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Pre-sampled data based prediction control for active power filters

Zhongfu Zhou, Yanzhen Liu

International Journal of Electrical Power & Energy Systems, Volume: 37, Issue: 1, Pages: 13 - 22

Swansea University Author: Zhongfu Zhou

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DOI (Published version): 10.1016/j.ijepes.2011.10.029

Abstract

A prediction control was investigated of active power filter using pre-sampled data from previous fundamental cycle. Details of method was introduced. the advantages of the proposed method is eliminate the effect of time delay on the the filter performance. Details of hardware circuit and test resul...

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Published in: International Journal of Electrical Power & Energy Systems
ISSN: 01420615
Published: 2012
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URI: https://cronfa.swan.ac.uk/Record/cronfa35021
first_indexed 2017-08-25T18:48:55Z
last_indexed 2018-02-09T05:25:45Z
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spelling 2017-10-11T10:59:34.4052606 v2 35021 2017-08-25 Pre-sampled data based prediction control for active power filters 614fc57cde2ee383718d4f4c462b5fba Zhongfu Zhou Zhongfu Zhou true false 2017-08-25 A prediction control was investigated of active power filter using pre-sampled data from previous fundamental cycle. Details of method was introduced. the advantages of the proposed method is eliminate the effect of time delay on the the filter performance. Details of hardware circuit and test results were presented in the paper. Results show that the proposed prediction method is effective in compensation the phase delay of filter current. Journal Article International Journal of Electrical Power & Energy Systems 37 1 13 22 01420615 Active filter, Current control, Phase delay compensation, Harmonic current detection 9 1 2012 2012-01-09 10.1016/j.ijepes.2011.10.029 COLLEGE NANME COLLEGE CODE Swansea University 2017-10-11T10:59:34.4052606 2017-08-25T16:07:35.6035407 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Electronic and Electrical Engineering Zhongfu Zhou 1 Yanzhen Liu 2
title Pre-sampled data based prediction control for active power filters
spellingShingle Pre-sampled data based prediction control for active power filters
Zhongfu Zhou
title_short Pre-sampled data based prediction control for active power filters
title_full Pre-sampled data based prediction control for active power filters
title_fullStr Pre-sampled data based prediction control for active power filters
title_full_unstemmed Pre-sampled data based prediction control for active power filters
title_sort Pre-sampled data based prediction control for active power filters
author_id_str_mv 614fc57cde2ee383718d4f4c462b5fba
author_id_fullname_str_mv 614fc57cde2ee383718d4f4c462b5fba_***_Zhongfu Zhou
author Zhongfu Zhou
author2 Zhongfu Zhou
Yanzhen Liu
format Journal article
container_title International Journal of Electrical Power & Energy Systems
container_volume 37
container_issue 1
container_start_page 13
publishDate 2012
institution Swansea University
issn 01420615
doi_str_mv 10.1016/j.ijepes.2011.10.029
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Electronic and Electrical Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Electronic and Electrical Engineering
document_store_str 0
active_str 0
description A prediction control was investigated of active power filter using pre-sampled data from previous fundamental cycle. Details of method was introduced. the advantages of the proposed method is eliminate the effect of time delay on the the filter performance. Details of hardware circuit and test results were presented in the paper. Results show that the proposed prediction method is effective in compensation the phase delay of filter current.
published_date 2012-01-09T04:09:44Z
_version_ 1851092930079490048
score 11.089407

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