Decentralized Energy Hub Management in Networked Microgrids With Bi-Directional Energy Trading: An RO-IGDT Approach

Abstract

The advancement of technologies in combined cooling, heat, and power (CCHP) systems has significantly driven the development of energy hubs (EHs), offering an efficient platform to integrate diverse energy carriers. This study proposes a comprehensive framework for interconnected energy hubs within networked microgrids (NMGs), aiming to improve the efficiency of multi-carrier energy systems through optimal coordination among the involved entities. In the proposed model, both microgrids and the distribution network are treated as autonomous agents, each managing its own local scheduling challenges. To achieve seamless coordination between these entities, a distributed approach based on the alternating direction method of multipliers (ADMM) is utilised to mitigate power exchange conflicts between multiple microgrids and the distribution network. Additionally, energy systems often operate under uncertain conditions due to the integration of renewable energy sources (RES) and their interactions with the electricity market. To address these uncertainties, this study introduces a novel decentralised optimisation framework that integrates robust optimization (RO) with information gap decision theory (IGDT). The proposed model is evaluated on multi-carrier energy systems within networked microgrids, and the results demonstrate its low computational complexity and guaranteed convergence of the distributed algorithm.