Roberto Rocca (Member, IEEE) was born in Rome, Italy, in 1989. He received the B.S. degree in energy engineering and M.S. degree in electrical engineering in 2013 and 2015, respectively, both from the Sapienza University of Rome, Rome, Italy. In 2020, he received the Ph.D. degree in electrical and electronics engineering from the Power Electronics, Machines and Control Group of the University of Nottingham, Nottingham, U.K. From 2019 to 2020, he was the Postdoctoral Researcher with Sapienza Electrical Machines and Power Electronics Research Group of the Sapienza University of Rome. He is currently a Research Fellow with the Research Centre for Energy Resources and Consumption (CIRCE), Zaragoza, Spain and an Adjunct Research Fellow with the CIRCE Mixed Research Institute, Zaragoza. Dr. Rocca is Member of the IEEE Power and Energy Society, where he is volunteering as secretary of the Spanish Chapter and is an accredited lecturer/assistant professor for the Spanish Ministry of University.
EDUCATION
Bachelor Degree in Energy Engineering
Master Degree in Electrical Engineering
Ph.D. Degree in Electrical and Electronics Engineering
RESEARCH, TEACHING, or OTHER INTERESTS
Electrical and Electronic Engineering, Energy Engineering and Power Technology, Control and Optimization
26
Scopus Publications
246
Scholar Citations
10
Scholar h-index
10
Scholar i10-index
Scopus Publications
Improved Design-Oriented Analytical Model for Switched Reluctance Machines' Unsaturated Inductance in Non-Overlap Conditions Roberto Rocca, Giulio De Donato, Paolo Bolognesi, Chris Gerada, Fabio Giulii Capponi IEEE Transactions on Energy Conversion, 2026 Design-oriented analytical modelling of switched reluctance machines (SRMs) is currently an active field of research, as it significantly alleviates the computational burden of design processes by replacing or complementing finite element analysis. The modelling of saturated SRMs, including the determination of saturated flux loci and the calculation of torque and current waveforms, requires prior knowledge of the unsaturated inductance vs rotor position profile. This work proposes an improved analytical model to determine unsaturated inductances in non-overlap conditions, based on a twofold improvement of the permeance method: the use of elliptic flux tubes; and the ability to self-tailor the flux tube shapes to any machine geometry. Its accuracy is proven against finite element analysis applied to four designs and against experimental results of a full-scale prototype. Finally, it is shown how the model can be incorporated into a fully analytical design tool, whose accuracy in calculating performance and computational burden are evaluated.
Practical Considerations for the Development of Two-Stage Deterministic EMS (Cloud–Edge) to Mitigate Forecast Error Impact on the Objective Function Gregorio Fernández, J. F. Sanz Osorio, Roberto Rocca, Luis Luengo-Baranguan, Miguel Torres Applied Sciences Switzerland, 2026 The growing penetration of Distributed Energy Resources (DERs)—such as photovoltaic generation, battery energy storage, electric vehicles, hydrogen technologies and flexible loads—requires advanced Energy Management Systems (EMS) capable of coordinating their operation and leveraging controllability to optimize microgrid performance and enable flexibility provision to the grid. When the physical, electrical, and economic system model is properly defined, the main sources of performance degradation typically arise from forecast uncertainty and temporal discretization effects, which propagate into sub-optimal schedules and infeasible setpoints. This paper proposes and tests a two-stage deterministic EMS architecture featuring rolling-horizon planning at an upper layer and fast local setpoint adaptation at a lower layer, jointly to reduce the impact of forecast errors and other uncertainties on the objective function. The first stage can be deployed either on the edge or in the cloud, depending on computational requirements, whereas the second stage is executed locally, close to the physical assets, to ensure timely corrective action. In the simulated cloud-executed planning case, moving from hourly to 15 min granularity improves the objective value from −49.39€ to −72.12€, corresponding to an approximate 46% reduction in operating cost. In our case study, the proposed second-stage local adaptation can reduce the mean absolute error (MAE) of the EMS performance loss by approximately 50% compared with applying the first-stage schedule without local correction. Results show that this two-stage hierarchical EMS effectively limits objective-function degradation while preserving operational efficiency and robustness.
Optimal PV-BESS Systems Sizing Algorithm with a Novel Price-Driven Rule-Based Energy Management Strategy Luis Luengo-Baranguan, Roberto Rocca, Marcos Remiro-Cinca, David Rivas-Ascaso, Gregorio Fernández-Aznar, Sara Barja-Martinez, Lorena Elorza-Uriarte IEEE Transactions on Industry Applications, 2026 In recent years, combined optimisation of Photovoltaic (PV) and Battery Energy Storage Systems (BESS) has attracted remarkable attention both in academic and industrial world, as it provides a twofold solution to increase prosumers self-consumption and mitigate issues related to high BESS capital costs. In this context, this work proposes a novel optimal sizing algorithm for PV-BESS systems, based on a two-level architecture. In the upper level, a Genetic Algorithm (GA) determines the optimal rated PV power, BESS power and storage capacity, with the objective of minimising the Levelised Cost of Energy (LCOE). In the lower level, a novel rule-based Energy Management System (EMS) is embedded, with rules being written for dynamic retailer and feed-in tariffs. In particular, electricity buy and sell price thresholds are also optimised by the GA. The proposed algorithm is eventually tested in a reality-based case study, with real data from a commercial prosumer located in Zaragoza, Spain, where the proposed solution is benchmarked against an optimal sizing algorithm composed of a GA in the upper level, and a Mixed Integer Linear Programming (MILP) EMS in the lower level.
Comparative Study of Neuroevolution and Deep Reinforcement Learning for Voltage Regulation in Power Systems Adrián Alarcón Becerra, Vinícius Albernaz Lacerda, Roberto Rocca, Ana Patricia Talayero Navales, Andrés Llombart Estopiñán Inventions, 2025 The regulation of voltage in transmission networks is becoming increasingly complex due to the dynamic behavior of modern power systems and the growing penetration of renewable generation. This study presents a comparative analysis of three artificial intelligence approaches—Deep Q-Learning (DQL), Genetic Algorithms (GAs), and Particle Swarm Optimization (PSO)—for training agents capable of performing autonomous voltage control. A unified neural architecture was implemented and tested on the IEEE 30-bus system, where the agent was tasked with adjusting reactive power set points and transformer tap positions to maintain voltages within secure operating limits under a range of load conditions and contingencies. The experiments were carried out using the GridCal simulation environment, and performance was assessed through multiple indicators, including convergence rate, action efficiency, and cumulative reward. Quantitative results demonstrate that PSO achieved 3% higher cumulative rewards compared to GA and 5% higher than DQL, while requiring 8% fewer actions to stabilize the system. GA showed intermediate performance with 6% faster initial convergence than DQL but 4% more variable results than PSO. DQL demonstrated consistent learning progression throughout training, though it required approximately 12% more episodes to achieve similar performance levels. The quasi-dynamic validation confirmed PSO’s advantages over conventional AVR-based strategies, achieving voltage stabilization approximately 15% faster. These findings underscore the potential of neuroevolutionary algorithms as competitive alternatives for advanced voltage regulation in smart grids and point to promising research avenues such as topology optimization, hybrid metaheuristics, and federated learning for scalable deployment in distributed power systems.
Smart home energy flow optimization, a practical case study Stefano Leonori, Roberto Rocca, Marco Ricci, Fabio Massimo Frattale Mascioli Energy Conversion and Management X, 2025 This paper presents a practical framework for energy management in smart homes, based on a realistic case study of energy flow optimization involving controllable devices usually available in modern households, including both thermal and battery storage systems. The framework is defined based on a practical energy paradigm and formulates the optimization problem, including all equations and constraints. The smart home model includes a rooftop PV system, battery, a bidirectional Smart Charger, Deferrable Appliances, and an electrified Ground Source Heat Pump equipped with a Thermal Energy Storage. A dedicated dataset is built from peer-reviewed literature and statistical datasets following an easily replicable methodology. The period considered spans one year, capturing seasonal variations and hence providing a robust foundation for performance evaluation. Three case studies are developed using a Dynamic Programming (DP) algorithm, each targeting a distinct Objective Function: maximizing self-consumption, minimizing fluctuations in exchange power with the grid, and promoting a constant daily exchange. Compared to a baseline configuration without an energy management system, results show that minimizing power fluctuations leads to a nearly 100% improvement in squared temporal variations of grid energy exchanges. The self-consumption case yields a limited 13% improvement due to an unfavorable production–demand imbalance, while the third case achieves a 28% improvement in maintaining a flat daily grid energy exchange. As an additional element of novelty, this work wishes to provide a valuable reference for future research, as the proposed DP-based framework allows a simple and thorough evaluation of the flexibility contributions provided by each single energy device, an approach rarely explored in existing literature.
Optimal scheduling of district heat pumps conceived for implementation in Energy Management Systems to participate in demand response Roberto Rocca, Stefano Leonori, Gregorio Fernández Aznar, Riccardo Toffanin, Luis Luengo-Baranguan Energy Conversion and Management X, 2025 Nowadays, the exponential growth of Indirect Demand Response (IDR) and Direct Demand Response (DDR) programs is urging researchers to investigate new strategies to enable the provision of flexibility services from any type of energy device. In the case of Heat Pumps (HPs), research efforts revolve around their integration in Energy Management Systems (EMS). To this end, this work proposes a novel formulation of the optimal scheduling problem of district-level HPs, conceived for EMS implementation, and based on a quadratic programming algorithm, with a specific objective function for IDR and DDR. Furthermore, a rigorous methodology is defined to assess HPs’ performance under both IDR and DDR, where IDR price signals pursue a peak-shaving/valley-filling objective, while DDR considers participation in flexibility markets. The proposed optimal scheduling is implemented in a practical case study, based on real data from the Horizon-Europe project REEFLEX. Results under IDR prove the peak shaving and valley filling capabilities, obtaining reductions in consumption peak and peak-to-dip gap of up to 13% and 34% respectively. Possibility of designing IDR price signals to avoid extra costs for the end users is also proven. For DDR, a sensitivity analysis of peak and average consumption against the price of the flexibility offer is conducted. Peak and average consumption are proven to reduce up to 20% and 35% for upwards flexibility, and to increase up to 100% and 80% for downwards flexibility. Besides, the total energy cost increases against the flexibility price offers at rates of up to 3.75% and 11.25%, respectively in upwards and downwards flexibility.
Modelling of Underground Cables to Evaluate Transient Overvoltages Induced by Lightning Strokes Proximate to the Burial Point Mario Garcia-Molina, Fidel S. Moreno, Roberto Rocca IEEE Pes Innovative Smart Grid Technologies Conference Europe, 2025 This work presents a novel modelling methodology for underground cables, aimed at evaluating transient overvoltages induced by lightning strokes in the proximity of their burial points. A detailed electromagnetic model of the complete cable-line system is developed, including a novel modelling of the cable section directly exposed to soil ionisation effects, i.e., buried within the so-called primary ionisation zone. The model has been implemented in a practical study in the ATP software. Results show that lightning impacts nearby cables burial points may generate overvoltages exceeding insulation withstand thresholds. In particular, it is shown that critical overvoltages arise within a specific distance between substation/wind turbine, referred to as critical distance.
Consideration of Battery Ageing and Charger Efficiency Nonlinearity in the Optimal Scheduling of V2G Chargers with MIQP Algorithms Roberto Rocca, Gregorio Fernández-Aznar, Alfonso Calavia-Sainz-Maza, Stefano Leonori IEEE Pes Innovative Smart Grid Technologies Conference Europe, 2025 This work proposes a simple methodology to include nonlinearities of Battery Ageing (BA) and Charger Efficiency (CE) in the optimisation of Vehicle-to-Grid (V2G) chargers’ scheduling through Mixed-Integer Quadratic Programming. BA is addressed with a 1st-order, piecewise expression already available in the literature, adapted to include the rated lifetime number of cycles. For CE, data available are firstly interpolated with a Frohlich equation, which is subsequently resampled with a 1st-order, piecewise expression. The idea is implemented in a case study to optimise the scheduling of a small-office V2G charger, minimising the sum of energy and battery degradation costs.
Genetic-Algorithm-Based Energy Flow Optimization for Smart Homes Stefano Leonori, Roberto Rocca, Marco Ricci, Fabio Massimo Frattale Mascioli, Luigi Martines IEEE Pes Innovative Smart Grid Technologies Conference Europe, 2025 This paper presents a Genetic Algorithm (GA)-based approach for optimal energy flow scheduling in smart homes equipped with several energy devices, including Photovoltaic, Battery Energy Storage System, Deferrable Appliances, and Electric Vehicle Smart Charger. The objective of the optimization is to minimize the fluctuations of the power exchanged with the grid by minimizing the cumulative quadratic difference of consumption in subsequent time-steps, promoting so load balancing and alleviating grid stress. Due to the quadratic nature of the problem, classical solvers such as MILP/MIQP are unsuitable, while Dynamic Programming suffers of poor replicability. By contrast, the proposed GA-based method offers a flexible and effective alternative. Simulation results highlight substantial improvements with respect to a non-flexible baseline, obtaining a considerable grid stress reduction. Additionally, valuable insights into the impact of GA parameter tuning are provided, along with a proof of the effectiveness of the sequential optimization of controllable devices, which facilitates the integration of larger numbers of devices while maintaining a reasonable computation burden.
Energy Flow Management in Smart Homes via Pontryagin Minimum Principle Stefano Leonori, Roberto Rocca, Marco Ricci, Fabio Massimo Frattale Mascioli, Luigi Martines IEEE Pes Innovative Smart Grid Technologies Conference Europe, 2025 This paper presents a study on the application of the Pontryagin’s Minimum Principle algorithm for energy flow scheduling in a prosumer smart home equipped with Photovoltaic generation and a Battery Energy Storage System. The optimization objective is to minimize the cumulative quadratic deviation of grid exchange with respect to the daily net energy demand, thereby promoting load balancing and reducing grid stress. The proposed method provides a flexible and effective alternative to Rule Based solutions, showing substantial improvements. Valuable insights are also provided through a comparison with a Dynamic Programming solution used as benchmark. Compared to complex solvers, the proposed method is easy to implement, computationally lightweight, and versatile. Moreover, the approach can be extended to add other devices and/or accommodate multi-objective optimizations.
Electrical Flexibility Forecasting and Assessment for Heat-Pump-Based District Heating Systems Roberto Rocca, Lorena Elorza-Uriarte, Arjen Schamhart, Gerwin Verschuur, David Miguel Rivas-Ascaso Proceedings 24th Eeeic International Conference on Environment and Electrical Engineering and 8th I and Cps Industrial and Commercial Power Systems Europe Eeeic I and Cps Europe 2024, 2024
Initial Assessment of Electrical Flexibility of Combustion-Based District Heating Systems Lorena Elorza-Uriarte, Roberto Rocca, Itziar Zubia, Daniele Farrace, Riccardo Toffanin, David Miguel Rivas-Ascaso Proceedings 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe Eeeic I and Cps Europe 2023, 2023
Practical Considerations for the Development of Two-Stage Deterministic EMS (Cloud–Edge) to Mitigate Forecast Error Impact on the Objective Function G Fernández, JF Sanz Osorio, R Rocca, L Luengo-Baranguan, M Torres Applied Sciences 16 (4), 1844 , 2026 2026 Citations: 1
Optimal PV-BESS Systems Sizing Algorithm with a Novel Price-Driven Rule-Based Energy Management Strategy L Luengo-Baranguan, R Rocca, M Remiro-Cinca, D Rivas-Ascaso, ... IEEE Transactions on Industry Applications , 2026 2026 Citations: 1
Comparative Study of Neuroevolution and Deep Reinforcement Learning for Voltage Regulation in Power Systems A Alarcón Becerra, V Albernaz Lacerda, R Rocca, AP Talayero Navales, ... Inventions 10 (6), 110 , 2025 2025 Citations: 2
Modelling of Underground Cables to Evaluate Transient Overvoltages Induced by Lightning Strokes Proximate to the Burial Point M Garcia-Molina, FS Moreno, R Rocca 2025 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT … , 2025 2025
Consideration of Battery Ageing and Charger Efficiency Nonlinearity in the Optimal Scheduling of V2G Chargers with MIQP Algorithms R Rocca, G Fernández-Aznar, A Calavia-Sainz-Maza, S Leonori 2025 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT … , 2025 2025
Genetic-Algorithm-Based Energy Flow Optimization for Smart Homes S Leonori, R Rocca, M Ricci, FMF Mascioli, L Martines 2025 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT … , 2025 2025
Energy Flow Management in Smart Homes via Pontryagin Minimum Principle S Leonori, R Rocca, M Ricci, FMF Mascioli, L Martines 2025 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT … , 2025 2025
Smart home energy flow optimization, a practical case study S Leonori, R Rocca, M Ricci, FMF Mascioli Energy Conversion and Management: X, 101340 , 2025 2025 Citations: 3
Maturity assessment of grid-scale flexibility and energy storage services towards a decarbonized Europe P Munuera-Mínguez, R Rocca, KN Malamaki, M Zafeiropulou, ... Open Research Europe 4 (196), 196 , 2025 2025 Citations: 1
Improved Design-Oriented Analytical Model for Switched Reluctance Machines' Unsaturated Inductance in Non-Overlap Conditions R Rocca, G De Donato, P Bolognesi, C Gerada, FG Capponi IEEE Transactions on Energy Conversion , 2025 2025 Citations: 1
Optimal scheduling of district heat pumps conceived for implementation in energy management systems to participate in demand response R Rocca, S Leonori, GF Aznar, R Toffanin, L Luengo-Baranguan Energy Conversion and Management: X 27, 101074 , 2025 2025 Citations: 12
Optimal sizing algorithm of pv-bess systems considering a price-driven rule-based energy management strategy L Luengo-Baranguan, M Remiro-Cinca, D Rivas-Ascaso, R Rocca, ... 2024 IEEE International Conference on Environment and Electrical Engineering … , 2024 2024 Citations: 3
Electrical flexibility forecasting and assessment for heat-pump-based district heating systems R Rocca, L Elorza-Uriarte, A Schamhart, G Verschuur, DM Rivas-Ascaso 2024 IEEE International Conference on Environment and Electrical Engineering … , 2024 2024 Citations: 4
Techno-economic analysis of electrical flexibility in combustion-based district heating systems: A Swiss case study R Rocca, L Elorza-Uriarte, I Zubia, D Farrace, R Toffanin, ... International Journal of Electrical Power & Energy Systems 157, 109869 , 2024 2024 Citations: 6
Improved design-oriented analytical modelling of switched reluctance machines based on Fröhlich-Kennelly equations R Rocca, G De Donato, P Bolognesi, C Boccaletti, FG Capponi IEEE Transactions on Energy Conversion 39 (1), 734-746 , 2023 2023 Citations: 10
Grid impact of frequency regulation provided by V2Gs aggregated at HV, MV, and LV level M Bernal-Sancho, R Rocca, G Fernandez-Aznar, MP Comech, ... IEEe Access 11, 76768-76780 , 2023 2023 Citations: 28
Initial assessment of electrical flexibility of combustion-based district heating systems L Elorza-Uriarte, R Rocca, I Zubia, D Farrace, R Toffanin, ... 2023 IEEE International Conference on Environment and Electrical Engineering … , 2023 2023 Citations: 3
Impact Assessment of Different Battery Energy Storage Technologies in Distribution Grids with High Penetration of Renewable Energies Surve, S.P., Rocca, R., Hengeveld, E.J., Martínez, D., Comech, M.P., Rivas, D.M. Renewable Energy and Power Quality Journal, 2022 20, 650-655 , 2022 2022 Citations: 15
Hydrogen Technologies to Provide Flexibility to the Electric System: A Review D Menéndez-Agudin, Á., Rocca, R., Fernandez, G., Luengo-Baranguan, L., Zaldivar Renewable Energy and Power Quality Journal, 2022 20, 656–661 , 2022 2022 Citations: 10
Development and testing of soft magnetic rotor for a switched reluctance motor built through additive manufacturing technology L Gargalis, V Madonna, P Giangrande, R Rocca, I Ashcroft, R Hague, ... 2020 23rd International conference on electrical machines and systems (ICEMS … , 2020 2020 Citations: 9
MOST CITED SCHOLAR PUBLICATIONS
Additive manufacturing and testing of a soft magnetic rotor for a switched reluctance motor L Gargalis, V Madonna, P Giangrande, R Rocca, M Hardy, I Ashcroft, ... IEEE Access 8, 206982-206991 , 2020 2020 Citations: 67
Grid impact of frequency regulation provided by V2Gs aggregated at HV, MV, and LV level M Bernal-Sancho, R Rocca, G Fernandez-Aznar, MP Comech, ... IEEe Access 11, 76768-76780 , 2023 2023 Citations: 28
Optimal advance angle for aided maximum-speed-node design of switched reluctance machines R Rocca, FG Capponi, S Papadopoulos, G De Donato, M Rashed, ... IEEE Transactions on Energy Conversion 35 (2), 775-785 , 2019 2019 Citations: 18
A one-body, laminated-rotor flywheel switched reluctance machine for energy storage: Design trade-offs R Rocca, S Papadopoulos, M Rashed, G Prassinos, FG Capponi, ... 2020 IEEE International Conference on Environment and Electrical Engineering … , 2020 2020 Citations: 17
Impact Assessment of Different Battery Energy Storage Technologies in Distribution Grids with High Penetration of Renewable Energies Surve, S.P., Rocca, R., Hengeveld, E.J., Martínez, D., Comech, M.P., Rivas, D.M. Renewable Energy and Power Quality Journal, 2022 20, 650-655 , 2022 2022 Citations: 15
Optimal scheduling of district heat pumps conceived for implementation in energy management systems to participate in demand response R Rocca, S Leonori, GF Aznar, R Toffanin, L Luengo-Baranguan Energy Conversion and Management: X 27, 101074 , 2025 2025 Citations: 12
Design trade-offs and feasibility assessment of a novel one-body, laminated-rotor flywheel switched reluctance machine R Rocca, S Papadopoulos, M Rashed, G Prassinos, F Giulii Capponi, ... Energies 13 (22), 5857 , 2020 2020 Citations: 12
Improved design-oriented analytical modelling of switched reluctance machines based on Fröhlich-Kennelly equations R Rocca, G De Donato, P Bolognesi, C Boccaletti, FG Capponi IEEE Transactions on Energy Conversion 39 (1), 734-746 , 2023 2023 Citations: 10
Hydrogen Technologies to Provide Flexibility to the Electric System: A Review D Menéndez-Agudin, Á., Rocca, R., Fernandez, G., Luengo-Baranguan, L., Zaldivar Renewable Energy and Power Quality Journal, 2022 20, 656–661 , 2022 2022 Citations: 10
Actual design space methodology for preliminary design analysis of switched reluctance machines R Rocca, FG Capponi, G De Donato, S Papadopoulos, F Caricchi, ... IEEE Transactions on Industry Applications 57 (1), 397-408 , 2020 2020 Citations: 10
Development and testing of soft magnetic rotor for a switched reluctance motor built through additive manufacturing technology L Gargalis, V Madonna, P Giangrande, R Rocca, I Ashcroft, R Hague, ... 2020 23rd International conference on electrical machines and systems (ICEMS … , 2020 2020 Citations: 9
Analytical approach for the identification of an optimal design space for switched reluctance machines R Rocca, FG Capponi, G De Donato, M Rashed, S Papadopoulos, ... 2018 XIII International Conference on Electrical Machines (ICEM), 569-575 , 2018 2018 Citations: 7
Techno-economic analysis of electrical flexibility in combustion-based district heating systems: A Swiss case study R Rocca, L Elorza-Uriarte, I Zubia, D Farrace, R Toffanin, ... International Journal of Electrical Power & Energy Systems 157, 109869 , 2024 2024 Citations: 6
Electrical flexibility forecasting and assessment for heat-pump-based district heating systems R Rocca, L Elorza-Uriarte, A Schamhart, G Verschuur, DM Rivas-Ascaso 2024 IEEE International Conference on Environment and Electrical Engineering … , 2024 2024 Citations: 4
Smart home energy flow optimization, a practical case study S Leonori, R Rocca, M Ricci, FMF Mascioli Energy Conversion and Management: X, 101340 , 2025 2025 Citations: 3
Optimal sizing algorithm of pv-bess systems considering a price-driven rule-based energy management strategy L Luengo-Baranguan, M Remiro-Cinca, D Rivas-Ascaso, R Rocca, ... 2024 IEEE International Conference on Environment and Electrical Engineering … , 2024 2024 Citations: 3
Initial assessment of electrical flexibility of combustion-based district heating systems L Elorza-Uriarte, R Rocca, I Zubia, D Farrace, R Toffanin, ... 2023 IEEE International Conference on Environment and Electrical Engineering … , 2023 2023 Citations: 3
Actual Design Space Methodolofy for High-Performance Switched Reluctance Machines Design R Rocca The University of Nottingham: Nottingham, UK , 2020 2020 Citations: 3
Optimal advance angle for torque maximisation in high-speed, single-pulse operated, switched reluctance machines R Rocca, FG Capponi, S Papadopoulos, G De Donato, M Rashed, ... 2019 IEEE International Electric Machines & Drives Conference (IEMDC), 80-85 , 2019 2019 Citations: 3
Comparative Study of Neuroevolution and Deep Reinforcement Learning for Voltage Regulation in Power Systems A Alarcón Becerra, V Albernaz Lacerda, R Rocca, AP Talayero Navales, ... Inventions 10 (6), 110 , 2025 2025 Citations: 2
