Distributed Predictive Secondary Control With Soft Constraints for Optimal Dispatch in Hybrid AC/DC Microgrids

Alex Navas-Fonseca, Claudio Burgos-Mellado, Juan S. Gomez, Enrique Espina, Jacqueline Llanos, Doris Saez, Mark Sumner, Daniel E. Olivares

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


Hybrid AC/DC microgrids (H-MGs) are a prominent solution for integrating distributed generation and modern AC and DC loads. However, controlling these systems is challenging as multiple electrical variables need to be controlled and coordinated. To provide flexibility to the control system, these variables can be regulated to specific values or within secure bands. This paper proposes a set of distributed model predictive control schemes for the secondary control level to control certain variables to specific values and other variables within secure pre-defined bands into H-MGs. Specifically, optimal dispatch of active and reactive power is achieved while frequency and voltages are regulated within secure bands in H-MGs. Dynamic models of AC generators, DC generators and interlinking converters along with their novel multi-objective cost functions are developed in constrained distributed predictive optimisation problems to simultaneously achieve the aforementioned objectives via information sharing. Extensive simulation work validates the performance of this proposal.

Original languageEnglish
Pages (from-to)4204-4218
Number of pages15
JournalIEEE Transactions on Smart Grid
Issue number6
Publication statusPublished - 1 Nov 2023


  • distributed predictive control
  • Hybrid AC/DC microgrids
  • predictive optimal dispatch
  • secondary controllers

ASJC Scopus subject areas

  • General Computer Science


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