Roberto Quadrini
Roberto Quadrini/
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Academic
Academic
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Academic

Personal

Data

  • Surname, Name: Quadrini, Roberto
  • Date of birth: 05/10/1968
  • Personal address: Via Don Gaetano Galli, 25 - 20852 Villasanta (MB)
  • ORCID number: 0000-0002-2551-9672
  • private E-mail address: roberto.quadrini@gmail.com

Education

  • Degrees: Engineer
  • Date: 1997
  • Title of the diploma: BACHELOR OF ENGINEERING SOFTWARE AND AUTOMATION, BENG
  • Name of the educational institution: “La Sapienza University”
  • Locality, Country: Rome, Italy

Additional relevant training 

  • Date: 1989
  • Title: Classical High School
  • Name of institution: Istituto San Bernardo
  • Locality, Country: Casamari (FR), Italy

Present and past positions

  • Date (from – to): 04/11/2010 - Present
  • Position – employment rate: Chief Scientific Officer
  • Name of the institution: Tecnalogic srl (R&D Company)
  • Locality, Country: Vimercate, Italy
 
  • Date (from – to): 14/02/2013 - 31/12/2013
  • Position – employment rate: Energy Consultant
  • Name of the institution: Reply S.p.A
  • Locality, Country: Milano, Italy
 
  • Date (from – to): 07/07/2009 - 31/10/2010
  • Position – employment rate: Chief Scientific Officer
  • Name of the institution: Digitalwatt (R&D Company)
  • Locality, Country: Besana, Italy
 
  • Date (from – to): 09/08/2005 - 30/09/2007
  • Position – employment rate: Energy Consultant
  • Name of the institution: HP
  • Locality, Country: Cernusco S/N Naviglio, Italy
 
  • Date (from – to): 16/09/1999 - 08/08/2005
  • Position – employment rate: Software Architect
  • Name of the institution: HP
  • Locality, Country: Cernusco S/N Naviglio, Italy
 
  • Date (from – to): 01/09/1997 - 31/08/1999
  • Position – employment rate: ICT System Administrator
  • Name of the institution: Spazio ZeroUno S.p.A.
  • Locality, Country: Vimodrone, Italy

Honors and awards

  • NegaWh EXchange, Balancing demand-response platform for an efficient, reasonably-priced and sustainable electricity market – SME instrument phase 1, Grant agreement ID: 827753
  • Winewise, Next Generation Architecture for Smart Wine production. Innovation Awards 2012 at Cisco Live. Category: “Most Innovative Business Impacting Network of the Year” nella categoria Food and Beverage

Language skills

  • English: C1
 

Research & Development

Self-evaluation

Breakthroughs in research and development for the energy and agrifood sectors, utilizing advanced models and tools (Deep Learning, Machine Learning, Artificial Intelligence), have led to the creation of the General PSB Methodology (Profiling, Scheduling, Balancing).
This methodology marks a significant leap forward in modern electrical grid management, particularly given the increasing presence of renewable energy sources and highly variable demand. The PSB Methodology surpasses the current state-of-the-art in electricity consumption forecasting by balancing the electrical grid through aggregated consumption, dynamically modulated by advanced self-learning mathematical models. Its effectiveness is built upon three core functions:
  • Profiling: This function acquires hourly electricity consumption data, mapping the characteristic energy profiles of individual consumption units, across both industrial and commercial sectors. This phase enables the correlation of consumption with operational or environmental variables, establishing a precise and detailed database for analysis and management.
  • Scheduling: Through dynamic and centralized control, this optimizes electrical loads by programming corrective interventions on consumption. This adapts demand to the network's needs and to production and market constraints.
  • Balancing: This maintains overall consumption within pre-established thresholds by implementing targeted programming on secondary loads. This allows for real-time modulation of aggregated consumption to meet grid balancing requirements, reducing the risks of over- or under-consumption and contributing to the stability of the electrical system.
The versatility of the General PSB Methodology is further demonstrated by its successful application in the agrifood sector, where specific mathematical models have been developed for that context.

Research outputs

[1] Invention Patents
  • R.Quadrini, “A method and a device for profiling and scheduling electricity consumption” Nov 05, 2015. Country[IT] Patent Nº 0001419107.
  • R.Quadrini, “A method and a device for balancing electric consumption” Nov 05, 2015. Country[IT] Patent Nº 0001419109.
  • R.Quadrini, “A method for profiling and scheduling production and feed-in of electrical energy into a power grid” May 14, 2016. Country[IT] Patent Nº 0001421371.
  • R.Quadrini, “A method and a device for balancing electric consumption” Jun 5, 2018. Country[US] Patent Nº US 9,991,705 B2.
  • R.Quadrini, “A method and a device for balancing electric consumption” (divisional patent) Aug 6, 2019. Country[US] Patent Nº US 10,374,425 B2.
  • R.Quadrini, “A method and a device for balancing electric consumption” Sep 12, 2018. Country[RU]  Patent Nº RU 2,666,751 C2.
  • R.Quadrini, “A method and a device for balancing electric consumption” (divisional patent) Sep 2, 2021. Country[RU]  Patent Nº RU 2,754,484 C2.
  • R.Quadrini, “A method and a device for balancing electric consumption” Jun 12, 2019. Country [IT, AT, BE, FR, DE, GB, IL, MC, NL, SI, ES, CH] Patent Nº EP 3,028,361 B1
 
[2] Utility Model Patents
  • R.Quadrini, “System monitoring, control of carbon emissions from electricity load connected to it directly” Apr 08, 2013. Country[IT] Patent Nº 0000275451.
 
[3] Oratrios
  • Advanced IT service for the identification and management of the characteristic energy profile through exclusive Profiling, Scheduling and Balancing algorithms.
 
[4] Agrifood Traceability
  • Technological solution for the traceability of the entire life cycle of an agrifood product through sensors and digitization of knowledge bases specific for each sector.
 
[5] NegaWh EXchange
  • Balancing demand-response platform for an efficient, reasonably-priced and sustainable electricity market.

Publications

"Balancing Energy: Addressing the Impact of Renewable Energy in Italy through Skew Forecasting” - Annals of Operations Research, 2024
Abstract: In this study, we introduce a conservative model designed to accurately predict renewable energy generation while addressing fluctuations and imbalances in power supply. Our focus is on minimizing deficits caused by underestimating actual generation levels. By prioritizing a positively skewed distribution of deviations and aiming for them to cluster around zero, we achieve significant reductions in forecasting errors compared to established benchmarks. Utilizing hourly data from Terna in 2023, our model illustrates the effects of energy imbalances, which lead to financial losses, yet also highlights enhanced cost savings and significant reductions in CO2 emissions.
DOI: 10.1007/s10479-024-06256-2
Publisher: Springer Journals
Sharing paper via Springer Nature Sharedit

Scientific planning

Research planned for 2025 focuses on the creation of a mathematical engine that builds a neural network that virtualizes the power grid. This virtual network works by monitoring and regulating the total electricity consumption of many grouped users (so-called aggregate consumption). The mathematical engine, through AI agents present in each aggregate, learns the behavior of these users and, based on this knowledge, maps and proposes the optimal consumption schedule 15 minutes in advance (ex-ante).
Neural Grid transforms groups of industrial, commercial, and residential consumers into virtual power plants. These virtual power plants can participate in electricity markets by offering NegaWh, or consumption schedules planned in advance and adjusted in real time to contribute to balancing the electricity grid.
The mathematical engine uses various advanced algorithms from various fields, such as:
  • Optimization (identifying the best solutions),
  • Game theory (modeling interactions between different actors),
  • Renewable energy production forecasting, and more.

Research collaborations

[1] R&D Project
  • “Intelligent Power Distributor Unit Next generation of switched power distribution units (PDU)”
Output
  • PDU Prototype (HW+SW)
  • Patent: R.Quadrini, “System monitoring, control of carbon emissions from electricity load connected to it directly” Apr 08, 2013. Country[IT] Patent Nº 0000275451.
Role
  • Design and inventor of PDU system
Partner: Cisco System
 
[2] R&D Project
  • “Demand-Response Load Shaping Node Based”
Output
  • Invention Patents (R.Quadrini, “A method and a device for balancing electric consumption”)
Role
  • Design and inventor of Demand-Response Program Software
Pilot Site
  • IRCCS Istituto Clinico Humanitas Research Hospital (Milan)
Technology Partner
  • Reply
  • Cisco System
  • Innowatio Trading
 
[3] R&D Project
  • “WineWise Next Generation Architecture for Smart Wine Production”
Academic Partners
  • Università degli Studi di Napoli Federico II, Dipartimento di Agraria
  • Università degli Studi di Milano, Dipartimento di Scienze Agrarie e Ambientali - Produzione, Territorio, Agroenergia
Role
  • Inventor of the method of traceability to the origin of the wine product
Technology Partner
  • Cisco System
Site
  • Castel di Stefanago, Organic Winery, Località Stefanago 27040, Borgo Priolo (Pavia)
 
[4] Platform IT
  • “Power Trading and Management System”
Technology Partner
  • HP Hungary
  • Softeco Sismat
Role
  • Development of mathematical models based on ANNs
Academic Partner
  • BUDAPESTI MUSZAKI ES GAZDASAGTUDOMANYI EGYETEM (BME)
 
[5] Algorithms and AI Agent
  • “Algorithms for photovoltaic energy production for Regula AI Agent”
Site
  • Comunità Energetica Rinnovabile Monastero Valserena, monache cistercensi - Guardistallo (Pisa)
Role
  • Co-Autor of "Balancing Energy: Addressing the Impact of Renewable Energy in Italy through Skew Forecasting” - Annals of Operations Research, 2024
Academic Partner

Research funding and grants

  • Grant number: 827753
  • Project Title: Balancing demand-response platform for an efficient, reasonably-priced and sustainable electricity market
  • Institution: EU - Horizon 2020
  • Type project (competitive/non-competitive): competitive
  • Funding Agency: INDUSTRIAL LEADERSHIP - Innovation In SMEsProject Start
  • Project Start: 1 August 2018
  • Project End: 30 November 2018
  • You Role: Main Applicant/Principal Investigator
  • Project Manager / Project coordinator: YES
  • Global Granted Budget (CHF): 66.508
  • Own Budget (CHF) : 46.555

Research supervision and mentoring

[1]  R&D Project
  • “Intelligent Power Distributor Unit Next generation of switched power distribution units (PDU)”
Team
  • FTE: 105
  • n.5 (HW Designer, Firmware Designer, Software developer backend and front end
Role
  • Design and inventor of PDU system and Project Manager
 
[2]  R&D Project
  • “Demand-Response Load Shaping Node Based”
Team
  • FTE: 310
  • n.8 (Mathematicians, Engineering Software and Automation, Software Developers, HMI)
Role
  • Design and inventor of Demand-Response Program Software, Project Manager
Non-Academic Position Obtained
  • Eng. Stefano Bonomi, Smart Grids and Innovation Consultant CESI SpA
 
[3]  R&D Project
  • “WineWise Next Generation Architecture for Smart Wine Production”
Team
  • FTE: 220
  • n.6 (Biochemists, Agronomists, Oenologists, Electronic Engineers, Software Developers)
Role
  • Inventor of the method of traceability, Project Manager

Other scientific activities

Invited Speaker
  • “Invitation to discuss possible academic and professional cooperation for new Israeli energy market” Technion - Israel Institute of Technology (Andrew and Erna Viterbi Faculty of electrical Engineering) by Professor and Dean Nahum Shimkin, 18 July, 2018 - Haifa (Israel)
  • “Smart Environment and Energy”, Smart City Exhibition, 31 October, 2012 - Bologna
  • “The New Frontiers of Energy (Competitiveness Economic Development, “European Energy Efficiency Strategies", Platts 19-20 October, 2009 - Brussels
  • “Venice Declaration, The Third Industrial Revolution in Architecture”, The Foundation on Economic Trends (Jeremy Rifkin Office), 15 June, 2009 - Rome
  • International Energy Forum, 9-11 November, 2005 - Rimini
  • “IT and Energy Efficiency: a winning combination that increases competitiveness”, 2004-2008, Energy Efficiency Workshop, Impresa x Innovazione - Confindustria
 
Expert Evaluator
  • “Multivector Integrated Smart System and Intelligent for accelerating the energy transitiON” as Member of the commission of currency experts for the advancement of the POA 2021-2023 of ENEA - Mission Innovation. Ministry of the Environment and Energetic Safety (MASE), Sep 2022- Nov 2022; Milan
  • “Strengthening of the SiMTE platform (Energy Technology Monitoring System)” and “Models and tools to increase energy efficiency in the cycle of production, transport and distribution of electricity” as Member of the commission of currency experts for the advancement of the Three-Year Implementation Plan (PTR) 2019-2021 of ENEA. Final Report. Ministry of the Environment and Energetic Safety (MASE), Jul 2022- Oct 2022; Milan
  • “Application to the power grid of information technologies, IoT, P2P” as Member of the commission of currency experts for the advancement of the Three-Year Implementation Plan (PTR) 2019-2021 of RSE. Ministry of Ecological Transition (MiTE), Nov 2021- Feb 2022; Milan
  • “Multivector Integrated Smart System and Intelligent microgrids for accelerating the energy transitiON” as Member of the commission of expert evaluators of the Operational Activity Plan (POA) 2021-2023 relating to the MiTE-ENEA program agreement. (ENEA, CNR, RSE). Ministry of Ecological Transition (MiTE), Oct 2021- Nov 2021; Milan
 
Expert Contributor
  • “General PSB Methodology for introducing UCs in national, global and local ancillary service” request by Special Office for Euro-Unitary Regulation (STAFF) to submit to ARERA for contribute to the reform of the electricity market, specifically for the TIDE (Integrated Text on Electricity Dispatching), 10 March, 2023 - ARERA
 
Reviewer
  • Academia Green Energy

Teaching

Self-evaluation

In my role as Chief Scientific Officer, I developed a teaching model based on several key principles:
  • I promote active participation of all team members in every phase of the project, from implementation to communication and dissemination of results, fostering a shared sense of responsibility. I value the diverse scientific skills and personal qualities of each individual, enhancing motivation, cohesion, and collaboration while maintaining a strong focus on objectives.
  • I encourage interdisciplinary collaboration by integrating different competencies such as interface design, microelectronics, software development, and marketing through diverse activities that stimulate innovation. I foster open discussion and critical debate on every aspect of the project, involving all participants to drive continuous improvement.
  • I adopt lateral thinking, a creative and unconventional approach to problem-solving, successfully applied in the WineWise project, where we developed a platform to trace wine throughout its supply chain, adapting methodologies from the energy sector to agrifood.
  • I delegate autonomy and responsibility in managing individual tasks, instilling trust and stimulating critical thinking in each team member. Teaching is always oriented towards clear objectives and the use of problem-based situations for practical and targeted learning.
Finally, I promote scientific rigor based on the null hypothesis, encouraging a critical mindset and the collection of solid evidence before accepting any effect or significant relationship, thus ensuring reliability and rigor in research.

Supervision of thesis and mentoring

[1] Candidate: Ivan Cazzol
  • Title: “Renewable energy remote management and control system for powerline photovoltaic systems”
  • Year: 2007-2008
  • University: Università degli Studi di Milano
  • Faculty: Scienze Matematiche, Fisiche e Naturali
  • University Degree: Computer Science
  • Mentor: Roberto Quadrini
 
[2] Candidate: Luca Confalonieri
  • Title: “Creating an innovative enterprise located in the smart grid sector: the case of an energy consumption optimization project within the Campus University of Bergamo”
  • Year: 2010-2011
  • University: Università degli Studi di Bergamo
  • Faculty: Engineering
  • University Degree: Management Engineering
  • Mentor: Roberto Quadrini
 
[3] Candidate: Stefano Bonomi
  • Title: “Real-time scheduling system for managing energy imbalances in industrial loads for demand-response applications”
  • Year: 2012-2013
  • University: Politecnico di Milano, V Scuola di Ingegneria
  • Department: Electronics and Computer Science
  • University Degree: Engineering Automation
  • Mentor: Roberto Quadrini

Designing new study programs and/or modules

The design of new educational modules and their corresponding curricula is grounded in a rigorous Research and Development (R&D) model aimed at precisely identifying the needs and challenges associated with critical infrastructures (such as those in the energy, transportation, digital, water, and food sectors, among others). The preliminary phase involves an in-depth analysis of the respective supply chains to identify critical bottlenecks that hinder truly integrated and collaborative participation among all stakeholders involved in the system.
The identified challenges are subsequently subjected to a multi-area qualification process that evaluates not only the scientific relevance of the proposed solution but, more importantly, its practical applicability in the market context and its capacity to be implemented in real-world and complex scenarios.
The value attributed to each innovation emerges from a critical examination of several foundational pillars, including:
  • The existence or prospect of new business models aimed at the concrete commercial proposition of the solution;
  • The multi-sided nature of the proposal, understood as generating value shared among multiple actors across the supply chain rather than benefiting a single entity;
  • The readiness and suitability of the market to adopt and integrate the solution, also considering the potential necessity of transitional incentive mechanisms;
  • The solution’s ability to anticipate European regulatory requirements, implicitly supporting legislators and contributing to the development of directives such as the TIDE for ARERA (Italian Regulatory Authority for Energy, Networks and Environment);
  • The identification of potential cross-sectoral application areas within critical infrastructures, enabled by a lateral thinking approach which fosters multidisciplinary innovation;
  • The determination of the solution’s contribution to security, with a particular focus on Operational Technology (OT), a crucial element for protecting industrial and infrastructural systems;
  • The realization of a Proof of Concept (PoC) leveraging simulation systems based on artificial intelligence to validate the solution under controlled yet realistic operational conditions;
  • The production of significant scientific outputs, such as patents and academic publications, attesting to the methodological rigor and innovative relevance of the developed solutions.
In this context, the integration of lateral thinking assumes a strategic role as it permits overcoming the constraints of orthodox reasoning and exploring novel application modalities of the solution within various critical infrastructure domains. OT security also constitutes an indispensable criterion, reflecting the urgency of preserving the integrity and resilience of interconnected physical systems against increasingly sophisticated digital threats.
Finally, prototyping through AI-driven simulations represents a fundamental step, not only as a technical verification tool but also as the fulcrum of an R&D process capable of generating transferable and protectable knowledge—testimony to the solid scientific foundation and pragmatic orientation that characterize the design and educational development of new training areas dedicated to critical infrastructures.

Research Areas

Applied Artificial Intelligence

  • Design and development of innovative algorithms for optimizing complex systems.
  • Implementation of AI solutions in energy management and critical infrastructure.
  • Use of machine learning techniques integrated with data and simulations.
  • The determination of the solution’s contribution to security, with a particular focus on Operational Technology (OT), a crucial element for protecting industrial and infrastructural systems

Advanced Energy Methodologies

  • Development of advanced methodologies for managing and optimizing energy resources.
  • Creation and application of the PSB method (Profiling, Scheduling, Balancing), aimed at improving energy efficiency in distributed systems.
  • Demand-Response programs

Optimization of Critical Infrastructures

  • Research and applications for operational optimization of essential infrastructures.
  • Formulation of mathematical models for load balancing, scheduling, and the load consumption aggregation (industrial/commercial) that support the power grid as ancillary services

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