A Hybrid Agent-based Model Predictive Control Scheme for Smart Community Energy System with Uncertain DGs and Loads

Abstract

A multi-agent consensus-based market scheme is proposed for the cooperation of community and multiple microgrids (MGs) in a distributed, economic and hierarchal manner. The proposed community-based market framework with frequency regulation (FR) market is formulated as a two-level scheduling problem: the global decision-making process of community agent (CA) to participate in the FR market and the interaction and control process of local MGs to achieve collaboration in response to the global target with efficient pricing rules. Specifically, the model predictive control (MPC) is integrated with the consensus-based theory to allow MG to obtain an economic and reliable dispatch in the presence of uncertainties of distributed generators and loads. Thanks to the distributed nature of the proposed scheme, its robustness to communication issues has been strengthened and a win-win situation for all energy stakeholders can be achieved. The robustness of the proposed scheme is investigated in various conditions, including different implementation strategies, communication topologies, and the level of uncertainties.