Energy management for multi-microgrid system based on model predictive control

  • Ke-yong HuEmail author
  • Wen-juan Li
  • Li-dong Wang
  • Shi-hua Cao
  • Fang-ming Zhu
  • Zhou-xiang Shou


To reduce the computation complexity of the optimization algorithm used in energy management of a multi-microgrid system, an energy optimization management method based on model predictive control is presented. The idea of decomposition and coordination is adopted to achieve the balance between power supply and user demand, and the power supply cost is minimized by coordinating surplus energy in the multi-microgrid system. The energy management model and energy optimization problem are established according to the power flow characteristics of microgrids. A dual decomposition approach is imposed to decompose the optimization problem into two parts, and a distributed predictive control algorithm based on global optimization is introduced to achieve the optimal solution by iteration and coordination. The proposed method has been verified by simulation, and simulation results show that the proposed method provides the demanded energy to consumers in real time, and improves renewable energy efficiency. In addition, the proposed algorithm has been compared with the particle swarm optimization (PSO) algorithm. The results show that compared with PSO, the proposed method has better performance, faster convergence, and significantly higher efficiency.

Key words

Microgrids Energy management Predictive control Renewable energy Controllable energy 

CLC number



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Copyright information

© Editorial Office of Journal of Zhejiang University Science and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Qianjiang CollegeHangzhou Normal UniversityHangzhouChina
  2. 2.MOE Key Laboratory of Special Purpose Equipment and Advanced Manufacturing TechnologyZhejiang University of TechnologyHangzhouChina
  3. 3.School of Information Science and EngineeringHangzhou Normal UniversityHangzhouChina

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