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Distributed robust data-enabled predictive control based voltage control for networked microgrid system
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DOI：10.1016/j.epsr.2024.110360.png)
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Abstract
En 中文
The networked microgrid system (NMG) has become an effective alternative for integrating various types of distributed energy resources (DERs). However, because of the increasing share of DERs and high R/X ratio in the system, the uncertainty and variability of DERs ' power generation may cause significant voltage violations in the system. To address these issues, this paper introduces a novel distributed data-driven voltage control strategy based on data-enabled predictive control (DeePC) to address voltage violations problems in the NMG. The DeePC algorithm uses only historical system trajectories, eliminating the need for parameter identification procedures of power system. Based on the system data model, the proposed controller coordinates MGs in the NMG in a distributed manner by employing a consensus version of the fast alternating direction method of the multiplier algorithm (FADMM), which achieves a better privacy and scalability. Simulation studies in a modified two-MG NMG demonstrate the effectiveness and superiority of the proposed algorithm.
Keywords:
Data-driven control
Distributed control
Networked microgrid system
Voltage control
fast alternating direction method of the multiple (FADMM)
Journal
IF:
4.2
Papers:
1.1W
Citations:
2.2W