Economic Model Predictive Control for Microgrid Optimization: A Review

Jiefeng Hu, Yinghao Shan, Yong Yang, Alessandra Parisio, Yong Li, Nima Amjady, Syed Islam, Ka Wai Cheng, Josep M. Guerrero, José Rodríguez

Research output: Contribution to journalArticlepeer-review


Microgrids have emerged as a promising solution to integrate distributed energy resources (DERs) and supply reliable and efficient electricity. The operation of a microgrid involves the coordination of different DERs and loads. To date, various control methods have been developed to maximize the overall benefit while satisfying various constraints. Now it is urgently needed to understand and comprehend these approaches to further stimulate the deployment of microgrids. This paper presents an overview for researchers on economic model predictive control (EMPC) methods of microgrids to achieve a variety of objectives such as cost minimization and benefit maximization. The fundamental principle of the EMPC theory is explained in detail. The most popular and important strategies applied to stand-alone microgrids, grid-connected microgrids, residential smart homes, as well as networked microgrids are discussed. Future trends are also highlighted.
Original languageEnglish
Pages (from-to)1-1
JournalIEEE Transactions on Smart Grid
Early online date11 Apr 2023
Publication statusE-pub ahead of print - 11 Apr 2023


  • Energy management
  • Energy storage
  • Generators
  • Load modeling
  • Microgrids
  • Renewable energy sources
  • Wind turbines
  • energy management
  • model predictive control
  • renewable energy


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