Numerical modeling and optimization of energy systems

Description

The activity focuses on the modeling and optimization of complex energy systems, with particular emphasis on Renewable Energy Communities (RECs) and energy storage systems such as batteries and hydrogen. Using advanced numerical simulation techniques, the research group analyses the energy performance of multi-vector systems to maximise energy efficiency, reduce costs, and minimise environmental impact. Research activities include the development of algorithms for optimal energy management, the integration of renewable energy sources, and the improvement of grid flexibility through the coordination of various energy storage and generation systems.

Publications

• Integration of battery and hydrogen energy storage systems with small-scale hydropower plants in off-grid local energy communities, Lin J, Rossi M, Monforti Ferrario A, Alberizzi J.C, Renzi M, Comodi G, 2023, Energy Conversion and Management, Volume 286, Articolo 117019, ELSEVIER, doi: 10.1016/j.enconman.2023.117019.
• Environmental constrained medium-term energy planning: The case study of an Italian university campus as a multi-carrier local energy community, Jin L, Rossi M, Ciabattoni L, Di Somma M, Graditi G, Comodi G, 2023, Energy Conversion and Management, Volume 278, Articolo 116701, ELSEVIER, doi: 10.1016/j.enconman.2023.116701.
• Li-ion battery aging model robustness: An analysis using univariate and multivariate techniques, Marchegiani E, Ferracuti F, Monteriù A, Jin L, Rossi M, Comodi G, Ciabattoni L, 2023, Journal of Energy Storage, Volume 72, Articolo 108591, ELSEVIER, doi: 10.1016/j.est.2023.108591.
• A novel approach for multi-stage investment decisions and dynamic variations in medium-term energy planning for multi-energy carriers community, Pizzuti A, Jin L, Rossi M, Marinelli F, Comodi G, 2024, Applied Energy, Volume 353, Articolo 122177, ELSEVIER, doi: 10.1016/j.apenergy.2023.122177.
• Designing hybrid energy storage systems for steady green hydrogen production in residential areas: A GIS-based framework, Jin L, Rossi M, Monforti Ferrario A, Mennilli F, Comodi G, 2025, Applied Energy, Volume 389, Articolo 125765, doi: 10.1016/j.apenergy.2025.125765.

Staff

Prof. Gabriele Comodi
Tel. +39 071 220 4761
E-mail: g.comodi@staff.univpm.it

Prof. Flavio Caresana
Tel. +39 071 220 4765
E-mail: f.caresana@staff.univpm.it

Prof. Leonardo Pelagalli
Tel. +39 071 220 4774
E-mail: l.pelagalli@staff.univpm.it

Ing. Mosè Rossi, PhD
E-mail: mose.rossi@staff.univpm.it