Dual-Boost Inverter for PV Microinverter Application—An Assessment of Control Strategies

Diana Lopez-Caiza, Hugues Renaudineau, Nicolas Muller, Freddy Flores-Bahamonde, Samir Kouro, Jose Rodriguez

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


Photovoltaic (PV) microinverters have grown rapidly in the small-scale PV market, where typical two-stage converters are used to connect one PV module to the single-phase AC grid. This configuration achieves better performance in terms of energy yield compared with other PV configu-rations. However, the conversion efficiency of a two-stage system is the main drawback, especially when a high-voltage gain effort is required. In this context, single-stage microinverter topologies have been recently proposed since only one power conversion stage is required to extract the maximum power of the PV module and inject the AC power to the grid. This single-stage configuration allows considerable improvement of the overall efficiency of microinverters by reducing the number of elements in the system. However, the main challenge of these topologies is their control, since all variables of the converter are composed by the AC waveform with DC-bias. In this paper, four control strategies are analyzed for the mainstream single-stage topology, which is the dual-boost inverter (DBI). Classical linear control and three non-linear strategies, namely finite control set–model predictive control, flatness-based control, and sliding mode control, are detailed. The main contribution of this work is a complete comparison of the control strategies, to give insights into the most suitable control strategy for the DBI in PV microinverter application.

Original languageEnglish
Article number5952
JournalApplied Sciences (Switzerland)
Issue number12
Publication statusPublished - 1 Jun 2022


  • FCS–model predictive control
  • flatness-based control
  • photovoltaic energy
  • PV microinverter
  • single-stage topologies
  • sliding mode control

ASJC Scopus subject areas

  • Materials Science(all)
  • Instrumentation
  • Engineering(all)
  • Process Chemistry and Technology
  • Computer Science Applications
  • Fluid Flow and Transfer Processes


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