Hierarchical predictive control and physics-inspired learning in multi-energy networks

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• Alessio La Bella, Politecnico di Milano
• Wednesday 22 May 2024, 15:00-16:00
• 611.

If you have a question about this talk, please contact Giordano Scarciotti.

Abstract: The synergetic operation of multiple energy carriers (e.g., electricity, heating, hydrogen) is recognized among the key solutions to increase the efficiency of the energy system and to foster the integration of renewable sources. However, the optimal and integrated control of multi-energy networks lead to additional issues, given their large-scale dimension, modelling complexity, diverse involved timescales, and the presence of multiple actors. This talk will firstly present a hierarchical predictive control approach which, relying on reduced energetic models and game-theoretical methods, is capable of effectively coordinating large-scale multi-energy networks. A physics-inspired learning method for energy networks will be also presented, particularly efficient to develop control-oriented models from data with enhanced accuracy and reduced complexity. Finally, future directions on the presented results will be discussed.

Biography: Alessio La Bella received the M.Sc. in Automation Engineering cum laude from Politecnico di Milano, Italy, in 2015. In 2016, he received the Alta Scuola Politecnica Diploma and the M.Sc. in Mechatronics Engineering cum laude at Politecnico di Torino, Italy. He received the Ph.D. Degree cum laude in Information Technology at Politecnico di Milano in 2020. From 2020 to 2022, he was Research Engineer at Ricerca sul Sistema Energetico – RSE SpA, Italy, designing and implementing predictive control systems for large-scale energy plants in collaboration with industrial companies and energy utilities. In 2022, he joined the Systems and Control group of Politecnico di Milano as Assistant Professor. He was visiting student at the KTH Royal Institute of Technology, Sweden, in 2014, he was visiting researcher at the École Polytechnique Fédérale de Lausanne, Switzerland, in 2018, and he was visiting professor at the Delft University of Technology in 2024. His research interests concern the theory and design of predictive, multi-agent and learning-based control systems, with particular emphasis on practical challenges arising from the upcoming energy transition. He was recipient of the Dimitris N. Chorafas Prize for his PhD Thesis in 2020.

This talk is part of the Control and Power Seminars series.

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• 611
• Andrea Picciau's list
• Control and Power Seminars

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