With the growing trend of electrification in heating systems and transportation, the need to provide flexibility in distribution networks has become increasingly important. In this paper, a decentralized planning framework is proposed for the simultaneous management of energy and the provision of flexibility services in local energy communities. The main objective of this planning approach is to reduce energy consumption costs at the prosumer level while enabling responsiveness to the needs of the distribution system operator through the provision of flexibility services.

In the proposed model, each member of the energy community — such as a building equipped with a photovoltaic system and an energy storage system — makes decisions independently with the aim of maximizing its own benefit. Coordination among community members is achieved through the ADMM algorithm, a decentralized optimization method based on iterative information exchange. To account for uncertainties in solar energy production and load forecasting, a rolling horizon scheduling algorithm is employed.

The effectiveness of the proposed framework is evaluated using real data from a demonstration site. The results show that this approach can reduce energy costs and peak demand, increase revenues from flexibility provision, and enhance the reliability of system operation.