Robust Coordinated Optimization With Adaptive Uncertainty Set for a Multi-Energy Microgrid

Junjie Zhong, Yong Li, Yijia Cao, Yi Tan, Yanjian Peng, Yicheng Zhou, Yosuke Nakanishi, Zhengmao Li

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


With the increasing integration of the multi-energy microgrid (MEM) with the distribution network (DN), the distributed coordination between MEM and DN becomes critical. This paper proposes a distributed scheduling method for the coupled MEM-DN under operational uncertainties. First, a worst-expectation min-max-max-min robust optimization model is formulated for MEM considering the uncertainties of renewable distributed generation (wind and photovoltaic) as well as its class probability. Second, the column and constraint generation algorithm with an alternating iteration strategy (C&CG-AIS) is proposed to accelerate the solution by decoupling the subproblems. Third, the multi-interval convex hull uncertainty set (MCHUS) is proposed to reduce the conservatism of robust optimization by decreasing the low-probability scenarios. Furthermore, the Bregman alternating direction method with multipliers (BADMM) is combined with the alternating optimization procedure (AOP) to overcome the convergence difficulty in the nonconvex distributed MEM-DN model. Finally, the effectiveness of the proposed model and method is verified by simulation tests based on IEEE-33 node DN and a park-level MEM.

Original languageEnglish
Pages (from-to)111-124
Number of pages14
JournalIEEE Transactions on Sustainable Energy
Issue number1
Publication statusPublished - 2023 Jan 1


  • Distributed operation
  • energy hub
  • multi-energy microgrid
  • robust optimization
  • uncertainty sets

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment


Dive into the research topics of 'Robust Coordinated Optimization With Adaptive Uncertainty Set for a Multi-Energy Microgrid'. Together they form a unique fingerprint.

Cite this