A Distributed-Optimization-Based Architecture for Management of Interconnected Energy Hubs

Abstract

This article proposes a system architecture for an energy community (EC) in a smart city for the optimal management of interconnected energy hubs (EHs) supervised by an Energy Community Manager (ECM). Considered EHs include building EH, microgrid EH, and electric vehicle EH. A dedicated peer-to-peer market is assumed to be present in the EC that allows the energy exchange among these EHs that are interconnected through an electricity network (E-N) and a district heating network (DH-N). The overall decision problem has been formalized as a constrained optimization problem, and a new distributed optimization algorithm, Nesterov-Proximal Atomic Coordination (NST-PAC), is proposed ensuring the privacy of information exchange, with Nesterov’s acceleration-based iterations that lead to a fast solution. The overall approach is evaluated using two case studies characterized by an IEEE 13-bus system as the E-N and nine nodes as the DH-N and by an IEEE 123-bus system as the E-N and 30 nodes as the DH-N. Different comparisons have been performed to show the advantages of the system architecture compared to the state of the art in practice and other recent approaches suggested in the literature in terms of savings, convergence speed, and scalability.