Journal
COMPUTERS & OPERATIONS RESEARCH
Volume 160, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cor.2023.106358
Keywords
Energy communities; Loads scheduling; Column generation heuristic
Ask authors/readers for more resources
This paper focuses on optimizing the collective self-consumption rate in energy communities by scheduling members' loads. The proposed strategy aims to implement a Demand Side Management program using controllable loads' characteristics. A MILP formulation is used to give optimal planning for electrical devices' operations and minimize energy flows from the public grid. Additionally, a column generation-based heuristic is developed for large problem instances. Numerical experiments show that joining an energy community saves money on energy bills and reduces energy drawn from the primary grid by at least 15%.
This paper focuses on optimizing the collective self-consumption rate in energy communities by scheduling members' loads. The community remains connected to the public grid and comprises prosumers, traditional consumers, and distributed storage units. Prosumers can exchange their energy with the public grid or other members. The proposed strategy aims at implementing a Demand Side Management program taking advantage of controllable loads' characteristics. A MILP formulation of the problem allows, on the one hand, to give the optimal planning for electrical devices' operations. On the other hand, it provides optimal solutions for managing the storage units, peer-to-peer exchanges, and interactions with the public grid to minimize the energy flows from the public grid over time. However, this MILP only allows for solving small problem instances. Thus, we develop a column generation-based heuristic for large problem instances. Our numerical experiments based on real data collected in the south of France show that joining an energy community saves money on energy bills and reduces the total energy drawn from the primary grid by at least 15%.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available