Optimal Allocation of Agents among Collective Self-Consumption Communities

Progressive apparition of collective self-consumption communities leads to a yet-unanswered question: how to consider a community not only as a single entity, but as part of a bigger local ecosystem such as a neighbourhood or a city ? A first step in answering this question is to consider community design not from a single community’s standpoint, but from a broader perspective, looking at which communities would be best to create in a local area context. This paper proposes an optimization-based approach for allocation of agents among potential Collective Self-Consumption communities, and compares two possible objective functions. The first is minimizing costs for all agents and the second is maximizing the savings for the agent with the least savings. The considered agent’s trades are also optimally allocated as part of the optimization process, according to the same objectives. The proposed approach is applied to a fictitious case study. The results show that the second objective function leads to significantly lower savings for the whole group, while providing little or no savings to the least savings agent, compared to the results obtained with the first objective function. Finally, a lower bound for the maximum number of agents that can be allocated using this approach was measured, fixing 60 agents over a month of hourly energy data as a limit.