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Resilient Decentralized Control of Inverter-interfaced Distributed Energy Sources in Low-voltage Distribution Grids
Author(s)
Date Issued
2019-10-29
Date Available
2019-12-11T12:15:53Z
Abstract
Abstract: This paper shows that a relation can be found between the voltage at the terminals of an inverter-interfaced Renewable Energy Source (RES) and its optimal reactive power support. This relationship, known as Volt-Var Curve (VVC), enables the decentral operation of RES for Active Voltage Management (AVM). In this paper, the decentralized AVM technique is modified to consider the effects of the realistic operational constraints of RES. The AVM technique capitalizes on the reactive power support capabilities of inverters to achieve the desired objective in unbalanced active Low-Voltage Distribution Systems (LVDSs). However, as the results show, this AVM technique fails to satisfy the operator’s objective when the network structure dynamically changes. By updating the VVCs according to the system configuration and components’ availability, the objective functions will be significantly improved, and the AVM method remains resilient against the network changes. To keep the decentralized structure, the impedance identification capability of inverters is used to find the system configuration locally. Adaptive VVCs enable the decentralized control of inverters in an online setting. A real-life suburban residential LV-DS in Dublin, Ireland is used to showcasing the proposed method, and the effectiveness of the proposed resilient active voltage management technique is demonstrated.
Sponsorship
Science Foundation Ireland
Other Sponsorship
European Commission Irealnd
Type of Material
Journal Article
Publisher
Institution of Engineering and Technology
Journal
IET Smart Grid
Volume
3
Issue
2
Start Page
153
End Page
161
Copyright (Published Version)
2019 the Authors
Language
English
Status of Item
Peer reviewed
ISSN
2515-2947
This item is made available under a Creative Commons License
File(s)
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Name
Revised version Manuscript ID STG-2019-0163-V2.docx
Size
1.42 MB
Format
Unknown
Checksum (MD5)
760e6ac5614c5ca1326303dcadccb8f0
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