Abstract
ECODREAM Energy Communities (ECs) are envisioned to be the future of smart energy grids as they integrate distributed energy resources efficiently, by promoting self-consumption of the end-user(s). ECs are the result of a recent and evolving regulation framework that allows the end-users (a minimum of two participants) to define economic contracts in order to share distributed energy resources. An EC is characterized by end-user(s) in a close geographical proximity that have an electrical and/or thermal demand, along with individual/shared renewable energy resources and storage technologies. ECs have the potential to offer i) environmental benefits in the form of reduced carbon footprint, ii) social benefit in the form of increased end-user participation, iii) economic benefits in the form of the revenue obtained due to the reduction in distribution and transmission cost and grid losses. In order to guarantee stable and reliable operations of individual ECs, and possibly their interaction with external entities (such as neighboring ECs or for-profit entities such as the aggregator), a synergic combination of control algorithms aided with information and communication technologies (ICT) is needed. The control algorithms need to comply with regulation policies, end-user(s) preferences, operational constraints of the EC and their interaction with external entities. Motivated by the above challenges, the focus of the project is threefold: (i) to formalize new models specific to the design and functioning of ECs; (ii) to design distributed algorithms and software toolboxes capable of generating local-level control policies with global optimality and safety guarantee, and (iii) to test the algorithms on a real test-bed and their scalability through extensive large-scale simulations. ECODREAM aims at enlarging each partner’s knowledge and expertise towards the other ones’, extending existing methods in the core interest of the partners, and at employing this consolidated knowledge to converge vertically on the applications. The project algorithms will be benchmarked, both in simulation and on the test-bed, with the state of the art in terms of computational and control performance also, and within the possible extent, over a range of key performance indicators (such as energy and environmental, economic, social performance, and so on).
Dettagli del progetto
Responsabile scientifico: Giuseppe Notarstefano
Strutture Unibo coinvolte:
Dipartimento di Ingegneria dell'Energia Elettrica e dell'Informazione "Guglielmo Marconi"
Coordinatore:
Università del SANNIO di BENEVENTO(Italy)
Contributo totale Unibo: Euro (EUR) 63.856,00
Durata del progetto in mesi: 24
Data di inizio
28/09/2023
Data di fine:
28/02/2026
