Nowadays, the sharing of energy production within Energy Communities is promoting the diffusion of a decentralized energy system where renewable generation can be locally self-consumed by its members. The maximization of the matching between generation and demand is then crucial to ensure higher economic and environmental benefits for residential end-users joining Energy Communities. In this view, an optimization approach based on Mixed Integer Linear Programming is proposed to model end-users flexibility for investigating how the change in consumption habits can improve energy sharing by maximizing the match between renewable production and demand. The user’s discomfort is also considered to figure out the impact on the existing behavior. An Italian multi-family residential building case study is considered to highlight energy, economic, environmental, and social impacts due to flexible demand. Results reveal that if end-users fully agreed to flexible demand, self-consumption increased up to 95.9%, with a decrease in energy bills and carbon emissions of 4.6% and 9%, respectively. Otherwise, if a lower availability of end-users flexibility is also included in a multi-objective perspective, a possible trade-off between the energy and discomfort point of view can be found. In fact, suitable economic and environmental performances are still reached with self-consumption increased up to 93.7% and cost and emission savings of 3.8% and 7.5%, respectively.
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Lazzeroni et al. (2025) studied this question.
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