Staffordshire University logo
STORE - Staffordshire Online Repository

A Smart Fault Detection and Localization Strategy of Modular Multi-Level Converters for HVDC Networks

Abdelsalam, M., Tennakoon, S.B., Griffiths, A.L. and Marei, M.I. (2017) A Smart Fault Detection and Localization Strategy of Modular Multi-Level Converters for HVDC Networks. In: 5th IET International Conference on Renewable Power Generation (RPG) 2016, 21-23 Sept. 2016, London, UK.

[img] Text
07835513.pdf - AUTHOR'S ACCEPTED Version (default)
Restricted to Repository staff only
Available under License All Rights Reserved.

Download (589kB) | Request a copy

Abstract or description

This paper presents a new fault detection and localization strategy for Modular multilevel converters (MMC). The proposed fault detection technique depends on the estimation of the sub-module capacitor voltages using the RLS algorithm without the need of extra sensors or special power circuits. The dynamic performance of the proposed strategy is investigated using hardware in the loop (HIL) based on an OPAL-RT real time digital simulator and a cRIO FPGA controller. The real-time simulation results clearly show the robustness of the proposed technique in terms of accuracy and time which significantly enhances the reliability of the MMC.

Item Type: Conference or Workshop Item (Paper)
Additional Information: © 2016 IEEE
Faculty: School of Creative Arts and Engineering > Engineering
Event Title: 5th IET International Conference on Renewable Power Generation (RPG) 2016
Event Location: London, UK
Event Dates: 21-23 Sept. 2016
Depositing User: Alison GRIFFITHS
Date Deposited: 18 Feb 2019 14:00
Last Modified: 24 Feb 2023 13:53
URI: https://eprints.staffs.ac.uk/id/eprint/5113

Actions (login required)

View Item View Item

DisabledGo Staffordshire University is a recognised   Investor in People. Sustain Staffs
Legal | Freedom of Information | Site Map | Job Vacancies
Staffordshire University, College Road, Stoke-on-Trent, Staffordshire ST4 2DE t: +44 (0)1782 294000