A modified artificial neural network (ANN) algorithm to control shunt active power filter (SAPF) for current harmonics reduction
Proliferation of nonlinear loads /devices in power systems generates a major concern to power system engineers, courtesy of its severe contamination effects (polluting the distribution networks with current harmonics). This paper depicts artificial intelligence (AI) application on resolving the powe...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
IEEE
2013
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| Online Access: | http://psasir.upm.edu.my/id/eprint/68904/ http://psasir.upm.edu.my/id/eprint/68904/1/A%20modified%20artificial%20neural%20network%20%28ANN%29%20algorithm%20to%20control%20shunt%20active%20power%20filter%20%28SAPF%29%20for%20current%20harmonics%20reduction.pdf |
| _version_ | 1848856258745991168 |
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| author | Sabo, Aliyu Abdul Wahab, Noor Izzri Mohd Radzi, Mohd Amran Mailah, Nashiren Farzilah |
| author_facet | Sabo, Aliyu Abdul Wahab, Noor Izzri Mohd Radzi, Mohd Amran Mailah, Nashiren Farzilah |
| author_sort | Sabo, Aliyu |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Proliferation of nonlinear loads /devices in power systems generates a major concern to power system engineers, courtesy of its severe contamination effects (polluting the distribution networks with current harmonics). This paper depicts artificial intelligence (AI) application on resolving the power quality problem mentioned above by using the parallel active power filter (APF) strategy in two-wire distribution systems. The proposed AI adopted is an artificial neural network (ANN) responsible to detect current harmonics for the active power filtering process. The novelty control design is an artificial neural network (ANN) adopting a modified mathematical algorithm (a modified delta rule weight-updating W-H) and a suitable alpha value (learning rate value) which determines the filters optimal operation. The proposed scheme is achieved via simulation studies (under MATLAB SIMULINK environment) and results obtained are discussed to verify its performance. |
| first_indexed | 2025-11-15T11:38:48Z |
| format | Conference or Workshop Item |
| id | upm-68904 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T11:38:48Z |
| publishDate | 2013 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-689042019-06-11T02:03:40Z http://psasir.upm.edu.my/id/eprint/68904/ A modified artificial neural network (ANN) algorithm to control shunt active power filter (SAPF) for current harmonics reduction Sabo, Aliyu Abdul Wahab, Noor Izzri Mohd Radzi, Mohd Amran Mailah, Nashiren Farzilah Proliferation of nonlinear loads /devices in power systems generates a major concern to power system engineers, courtesy of its severe contamination effects (polluting the distribution networks with current harmonics). This paper depicts artificial intelligence (AI) application on resolving the power quality problem mentioned above by using the parallel active power filter (APF) strategy in two-wire distribution systems. The proposed AI adopted is an artificial neural network (ANN) responsible to detect current harmonics for the active power filtering process. The novelty control design is an artificial neural network (ANN) adopting a modified mathematical algorithm (a modified delta rule weight-updating W-H) and a suitable alpha value (learning rate value) which determines the filters optimal operation. The proposed scheme is achieved via simulation studies (under MATLAB SIMULINK environment) and results obtained are discussed to verify its performance. IEEE 2013 Conference or Workshop Item PeerReviewed text en http://psasir.upm.edu.my/id/eprint/68904/1/A%20modified%20artificial%20neural%20network%20%28ANN%29%20algorithm%20to%20control%20shunt%20active%20power%20filter%20%28SAPF%29%20for%20current%20harmonics%20reduction.pdf Sabo, Aliyu and Abdul Wahab, Noor Izzri and Mohd Radzi, Mohd Amran and Mailah, Nashiren Farzilah (2013) A modified artificial neural network (ANN) algorithm to control shunt active power filter (SAPF) for current harmonics reduction. In: 2013 IEEE Conference on Clean Energy and Technology (CEAT), 18-20 Nov. 2013, Langkawi, Kedah, Malaysia. (pp. 348-352). 10.1109/CEAT.2013.6775654 |
| spellingShingle | Sabo, Aliyu Abdul Wahab, Noor Izzri Mohd Radzi, Mohd Amran Mailah, Nashiren Farzilah A modified artificial neural network (ANN) algorithm to control shunt active power filter (SAPF) for current harmonics reduction |
| title | A modified artificial neural network (ANN) algorithm to control shunt active power filter (SAPF) for current harmonics reduction |
| title_full | A modified artificial neural network (ANN) algorithm to control shunt active power filter (SAPF) for current harmonics reduction |
| title_fullStr | A modified artificial neural network (ANN) algorithm to control shunt active power filter (SAPF) for current harmonics reduction |
| title_full_unstemmed | A modified artificial neural network (ANN) algorithm to control shunt active power filter (SAPF) for current harmonics reduction |
| title_short | A modified artificial neural network (ANN) algorithm to control shunt active power filter (SAPF) for current harmonics reduction |
| title_sort | modified artificial neural network (ann) algorithm to control shunt active power filter (sapf) for current harmonics reduction |
| url | http://psasir.upm.edu.my/id/eprint/68904/ http://psasir.upm.edu.my/id/eprint/68904/ http://psasir.upm.edu.my/id/eprint/68904/1/A%20modified%20artificial%20neural%20network%20%28ANN%29%20algorithm%20to%20control%20shunt%20active%20power%20filter%20%28SAPF%29%20for%20current%20harmonics%20reduction.pdf |