Statistical Analysis of an Energy Community S Operations in p2p Energy Trading and Flexibility Markets

This article explores statistical patterns in energy surplus sales from energy communities (EC) with high penetration of distributed energy resources (DERs) and their potential role in providing flexibility services to the distribution system operator (DSO). The study suggests a possible linear correlation between the distributions of the EC s aggregated PV generation and energy surplus sales, which could help DSOs estimate grid contributions based on solar production characteristics. Additionally, it characterizes EC behavior in terms of demand and energy trading, identifying hours with a higher likelihood of flexibility provision and estimating the potential quantity of such services. To generate the data, two optimization models were developed to simulate EC operations, focusing on peer-to-peer (P2P) energy trading and evaluating the EC s capability to provide flexibility as a service to the DSO. The models employ a second-order cone programming formulation incorporating distribution network (DN) constraints and considering different DERs, including rooftop solar panels, energy storage systems, electric vehicles, and heat pumps. Simulations were performed over a one-year horizon with hourly resolution using a modified single-phase version of the IEEE European Low Voltage test feeder, ensuring sufficient annual data for statistical analysis. As a result, the identified statistical patterns could assist the DSO in planning operations based only on aggregated community data, avoiding the need to model individual user decisions and ensuring data privacy. © 2025 Elsevier Ltd