An Improved Adaptive Coordination Control of Wind Integrated Multi-terminal HVdc System

Qingqing Yang, Jun Shen, Jianwei Li, Hongwen He, Zhongbao Wei, Petar Igic

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)
85 Downloads (Pure)

Abstract

The increasing penetration of the renewables and integration of the power electronic devices leads to lower system inertia, which is changeling the system stability of a multiterminal HVdc (MTdc) system. This article presents an improved adaptive predictive control with the multiobjective targets coordinating the key parameters that the dc voltage, ac frequency and power-sharing among the terminals in MTdc system. Specifically, we contribute two main points to the relevant literature, with the purpose of distinguishing our study from existing ones. First, the proposed method is based on minimal information exchange by only considering neighboring terminals. Second, the adaptive control is achieved by setting a weighted fitness function to adaptively tune the weights with the effective integration of the trust-region and particle swarm optimization. A four-Terminal HVdc system built within the IEEE 30-bus ac system is used as the study case to validate the robustness and efficiency of the proposed method. In the case study regarding the multiobjective fitness function, the proposed approach benefits in suppressing the voltage deviation, providing frequency support and establishing an automatically updated power equilibrium leveraging by the adaptive parameters.

Original languageEnglish
Pages (from-to)5490-5499
Number of pages10
JournalIEEE Transactions on Power Electronics
Volume38
Issue number4
Early online date30 Dec 2022
DOIs
Publication statusPublished - 1 Apr 2023

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This document is the author’s post-print version, incorporating any revisions agreed during the peer-review process. Some differences between the published version and this version may remain and you are advised to consult the published version if you wish to cite from it.

Keywords

  • Coordination control
  • hybrid system
  • model predictive control
  • particle swarm optimisation
  • wind generation

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