PROGRAMMA PRIN 2022 - BCALL PRIN2022 D.D. N.104 DEL 2 FEBRUARY 2022
PROJECT TITLE: Control, cOoperation, and Resilience in Rural Energy CommuniTies (CORRECT)
CUP CODE: D53D23000970006
Budget: € 172.016
P.I. and U.R. Coordinator Politecnico di Bari: Prof. Mariagrazia Dotoli
Other U.R.: University of Genoa (coordinator: Prof. Roberto Sacile)
Brief project description
The CORRECT project is situated within the context of the energy and digital transition, with particular reference to rural areas, which present specific characteristics in terms of resource availability, infrastructure, and energy demand. In these contexts, the integration of renewable sources, storage systems, agricultural electrical loads, and digital technologies generates complex and distributed systems, whose management requires advanced approaches to modeling, control, and optimization.
The project addressed these challenges by proposing a systemic approach to the study of Rural Energy Communities (RECs), understood as multi-actor and multi-energy-vector systems in which production, consumption, and storage are strongly interconnected. Within this framework, innovative methodologies were developed for the modeling, control, and optimal management of such systems, with particular attention to the integration between energy and agriculture (e.g., agrivoltaics, smart greenhouses, precision agriculture).
Project objectives
The main objective of the project was to design advanced control architectures and decision-support tools for the efficient, sustainable, and resilient operation of RECs.
In particular, the project pursued the following objectives:
to develop advanced models to describe the dynamic behavior of rural energy systems and agricultural infrastructures;
to design distributed and data-driven control strategies for the coordinated management of energy resources;
to enable cooperation mechanisms among the system actors, also through distributed optimization approaches and game theory;
to improve self-consumption and energy efficiency, reducing dependence on the traditional power grid;
to increase the resilience of the systems with respect to demand variations, environmental conditions, and market dynamics;
to validate the proposed solutions through advanced simulation environments and digital twin technologies.
Expected project results
The expected results of the project concerned both methodological and application aspects. In particular, the following were envisaged:
the development of multi-level models for representing rural energy systems and agricultural loads;
the definition of advanced control architectures for the integrated management of production, consumption, and storage;
the introduction of optimization tools for balancing energy production and agricultural activities;
the design of strategies to increase flexibility, self-consumption, and system resilience;
the creation of validation environments based on digital twins and realistic case studies;
the production of scientific results of high impact and their dissemination within the international scientific community.
Achieved project results
The results achieved are fully consistent with the project objectives and, in several cases, exceed initial expectations. The project has in fact led to the development of significant methodological and applied contributions in the following areas, as demonstrated by the publications obtained:
modeling and control of energy and agricultural systems, with particular reference to smart greenhouses and agrivoltaic systems, through the integration of physical models and data-driven approaches;
development of predictive and robust control algorithms capable of managing uncertainty and ensuring high performance in variable operational contexts;
definition of distributed and game-theory-based frameworks for energy resource management in multi-stakeholder contexts;
design of solutions for the resilience and electrification of rural areas, including storage infrastructure and distributed energy systems;
validation of the proposed methodologies through advanced simulation environments and digital twin platforms based on real data.
From a scientific perspective, the project results have been disseminated in high-level international journals and presented at major scientific conferences. For brevity, only journal publications are reported below.
Main international journal publications resulting from the project
Below are some of the main journal publications resulting from the project:
Mignoni, N.; Zero, E.; Scarabaggio, P.; Carli, R.; Sacile, R.; Dotoli, M. (2026) “A Robust Data-driven MPC for Greenhouses Temperature Control”, Control Engineering Practice, 173, 106983. doi: 10.1016/j.conengprac.2026.106983. In press.
Mignoni, N.; Scarabaggio, P.; Carli, R.; Dotoli M. (2026) “Controlling PV Panels Tilt Orientation for Optimal Crop Shading and Power Generation in Agrivoltaics,” IEEE Transactions on Control Systems Technology. doi: 10.1109/TCST.2026.3675731. In press.
Soussi, A.; Zero, E.; Herrera, C. D. C.; Zahmoun, S.; Bozzi, A.; Sacile, R. (2026) “Integrating Digital Twins and MPC for Sustainable Greenhouse Management in Smart Agriculture,” in IEEE Transactions on AgriFood Electronics, vol. 4, no. 1, pp. 39-55. doi: 10.1109/TAFE.2025.3572808.
Zhukovskii, K.; Scarabaggio, P.; Ovsiannikova, P.; Jhunjhunwala, P.; Carli, R.; Dotoli, M.; and Vyatkin, V. (2025) “Decentralized Control of Crop Growth Conditions in Vertical Farms under Dynamic Energy Markets” IEEE Transactions on Automation Science and Engineering, vol. 22, pp. 21498-21511. doi: 10.1109/TASE.2025.3609694.
Soussi, A., Zero, E., Bozzi, A., Sacile, R. (2024). Enhancing energy systems and rural communities through a system of systems approach: A comprehensive review. Energies, 17(19), 4988. doi: 10.3390/en17194988.
Soussi, A., Zero, E., Sacile, R., Trinchero, D., Fossa, M. (2024). Smart sensors and smart data for precision agriculture: a review. Sensors, 24(8), 2647. doi: 10.3390/s24082647.
Fig. 1 - Plant shading in agrivoltaic systems
Fig. 2 – Prototype of a module with trays for vertical farming
Fig. 3 - Mini greenhouse used in validation activities
