Hierarchical Optimization Method for Energy Scheduling of Multiple Microgrids

• Main Authors: Tao Rui, Guoli Li, Qunjing Wang, Cungang Hu, Weixiang Shen, Bin Xu
• Format: Article
• Language: English
• Published: MDPI AG 2019-02-01
• Series: Applied Sciences
• Subjects: multiple microgrid; rolling optimization; Stackelberg game; price mechanism
• Online Access: https://www.mdpi.com/2076-3417/9/4/624

This paper proposes a hierarchical optimization method for the energy scheduling of multiple microgrids (MMGs) in the distribution network of power grids. An energy market operator (EMO) is constructed to regulate energy storage systems (ESSs) and load demands in MMGs. The optimization process is divided into two stages. In the first stage, each MG optimizes the scheduling of its own ESS within a rolling horizon control framework based on a long-term forecast of the local photovoltaic (PV) output, the local load demand and the price sent by the EMO. In the second stage, the EMO establishes an internal price incentive mechanism to maximize its own profits based on the load demand of each MG. The optimization problems in these two stages are solved using mixed integer programming (MIP) and Stackelberg game theory, respectively. Simulation results verified the effectiveness of the proposed method in terms of the promotion of energy trading and improvement of economic benefits of MMGs.