Detailed versus aggregated modeling in energy community operation optimization

Energy communities are key paradigms in the transition toward decentralized and renewable-based energy systems. However, their inherent complexity often makes their optimal operation computationally demanding. This paper compares two alternative formulations for the optimal operation of a renewable energy community composed of residential multifamily buildings with rooftop photovoltaics and battery storage. On one hand, a detailed model represents each building as an individual active node, while on the other a simplified formulation aggregates all active components into a single equivalent node. Both are formulated as Linear Programming problems and applied to a case study using one-year real household and building load data from northern Italy, with synthetic photovoltaic generation based on typical meteorological year data. Multiple sizing scenarios are tested. Results show that the simplified model closely matches the detailed one, with annual energy quantities and optimal costs differing by less than 0.2%. Instead, solution times are reduced by over 80%, confirming that careful aggregation can be a valid strategy when detailed node-level outputs are not required.