Reactive power planning for maximum load margin improvement using Fast Artificial Immune Support Vector Machine (FAISVM)
Load margin improvement is an important issue in power system planning and operation. This paper, first, presents a newly voltage stability index called Voltage Stability Condition Indicator (VSCI) to evaluate the voltage stability state of load buses in a system. It also proposes a fast optimizatio...
Saved in:
| Main Authors: | , , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Published: |
Praise Worthy Prize
2023
|
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1833410724980850688 |
|---|---|
| author | Aziz N.F.A. Abdul Rahman T.K. Zakaria Z. |
| author2 | 57221906825 |
| author_facet | 57221906825 Aziz N.F.A. Abdul Rahman T.K. Zakaria Z. |
| author_sort | Aziz N.F.A. |
| building | UNITEN Library |
| collection | Institutional Repository |
| content_provider | Universiti Tenaga Nasional |
| content_source | UNITEN Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Load margin improvement is an important issue in power system planning and operation. This paper, first, presents a newly voltage stability index called Voltage Stability Condition Indicator (VSCI) to evaluate the voltage stability state of load buses in a system. It also proposes a fast optimization algorithm for reactive power planning problem (RPP) through Fast Artificial Immune Support Vector Machine (FAISVM). FAISVM is a hybrid algorithm that incorporates the application of Artificial Immune System (AIS) and Support Vector Machine (SVM) in solving RPP problems. The newly proposed algorithm can determine the optimal tap settings of tap changing transformers, the value of reactive power injection at the reactive power sources and the injection at the reactive power generator buses. The performances of the techniques proposed were verified using the IEEE 30-bus test system and compared with another newly developed hybrid Evolutionary Support Vector Machine (ESVM). The simulation results have shown that FASIVM outperformed ESVM in terms of maximum load margin improvement and computation time significantly and also reduce active power losses. © 2014 Praise Worthy Prize S.r.l. - All rights reserved. |
| format | Article |
| id | my.uniten.dspace-22029 |
| institution | Universiti Tenaga Nasional |
| publishDate | 2023 |
| publisher | Praise Worthy Prize |
| record_format | dspace |
| spelling | my.uniten.dspace-220292023-05-16T10:46:47Z Reactive power planning for maximum load margin improvement using Fast Artificial Immune Support Vector Machine (FAISVM) Aziz N.F.A. Abdul Rahman T.K. Zakaria Z. 57221906825 8922419700 56276791800 Load margin improvement is an important issue in power system planning and operation. This paper, first, presents a newly voltage stability index called Voltage Stability Condition Indicator (VSCI) to evaluate the voltage stability state of load buses in a system. It also proposes a fast optimization algorithm for reactive power planning problem (RPP) through Fast Artificial Immune Support Vector Machine (FAISVM). FAISVM is a hybrid algorithm that incorporates the application of Artificial Immune System (AIS) and Support Vector Machine (SVM) in solving RPP problems. The newly proposed algorithm can determine the optimal tap settings of tap changing transformers, the value of reactive power injection at the reactive power sources and the injection at the reactive power generator buses. The performances of the techniques proposed were verified using the IEEE 30-bus test system and compared with another newly developed hybrid Evolutionary Support Vector Machine (ESVM). The simulation results have shown that FASIVM outperformed ESVM in terms of maximum load margin improvement and computation time significantly and also reduce active power losses. © 2014 Praise Worthy Prize S.r.l. - All rights reserved. Final 2023-05-16T02:46:47Z 2023-05-16T02:46:47Z 2014 Article 10.15866/ireaco.v7i5.2361 2-s2.0-84908345064 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84908345064&doi=10.15866%2fireaco.v7i5.2361&partnerID=40&md5=7cc3512445ed729db1d88741108ddfa8 https://irepository.uniten.edu.my/handle/123456789/22029 7 5 436 447 Praise Worthy Prize Scopus |
| spellingShingle | Aziz N.F.A. Abdul Rahman T.K. Zakaria Z. Reactive power planning for maximum load margin improvement using Fast Artificial Immune Support Vector Machine (FAISVM) |
| title | Reactive power planning for maximum load margin improvement using Fast Artificial Immune Support Vector Machine (FAISVM) |
| title_full | Reactive power planning for maximum load margin improvement using Fast Artificial Immune Support Vector Machine (FAISVM) |
| title_fullStr | Reactive power planning for maximum load margin improvement using Fast Artificial Immune Support Vector Machine (FAISVM) |
| title_full_unstemmed | Reactive power planning for maximum load margin improvement using Fast Artificial Immune Support Vector Machine (FAISVM) |
| title_short | Reactive power planning for maximum load margin improvement using Fast Artificial Immune Support Vector Machine (FAISVM) |
| title_sort | reactive power planning for maximum load margin improvement using fast artificial immune support vector machine (faisvm) |
| url_provider | http://dspace.uniten.edu.my/ |