An embedded accelerated decentralized optimization algorithm with application to energy communities
Giulio Ferro (Università degli Studi di Genova)
Sergio Grammatico (TU Delft - Team Sergio Grammatico)
Luca Parodi (Università degli Studi di Genova)
Reza Rahimi Baghbadorani ( Erasmus Universiteit Rotterdam)
Michela Robba (Università degli Studi di Genova)
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Abstract
Renewable Energy Communities (RECs) enable local energy sharing, reduce grid dependency, and support the energy transition. This work proposes an embedded-oriented Energy Community Management framework that maximizes shared energy while minimizing individual costs, increasing economic benefits. The architecture uses bilevel programming, decoupled via a reformulation of the objective and subproblems with KKT conditions. Optimization employs a modified ADMM algorithm with Nesterov acceleration for faster convergence. Implemented on low-power microcontrollers (ODROID-N2L and H3+), the framework demonstrates real-time feasibility and highlights the potential of lightweight, decentralized REC management.
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File under embargo until 21-09-2026