Robust model predictive control based voltage regulation method for a distribution system with renewable energy sources and energy storage systems

Yunyun Xie, Lin Liu, Qiuwei Wu*, Qian Zhou

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

With the integration of high penetration renewable energy sources (RESs) in distribution networks, the uncertainty of RES outputs brings a great challenge for the voltage regulation of distribution systems. This paper proposes a method based on robust model predictive control (RMPC) for voltage regulation by optimally coordinating the reactive power outputs of the RESs, energy storage systems and on-load tap changers (OLTCs). By considering the prediction error of the RES active outputs, the voltage regulation problem is formulated as a multitime period robust optimization model to obtain the optimal control actions in the prediction horizon. The control actions for the first time period are applied to the distribution network. Since the RMPC-based optimization model is nonlinear, it is linearized and transformed into a quadratic programming model that can be solved effectively by commercial software. The effectiveness of the proposed method is demonstrated in a real Finnish distribution network model.

Original languageEnglish
Article number105749
JournalInternational Journal of Electrical Power and Energy Systems
Volume118
Number of pages17
ISSN0142-0615
DOIs
Publication statusPublished - 1 Jun 2020

Keywords

  • Model predictive control
  • Robust optimization
  • Strong duality theory
  • Voltage control

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