Contact information
| Position | Research Scientist |
| Phone | +39 0916809822 |
| Email | |
| Office | INM Palermo |
| Address | Via Ugo La Malfa 153 Palermo, Italy |
| Research profiles | Google Scholar | Scopus | ORCID | Publons | CNR People |
| Webpage | www.giuseppelatona.com |
Short biography
| Giuseppe La Tona is a Tenured Researcher at the Institute of Marine Engineering (INM), Italian National Research Council (CNR), in Palermo, Italy. His research focuses on optimization and machine learning for energy management and time-series forecasting, with applications to smart buildings, smart vehicles, and microgrids. He has authored over 40 scientific publications and contributes to the community as reviewer, guest editor, and member of program committees of international conferences. |
Research interests
| Energy Management; optimization algorithms; machine learning; time series forecasting. |
Research topics/groups
| Smart technologies for sustainable and efficient energy conversion and management |
Selected projects
| PRIN HEROGRIDS |
| Giuseppe La Tona is the unit coordinator for INM for the HEROGRIDS project, whose P.I. is prof. Mattavelli of Padua University and which other units are the University of Salerno and the University of Cassino. The main objective of the project HEROGRIDS is the energy efficiency optimization by means of a comprehensive design and control approach of smart nanogrids, such as those existing in future commercial, residential and industrial buildings. This is obtained by coordinating and optimizing system design at all hierarchical levels considering, from top to bottom. Project duration: 26/01/2020 – 27/1/2024 |
| TecBIA – Tecnologie ad alta Efficienza per la Sostenibilità Energetica ed ambientale On-board |
| Research contract signed with Fincantieri S.p.A. under a project funded by MISE, PON I&C 2014-2020, with decree D.M. 01/06/2016. Topic: developing innovative technologies to generate and manage electrical power onboard Project duration: 31/10/2018 – 30/10/2022 Role: participant |
| Leadership Tecnologica – Generazione Elettrica Innovativa (GEI) |
| Research contract signed with Fincantieri S.p.A. under a project funded by MIT with decree n. 196 / 10.06.2015. Topic: developing innovative technologies for electrical generation onboard Project duration: from 01/01/2017 to 31/12/2018 Role: participant |
| BAITAH – Methodology and Instruments of Building Automation and Information Technology for pervasive models of treatment and Aids for domestic Healthcare |
| PON R&C project for domestic support to non completely auto-sufficient people throughAmbient Assisted Living (AAL). Activity: Development of vocal and graphical interfaces for human-robot interaction forAAL for peoples with special needs. Integration of iterfaces with smart supervision system and with domotic devices. Role: participant |
| CNR per il Mezzogiorno |
| Development of Energy Management System (EMS) in smart buildings connected to the electrical grid and equipped with electrical storage systems and renewable generators. Activity: Optimization techniques for scheduling of power flows between electrical devices of the system. Implementation of EMS on low-cost embedded devices. Role: participant |
Selected publications
- M. Luna, G. La Tona, A. Accetta, M. Pucci, A. Pietra, and M. C. Di Piazza, “Optimal Management of Battery and Fuel Cell-Based Decentralized Generation in DC Shipboard Microgrids,” Energies, vol. 16, no. 4, p. 1682, Feb. 2023, doi: 10.3390/en16041682.
- G. La Tona, M. Luna, and M. C. Di Piazza, “A Multi-Objective Optimization-based EMS for Residential Microgrids Considering Battery SoH,” in IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society, Oct. 2022, pp. 1–6. doi: 10.1109/IECON49645.2022.9968553.
- G. La Tona, M. C. Di Piazza, and M. Luna, “Effect of Daily Forecasting Frequency on Rolling-Horizon-Based EMS Reducing Electrical Demand Uncertainty in Microgrids,” Energies, vol. 14, no. 6, p. 1598, Mar. 2021.
- A. Di Piazza, M. C. Di Piazza, G. La Tona, and M. Luna, “An artificial neural network-based forecasting model of energy-related time series for electrical grid management,” Mathematics and Computers in Simulation, vol. 184, pp. 294–305, Jun. 2021.
- G. La Tona, M. Luna, M. C. Di Piazza, M. Pucci, and A. Accetta, “Development of a High-Performance, FPGA-Based Virtual Anemometer for Model-Based MPPT of Wind Generators,” Electronics, vol. 9, no. 1, p. 83, Jan. 2020.
- M. Luna, G. La Tona, A. Accetta, M. Pucci, and M. C. Di Piazza, “An Evolutionary EMI Filter Design Approach Based on In-Circuit Insertion Loss and Optimization of Power Density,” Energies, vol. 13, no. 8, p. 1957, Apr. 2020.
- G. La Tona, M. Luna, A. Di Piazza, and M. C. Di Piazza, “Towards the Real-World Deployment of a Smart Home EMS: A DP Implementation on the Raspberry Pi,” Applied Sciences, vol. 9, no. 10, p. 2120, May 2019.
- Di Piazza, M. C. et al. (2019) ‘Improving Grid Integration of Hybrid PV-Storage Systems Through a Suitable Energy Management Strategy’, IEEE Transactions on Industry Applications. IEEE, 55(1), pp. 60–68. doi: 10.1109/TIA.2018.2870348.
- La Tona, G. et al. (2018) ‘Modular multimodal user interface for distributed ambient intelligence architectures’, Internet Technology Letters, 1(2), p. e23. doi: 10.1002/itl2.23.
- Petrone, G. et al. (2018) ‘Online Identification of Photovoltaic Source Parameters by Using a Genetic Algorithm’, Applied Sciences, 8(1), p. 9. doi: 10.3390/app8010009.
- Di Piazza, M. C. et al. (2017) ‘A two-stage Energy Management System for smart buildings reducing the impact of demand uncertainty’, Energy and Buildings, 139, pp. 1–9. doi: 10.1016/j.enbuild.2017.01.003.
- Dindo, H. et al. (2013) ‘An architecture for observational learning and decision making based on internal models’, Biologically Inspired Cognitive Architectures, 5, pp. 52–63. doi: 10.1016/j.bica.2013.05.007.