Kalman filter-based power compensation strategy for Microgrids under uncertain disturbance

Jingxuan Wu*, Josep M. Guerrero, Amir Basati, Juan C. Vasquez, Shuting Li

*Corresponding author for this work

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

2 Citations (Scopus)

Abstract

The measurement and model errors always exist in the sample or data analysis part of Microgrids (MGs) system, bringing oscillation and inaccuracy to the controller and energy management system (EMS). This paper proposed a Kalman
filter (KF)-based control strategy for the battery energy storage system (BESS) in MGs with integrated renewable energy sources. The control scheme aims at minimizing the active and reactive power purchased from the main grid by regulating the output current of BESS. A detailed model of a wind-PV-battery
MG is built, and the sampling and measurement inaccuracy is considered. The control strategy is tested under rapid power supply oscillation and load changes, and the results show good performance.
Original languageEnglish
Title of host publicationSEST 2022 - 5th International Conference on Smart Energy Systems and Technologies : SEST 2022
PublisherIEEE
Publication date28 Sept 2022
ISBN (Electronic)9781665405577
DOIs
Publication statusPublished - 28 Sept 2022

Keywords

  • Battery Energy Storage
  • Kalman filter (KF)
  • Microgird
  • Renewable

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