization play a key role among tomorrow’s sustainable energy solutions, actively contributing to the transition toward low-carbon energy systems.

This session focuses on the performance, diagnostics, and ageing of hydrogen systems, encompassing the entire powertrain chain, from hydrogen production and storage to its conversion into mechanical or electrical energy. A deep understanding of the behavior, degradation mechanisms, and efficiency of the various hydrogen components (fuel cells, electrolyzers, storage materials, and hybrid propulsion systems) is essential to ensure the durability, safety, and competitiveness of these technologies.

We welcome contributions that explore both experimental and modeling approaches for system diagnostics, lifetime prediction, and performance optimization under real operating conditions. By bridging fundamental studies and applied research, this session aims to provide a comprehensive perspective on how hydrogen technologies can meet the reliability and durability requirements of future energy systems.

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Topics of Interest

  • Hydrogen systems (fuel cells, electrolyzers, storage materials, etc.)

  • Modeling and simulation of hydrogen systems 

  • Ageing mechanisms and durability of the components

  • Diagnostic tools and fault detection

  • Influence of auxiliaries on performance and ageing

  • Integration of hydrogen technologies

SPECIAL SESSION 3 (SS3)

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AI-DRIVEN METHODS AND SOLUTIONS FOR INTELLIGENT ENERGY SYSTEMS 

 

Co-Chairs

 

Theme

The accelerating digitalization and decentralization of modern power systems are reshaping how electricity networks are planned, operated, and optimized. Artificial Intelligence (AI) has emerged as a transformative enabler, driving new paradigms for achieving efficiency, resilience, and sustainability in energy systems.

This special session brings together cutting-edge research and practical innovations that leverage AI, data analytics, and machine learning to enable the next generation of intelligent power and energy systems. Contributions are invited that span from algorithmic developments to real-world deployments, addressing the technical, operational, and economic challenges of modern electricity networks.

Recent advances in deep learning, reinforcement learning, and physics-informed, data-driven modeling enable predictive maintenance, adaptive control, state estimation, and self-healing capabilities. AI-based optimization and decision-making are also accelerating the secure and efficient integration of distributed energy resources (DERs), electric mobility, and active consumer participation.

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Topics of Interest

  • AI and machine learning for network optimization, control, and forecasting

  • Deep learning and hybrid models for DER and renewable integration

  • AI for resilience, restoration, and self-healing distribution grids

  • Data-enhanced state estimation and anomaly detection

  • Transactive energy systems and intelligent digital markets

  • Digital twins and edge AI for real-time monitoring and operation

  • AI for microgrids, virtual power plants, and energy communities

  • Multi-energy system management through AI-based coordination

  • Integration of electric mobility and demand response via machine learning

  • Explainable, trustworthy, and physics-informed AI for power distribution

SPECIAL SESSION 4 (SS4)

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DESIGN, CONTROL, AND FAULT DETECTION OF POWER CONVERTERS FOR ENERGY STORAGE AND EV CHARGING SYSTEMS

 

Co-Chairs

 

Theme

Electric storage devices, like batteries, supercapacitors, and electric vehicles, are usually connected to the grid for cogeneration or energy conservation for future use. This connection is made through power electronics interfaces that should guarantee high stability, voltage regulation, power flow control, and low electromagnetic emission, along with high power density, low cost, and high reliability. To increase the power density, passive devices that are considered the bulkiest components in these systems should be reduced or avoided. This can be achieved by considering multilevel topologies that would comply with power quality requirements without the need for passive filters. This session is dedicated to the various solutions adopted for high quality energy management at storage or EV charging levels. More specifically, it will present advanced power electronics topologies used for power quality enhancement in such applications. Model-based or intelligent control algorithms ensuring a compliance with grid requirements, especially regarding power quality and V2G connectivity, and EV-related standards are also considered as major topics in this session. In addition, fault detection techniques dedicated to the diagnosis of power converters for electric vehicles and energy storage devices are also covered. 

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Topics of Interest

  • Multilevel converters in grid-connected storage devices

  • Fuel cells for EV drives

  • Battery charging systems

  • PV-assisted charging systems

  • Power quality in V2G systems

  • Model-based control design

  • Artificial intelligence-based control

  • Energy management in V2G systems

  • Open-winding motor drives

  • Current and voltage signature-based fault diagnosis methods for chargers

  • AI-based fault detection techniques for EV and battery charging systems  

... and more Special Sessions to come!

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