A Distributed Framework for Joint Energy and Flexibility Scheduling in Local Energy Communities

Other conference contribution, 2025

With the growing trend of electrification in heating and transportation systems, the need to provide flexibility in distribution networks has become increasingly important. This paper presents a decentralized scheduling framework for the simultaneous management of energy and provision of flexibility services within local energy communities. The main goal of this framework is to minimize energy consumption costs at the user level while  enabling responsiveness to the needs of the distribution system operator through the provision of flexibility services. In the proposed model, each community member makes independent decisions to maximize their own benefits. 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 generation 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, and the results show that this method can reduce energy costs and peak load, increase revenue from flexibility services, and enhance the system's operational reliability.