Prof Fabiano Pallonetto

Biography

I have a wide experience in the energy, IT and transport sectors working as an entrepreneur, data scientist and researcher across different industries and disciplines. My academic background in Computer Science and Engineering and my industry experience in Energy, Sustainable Mobility, Data Analytics, Control Algorithms and Optimisation makes me a pivotal asset for research based and commercial data centric projects. My goal is bridging academic research to industrial needs applying my multidisciplinary industry and entrepreneurship experience to build solutions and solve technical challenges for the deployment and integration of the smart grid and its associated carbon footprint reduction and promoting Sustainable Development Goals.

Research Projects

Title Role Description Start date End date Amount
Next Generation Energy Systems Funded Investigator By 2027, NexSys will have identified credible, just, and accelerated pathways for a net zero energy system, and have developed technologies and talent needed for the energy transition. In NexSys, we seek to collaborate as a multi-disciplinary team to provide technology development and evidence-based insights to the energy transition, through multi-dimensional research and outreach that is focused on equity for energy citizens and practical solutions for industry. 01/01/2022 01/12/2027
FLOW - Flexible Energy Systems by leveraging the optimal integration of EVs and their users Principal Investigator and WP Leader FLOW tests, validates and enhances user-centric V2X smart charging solutions and their orchestrated integration into energy grids that deliver flexibility assets to favour additional penetration of renewables and alleviate energy grid challenges. 01/07/2022 01/07/2026
RES4CITY - Renewable Energies System for Cities Coordinator A carbon-neutral European Union by 2050 is an ambitious target that presents technical and societal challenges. While technical research is advancing rapidly to reach a net-zero target, the overall skillsets of the working force are lagging behind in understanding, employing and mastering sustainable technologies for the business models. Therefore, the RES4City project envisions a codesigned educational framework for upskilling the workforce to integrate, influence and combine the current sustainability best practices for renewable energies and fuel technologies. 01/10/2022 01/10/2025

Peer Reviewed Journal

Year Publication
2024 Pierce, S.; Pallonetto, F.; De Donatis, L.; De Rosa, M. (2024) 'District energy modelling for decarbonisation strategies development—The case of a University campus'. Energy Reports, 11 . [Link] [DOI] [Full-Text]
2024 Alam, W.; Tahir, M.; Hussain, S.; Gul, S.; Hayat, M.; Irshad, R.R.; Pallonetto, F. (2024) 'Unveiling the Potential Pattern Representation of RNA 5-Methyluridine Modification Sites through a Novel Feature Fusion Model Leveraging Convolutional Neural Network and Tetranucleotide Composition'. Ieee Access, . [Link] [DOI]
2023 Bampoulas, A.; Pallonetto, F.; Mangina, E.; Finn, D.P. (2023) 'A Bayesian deep-learning framework for assessing the energy flexibility of residential buildings with multicomponent energy systems'. Applied Energy, 348 . [Link] [DOI]
2023 De Rosa, M.; Bianco, V.; Barth, H.; Pereira da Silva, P.; Vargas Salgado, C.; Pallonetto, F. (2023) 'Technologies and Strategies to Support Energy Transition in Urban Building and Transportation Sectors'. Energies, 16 . [Link] [DOI]
2023 Hussain, S.; Irshad, R.R.; Pallonetto, F.; Hussain, I.; Hussain, Z.; Tahir, M.; Abimannan, S.; Shukla, S.; Yousif, A.; Kim, Y.S.; El-Sayed, H. (2023) 'Hybrid coordination scheme based on fuzzy inference mechanism for residential charging of electric vehicles'. Applied Energy, 352 . [Link] [DOI]
2023 Li, H.; Johra, H.; de Andrade Pereira, F.; Hong, T.; Le Dréau, J.; Maturo, A.; Wei, M.; Liu, Y.; Saberi-Derakhtenjani, A.; Nagy, Z.; Marszal-Pomianowska, A.; Finn, D.; Miyata, S.; Kaspar, K.; Nweye, K.; O'Neill, Z.; Pallonetto, F.; Dong, B. (2023) 'Data-driven key performance indicators and datasets for building energy flexibility: A review and perspectives'. Applied Energy, 343 . [Link] [DOI]
2023 Kumar, P.; Vrontis, D.; Pallonetto, F. (2023) 'Cognitive engagement with AI-enabled technologies and value creation in healthcare'. Journal of Consumer Behaviour, . [Link] [DOI]
2023 Hussain, S.; Irshad, R.R.; Pallonetto, F.; Jan, Q.; Shukla, S.; Thakur, S.; Breslin, J.G.; Marzband, M.; Kim, Y.S.; Rathore, M.A.; El-Sayed, H. (2023) 'Enhancing the Efficiency of Electric Vehicles Charging Stations Based on Novel Fuzzy Integer Linear Programming'. IEEE Transactions on Intelligent Transportation Systems, . [Link] [DOI]
2022 Kiviluoma J.; Pallonetto F.; Marin M.; Savolainen P.T.; Soininen A.; Vennström P.; Rinne E.; Huang J.; Kouveliotis-Lysikatos I.; Ihlemann M.; Delarue E.; O'Dwyer C.; O'Donnel T.; Amelin M.; Söder L.; Dillon J. (2022) 'Spine Toolbox: A flexible open-source workflow management system with scenario and data management'. Softwarex, 17 . [DOI] [Full-Text]
2022 De Rosa M.; Gainsford K.; Pallonetto F.; Finn D.P. (2022) 'Diversification, concentration and renewability of the energy supply in the European Union'. Energy, 253 . [DOI]
2022 Bampoulas A.; Pallonetto F.; Mangina E.; Finn D.P. (2022) 'An ensemble learning-based framework for assessing the energy flexibility of residential buildings with multicomponent energy systems'. Applied Energy, 315 . [DOI]
2022 Pallonetto F.; Jin C.; Mangina E. (2022) 'Forecast electricity demand in commercial building with machine learning models to enable demand response programs'. Energy And Ai, 7 . [DOI] [Full-Text]
2021 Bampoulas A.; Saffari M.; Pallonetto F.; Mangina E.; Finn D.P. (2021) 'A fundamental unified framework to quantify and characterise energy flexibility of residential buildings with multiple electrical and thermal energy systems'. Applied Energy, 282 . [DOI] [Full-Text]
2021 Pallonetto F.; De Rosa M.; Finn D.P. (2021) 'Impact of intelligent control algorithms on demand response flexibility and thermal comfort in a smart grid ready residential building'. Smart Energy, 2 . [DOI] [Full-Text]
2020 Pallonetto F.; Galvani M.; Torti A.; Vantini S. (2020) 'A framework for analysis and expansion of public charging infrastructure under fast penetration of electric vehicles'. World Electric Vehicle Journal, 11 (1). [DOI] [Full-Text]
2020 Pallonetto F.; De Rosa M.; D'Ettorre F.; Finn D.P. (2020) 'On the assessment and control optimisation of demand response programs in residential buildings'. Renewable and Sustainable Energy Reviews, 127 . [DOI] [Full-Text]
2020 Pallonetto F.; De Rosa M.; Finn D.P. (2020) 'Environmental and economic benefits of building retrofit measures for the residential sector by utilizing sensor data and advanced calibrated models'. Advances in Building Energy Research, . [DOI] [Full-Text]
2019 Pallonetto F.; Mangina E.; Milano F.; Finn D. (2019) 'SimApi, a smartgrid co-simulation software platform for benchmarking building control algorithms'. Softwarex, 9 :271-281. [DOI] [Full-Text]
2019 Pallonetto F.; De Rosa M.; Milano F.; Finn D. (2019) 'Demand response algorithms for smart-grid ready residential buildings using machine learning models'. Applied Energy, 239 :1265-1282. [DOI] [Full-Text]
2018 Egan J.; Finn D.; Deogene Soares P.; Rocha Baumann V.; Aghamolaei R.; Beagon P.; Neu O.; Pallonetto F.; O'Donnell J. (2018) 'Definition of a useful minimal-set of accurately-specified input data for Building Energy Performance Simulation'. Energy and Buildings, 165 :172-183. [DOI] [Full-Text]
2018 de Oliveira da Costa P.; Mauceri S.; Carroll P.; Pallonetto F. (2018) 'A Genetic Algorithm for a Green Vehicle Routing Problem'. Electronic Notes in Discrete Mathematics, 64 :65-74. [DOI] [Full-Text]
2016 Pallonetto, F; Oxizidis, S; Milano, F; Finn, D (2016) 'The effect of time-of-use tariffs on the demand response flexibility of an all-electric smart-grid-ready dwelling'. Energy and Buildings, 128 :56-67. [DOI] [Full-Text]

Book Chapter

Year Publication
2023 Pallonetto, Fabiano (2023) 'Towards a More Sustainable Mobility' In: Handbook of Computational Social Science for Policy. : Springer International Publishing.
2022 Fabiano Pallonetto (2022) 'Advanced Energy Management Systems and Demand-Side Measures for Buildings towards the Decarbonisation of Our Society' In: Transitioning to Affordable and Clean Energy. Switzerland : MDPI. [Link] https://doi.org/10.3390/books978-3-03897-777-3-6

Conference Publication

Year Publication
2022 Meer A.V.D.; Rigoni V.; Pallonetto F.; Keane A. (2022) 2022 11th International Conference on Power Science and Engineering, ICPSE 2022 Impact Analysis of Electric Vehicle Charging and Demand Response Potential on a University Campus [DOI]
2021 Adamantios Bampoulas, Fabiano Pallonetto, Eleni Mangina, Donal P. Finn (2021) Building Simulation 2021 Conference A machine learning-based methodology for harnessing the energy flexibility potential of residential buildings Bruges, Belgium, 01/09/2021- 03/09/2021 [Link]
2021 Susan Pierce, Lorenzo De Donatis, Fabiano Pallonetto, Giovanni Tardioli (2021) Building Simulation 2021 Conference Use of district energy modelling and stakeholder engagement in developing decarbonisation strategies Bruges, Belgium, 01/09/2021- 03/09/2021 [Link]
2019 Bampoulas A.; Saffari M.; Pallonetto F.; Mangina E.; Finn D.P. (2019) IEEE 5th World Forum on Internet of Things, WF-IoT 2019 - Conference Proceedings Self-Learning Control Algorithms for Energy Systems Integration in the Residential Building Sector [DOI] [Full-Text]
2014 Pallonetto F.; Mangina E.; Finn D.; Wang F.; Wang A. (2014) BuildSys 2014 - Proceedings of the 1st ACM Conference on Embedded Systems for Energy-Efficient Buildings A RestFUL API to control a energy plus smart grid-ready residential building [DOI] [Full-Text]
2022 Pierce, S.; De Donatis, L.; Pallonetto, F.; Tardioli, G. (2022) Building Simulation Conference Proceedings Use of District Energy Modelling and Stakeholder Engagement in Developing Decarbonisation Strategies [Link] [DOI]
2022 De Lira, V.M.; Pallonetto, F.; Gabrielli, L.; Renso, C. (2022) Predicting Vehicles Parking Behaviour for EV Recharge Optimization [Link]
2019 (2019) 2019 IEEE 5th World Forum on Internet of Things (WF-IoT) Self-Learning Control Algorithms for Energy Systems Integration in the Residential Building Sector [DOI]
2013 Neu, O.; Oxizidis, S.; Flynn, D.; Pallonetto, F.; Finn, D.; (2013) Proceedings of BS 2013: 13th Conference of the International Building Performance Simulation Association High resolution space - Time data: Methodology for residential building simulation modelling
2013 Pallonetto, F.; Oxizidis, S.; Duignan, R.; Neu, O.; Finn, D.; (2013) Proceedings of BS 2013: 13th Conference of the International Building Performance Simulation Association Demand response optimisation of all-electric residential buildings in a dynamic grid environment: Irish case study
2023 Bampoulas, A.; Cheng, Y.; Pallonetto, F.; Finn, D.P.; Mangina, E. (2023) Building Simulation Conference Proceedings A Bayesian deep learning methodology with uncertainty quantification for harnessing the residential building heating system energy flexibility [Link] [DOI]

Conference Contribution

Year Publication
2021 Fabiano Pallonetto (2021) ICPEA IEEE The 4th International Conference on Power and Energy Applications Pusan, South Korea, .
Certain data included herein are derived from the © Web of Science (2024) of Clarivate. All rights reserved.

Current Students

Student Name Degree Supervision
MR B. MOHSENI GHARYEHSAFA RESEARCH PH.D. (10)