Optimization-Based Dynamic Voltage Support of Microgrids Using Energy Storage Systems

  • Niranjan Bhujel
  • , Nischal Guruwacharya
  • , Ujjwol Tamrakar
  • , Raymond Byrne
  • , Timothy Hansen
  • , Donald Hummels
  • , Reinaldo Tonkoski

Research output: Contribution to journalArticlepeer-review

Abstract

A microgrid network is characterized by a high R/X ratio, making the voltage more sensitive to active power changes compared to bulk power systems, where the voltage is regulated primarily by reactive power. Due to its sensitivity, voltage control approaches for microgrids should also consider the active power input coupling, making it very different from conventional power systems. Additionally, as the energy costs associated with active and reactive powers are different and the operational conditions of microgrids connected to active distribution systems vary over time, the ideal controller to provide voltage support must be flexible enough to handle these technical and operational constraints. This paper proposes a model predictive control approach to provide dynamic voltage support using energy storage systems. This approach uses a simplified predictive model of the system to solve the model predictive control problem. By proper selection of model predictive control weighting parameters, the quality of service provided can be adjusted to achieve the desired performance. A simulation study in MATLAB/Simulink validates the proposed approach for the Cordova, Alaska microgrid. Results show that the performance of the voltage support can be adjusted depending on the choice of weight and constraints of the controller.
Original languageAmerican English
Pages (from-to)157918-157932
Number of pages15
JournalIEEE Access
Volume13
DOIs
StatePublished - 2025

NLR Publication Number

  • NREL/JA-5D00-97133

Keywords

  • dynamic state estimation
  • dynamic voltage support
  • model predictive control
  • moving horizon estimation
  • parameter estimation

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