A Model Predictive Control for Renewable Energy Based AC Microgrids without Any PID Regulators

Yinghao Shan, Jiefeng Hu, Zilin Li, Josep M. Guerrero

Research output: Journal article publicationJournal articleAcademic researchpeer-review

40 Citations (Scopus)

Abstract

This letter presents a novel model predictive control strategy without involving any proportional-integral-differential regulators for practical renewable energy based ac microgrids. The proposed method consists of a model predictive power control (MPPC) scheme and a model predictive voltage control (MPVC) scheme. By controlling the bidirectional buck-boost converters of the battery energy storage systems based on the MPPC algorithm, the fluctuating output from the renewable energy sources can be smoothed, while stable dc-bus voltages can be maintained as the inverters' inputs. Then, the parallel inverters are controlled by using a combination of the MPVC scheme and the droop method to ensure stable ac voltage output and proper power sharing. Compared with the traditional cascade control, the proposed method is simpler and shows better performance, which is validated in simulation on MATLAB/Simulink and on real-time laboratory platform.

Original languageEnglish
Article number8329538
Pages (from-to)9122-9126
Number of pages5
JournalIEEE Transactions on Power Electronics
Volume33
Issue number11
DOIs
Publication statusPublished - 1 Nov 2018

Keywords

  • DC-AC
  • DC-DC
  • droop control
  • energy storage system
  • microgrid
  • model predictive control (MPC)
  • real-time laboratory (RT-LAB)

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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