Fonseca, T.; Ferreira, L.L.; Landeck, J.; Klein, L.; Sousa, P.; Ahmed, F. Flexible Loads Scheduling Algorithms for Renewable Energy Communities. Energies2022, 15, 8875.
Fonseca, T.; Ferreira, L.L.; Landeck, J.; Klein, L.; Sousa, P.; Ahmed, F. Flexible Loads Scheduling Algorithms for Renewable Energy Communities. Energies 2022, 15, 8875.
Fonseca, T.; Ferreira, L.L.; Landeck, J.; Klein, L.; Sousa, P.; Ahmed, F. Flexible Loads Scheduling Algorithms for Renewable Energy Communities. Energies2022, 15, 8875.
Fonseca, T.; Ferreira, L.L.; Landeck, J.; Klein, L.; Sousa, P.; Ahmed, F. Flexible Loads Scheduling Algorithms for Renewable Energy Communities. Energies 2022, 15, 8875.
Abstract
Renewable Energy Communities (RECs) are emerging as an effective concept and model to empower the active participation of citizens on the energy transition, not only as energy consumers, but also as promoters of environmentally friendly energy generation solutions. This paper aims to contribute to the management and optimization of individual and community Distributed Energy Resources (DER). The solution follows a price and source-based REC management program, in which consumers day-ahead flexible loads (Flex Offers) are shifted according to electricity generation availability, prices and personal preferences, to balance the grid and incentivize user participation. The heuristic approach used in the proposed algorithms allows the optimization of energy resources in a distributed edge and fog approach with a low computational overhead. The simulations performed using real world energy consumption and flexibility data of a REC with 50 dwellings show an average cost reduction of 10.6% and an average increase of 11.4% in individual self-consumption. Additionally, the case-study demonstrates promising results regarding grid load balancing and the introduction of intra-community energy trading.
Keywords
Energy Community, Scheduling, Renewable energy, Flex-Offers, Algorithms
Subject
Engineering, Energy and Fuel Technology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
