English
 
Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Black-Box Impedance Prediction of Grid-Tied VSCs Under Variable Operating Conditions

Qiu, Q., Huang, Y., Ma, R., Kurths, J., Zhan, M. (2022): Black-Box Impedance Prediction of Grid-Tied VSCs Under Variable Operating Conditions. - IEEE Access, 10, 1289-1304.
https://doi.org/10.1109/ACCESS.2021.3139435

Item is

Files

show Files
hide Files
:
27044oa.pdf (Publisher version), 3MB
Name:
27044oa.pdf
Description:
-
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
-

Locators

show

Creators

show
hide
 Creators:
Qiu, Qi 1, Author
Huang, Yifan 1, Author
Ma, Rui 1, Author
Kurths, Jürgen2, Author              
Zhan, Meng 1, Author
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

Content

show
hide
Free keywords: -
 Abstract: Impedance/admittance models (IM/AMs) have been widely used to analyze the small-signal stability of grid-tied power electronic devices, such as the voltage source converter (VSC). They can be either derived from theoretical analysis under white-box conditions, where all parameters and control structures are fully known, or measured based on experiments under black-box conditions, where the topology and parameters of the controllers are completely unknown. As the IM/AMs depend on specific operating conditions, it is highly desirable to develop fast algorithms for IM/AM prediction (or estimation) under the black-box and variable-operating-point conditions. This article extends the nearly-decoupled AM method for sequence AMs proposed recently by Liu et al to fit any unknown control structure, including not only grid-following VSC, but also grid-forming VSC. It is, therefore, referred to as the fully-decoupled IM (FDIM) method. Furthermore, a curve fitting method for the transfer function is proposed to expedite the algorithm, based on the information of a few disturbance frequencies only. Finally, the algorithm is verified by wide simulations and experiments under different situations, including the direct-drive wind turbine generator. The whole approach is expected to be broadly applicable to the stability analysis of power-electronic-based power systems under variable operating conditions.

Details

show
hide
Language(s): eng - English
 Dates: 2021-12-302022-01-06
 Publication Status: Finally published
 Pages: 16
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1109/ACCESS.2021.3139435
MDB-ID: No data to archive
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
Research topic keyword: Complex Networks
Research topic keyword: Energy
Research topic keyword: Nonlinear Dynamics
Working Group: Network- and machine-learning-based prediction of extreme events
OATYPE: Gold Open Access
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: IEEE Access
Source Genre: Journal, SCI, Scopus, p3
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 10 Sequence Number: - Start / End Page: 1289 - 1304 Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/1803142
Publisher: Institute of Electrical and Electronics Engineers (IEEE)