Renewable Energy Communities are integral to the European Commission's energy transition agenda. These communities foster the participation of citizens, local authorities, and enterprises in producing, exchanging, and consuming renewable energy locally. The community members benefit from various financial incentives, including payments for excess renewable production, a premium tariff for renewable shared energy, and the refund of part of the electricity bill. However, high penetration of renewable energy sources can challenge grid stability, necessitating the adoption of flexibility strategies like battery systems and demand-side management. This paper presents a prototype of a tool for the real-time optimal management of renewable energy communities in which renewable generation, electrical loads and batteries are present. The community management tool implements: algorithms for forecasting load consumption and renewable generation; and algorithms for the optimal management of controllable resources.

Enhancing Management and Control of Renewable Energy Communities: A Practical Implementation

Conte F.;
2024-01-01

Abstract

Renewable Energy Communities are integral to the European Commission's energy transition agenda. These communities foster the participation of citizens, local authorities, and enterprises in producing, exchanging, and consuming renewable energy locally. The community members benefit from various financial incentives, including payments for excess renewable production, a premium tariff for renewable shared energy, and the refund of part of the electricity bill. However, high penetration of renewable energy sources can challenge grid stability, necessitating the adoption of flexibility strategies like battery systems and demand-side management. This paper presents a prototype of a tool for the real-time optimal management of renewable energy communities in which renewable generation, electrical loads and batteries are present. The community management tool implements: algorithms for forecasting load consumption and renewable generation; and algorithms for the optimal management of controllable resources.
2024
Battery Energy Storage Systems, Experimental Validation, Model Predictive Control, PV Systems, Renewable Energy Community, Software-in-the-Loop Simulation
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12610/87524
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