
PhD Student in Energetica , 37th cycle (2021-2024)
Department of Energy (DENERG)
Profile
PhD
Tutors
Awards and Honors
- 2021 Master Thesis Award on New Challenges for Energy and Industry - IEEE Italy Section & ABB (2021)
- Certificate of attendance for the Conferences SenSys 2022 and BuildSys 2022 (2022)
- Certificate of attendance for the 17th Conference on Sustainable Development of Energy, Water and Environment Systems (SDEWES 2022) (2022)
Teaching
Teachings
Bachelor of Science
- Fisica dell'edificio e climatizzazione. A.A. 2022/23, INGEGNERIA ENERGETICA. Collaboratore del corso
- Fisica dell'edificio e climatizzazione. A.A. 2021/22, INGEGNERIA ENERGETICA. Collaboratore del corso
Publications
PoliTO co-authors
Latest publications View all publications in Porto@Iris
- Silvestri, Alberto; Coraci, Davide; Wu, Duan; Borkowski, Esther; Schlueter, Arno (2023)
Comparison of two deep reinforcement learning algorithms towards an optimal policy for smart building thermal control. In: CISBAT 2023, Losanna (CHE), September 2023
Contributo in Atti di Convegno (Proceeding) - Coraci, D.; Brandi, S.; Capozzoli, A. (2023)
Effective pre-training of a deep reinforcement learning agent by means of long short-term memory models for thermal energy management in buildings. In: ENERGY CONVERSION AND MANAGEMENT, vol. 291. ISSN 0196-8904
Contributo su Rivista - Coraci, Davide; Brandi, Silvio; Hong, Tianzhen; Capozzoli, Alfonso (2023)
Online transfer learning strategy for enhancing the scalability and deployment of deep reinforcement learning control in smart buildings. In: APPLIED ENERGY, vol. 333. ISSN 0306-2619
Contributo su Rivista - Brandi, S.; Coraci, D.; Borello, D.; Capozzoli, A. (2022)
Energy Management of a Residential Heating System Through Deep Reinforcement Learning. In: 13th KES International Conference on Sustainability and Energy in Buildings, SEB 2021, 2021, pp. 329-339. ISSN 2190-3018. ISBN: 978-981-16-6268-3
Contributo in Atti di Convegno (Proceeding) - Deltetto, D.; Coraci, D.; Pinto, G.; Piscitelli, M. S.; Capozzoli, A. (2021)
Exploring the potentialities of deep reinforcement learning for incentive-based demand response in a cluster of small commercial buildings. In: ENERGIES, vol. 14. ISSN 1996-1073
Contributo su Rivista