Comparison of Grid Reactive Voltage Regulation with Reconfiguration Network for Electric Vehicle Penetration
Renewable energy sources and EV growth brings new challenges for grid stabilization. Smart grid techniques are required to reconfigure and compensate for load fluctuation and stabilize power losses and voltage fluctuation. Numerical tools are available to equip the smart grid to deal with such chall...
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2023
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| author | Nagi F. Azwin A. Boopalan N. Ramasamy A.K. Marsadek M. Ahmed S.K. |
| author2 | 56272534200 |
| author_facet | 56272534200 Nagi F. Azwin A. Boopalan N. Ramasamy A.K. Marsadek M. Ahmed S.K. |
| author_sort | Nagi F. |
| building | UNITEN Library |
| collection | Institutional Repository |
| content_provider | Universiti Tenaga Nasional |
| content_source | UNITEN Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Renewable energy sources and EV growth brings new challenges for grid stabilization. Smart grid techniques are required to reconfigure and compensate for load fluctuation and stabilize power losses and voltage fluctuation. Numerical tools are available to equip the smart grid to deal with such challenges. Distribution Feeder reconfiguration and reactive voltage injection to the disturbed grid are some of the techniques employed for the purpose. However, either reconfiguration or injection alone is used commonly for this purpose. In this study, both techniques are applied to EV penetration as load and compared. A balanced IEEE 33 Radial network is used in this study and selected branches with high power losses are targeted for the reactive voltage injection and Minimum Spanning tree techniques (MST). EV charging loads are usually modelled with time base distribution which requires times base power flow analysis for reactive power injection. A comparison between coordinated, reconfiguration, and reactive voltage injection shows differences in power losses, voltage distortion, and cost saving. The analysis is carried out with an integer linear programming technique for coordinated charging, a minimum spanning tree for network reconfiguration, and genetic optimization for reactive power injection. Besides, all power flow analyses are carried out with the Backward/Forward sweep method. The information would help lowering power losses, grid stabilization, and charging station infrastructure planning. � 2022 by the authors. |
| format | Article |
| id | my.uniten.dspace-26728 |
| institution | Universiti Tenaga Nasional |
| publishDate | 2023 |
| publisher | MDPI |
| record_format | dspace |
| spelling | my.uniten.dspace-267282023-05-29T17:36:22Z Comparison of Grid Reactive Voltage Regulation with Reconfiguration Network for Electric Vehicle Penetration Nagi F. Azwin A. Boopalan N. Ramasamy A.K. Marsadek M. Ahmed S.K. 56272534200 57201882059 57211414491 16023154400 26423183000 25926812900 Renewable energy sources and EV growth brings new challenges for grid stabilization. Smart grid techniques are required to reconfigure and compensate for load fluctuation and stabilize power losses and voltage fluctuation. Numerical tools are available to equip the smart grid to deal with such challenges. Distribution Feeder reconfiguration and reactive voltage injection to the disturbed grid are some of the techniques employed for the purpose. However, either reconfiguration or injection alone is used commonly for this purpose. In this study, both techniques are applied to EV penetration as load and compared. A balanced IEEE 33 Radial network is used in this study and selected branches with high power losses are targeted for the reactive voltage injection and Minimum Spanning tree techniques (MST). EV charging loads are usually modelled with time base distribution which requires times base power flow analysis for reactive power injection. A comparison between coordinated, reconfiguration, and reactive voltage injection shows differences in power losses, voltage distortion, and cost saving. The analysis is carried out with an integer linear programming technique for coordinated charging, a minimum spanning tree for network reconfiguration, and genetic optimization for reactive power injection. Besides, all power flow analyses are carried out with the Backward/Forward sweep method. The information would help lowering power losses, grid stabilization, and charging station infrastructure planning. � 2022 by the authors. Final 2023-05-29T09:36:22Z 2023-05-29T09:36:22Z 2022 Article 10.3390/electronics11193221 2-s2.0-85139848309 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85139848309&doi=10.3390%2felectronics11193221&partnerID=40&md5=8caeec2fd3028a52a4ea0ea5956df460 https://irepository.uniten.edu.my/handle/123456789/26728 11 19 3221 All Open Access, Gold MDPI Scopus |
| spellingShingle | Nagi F. Azwin A. Boopalan N. Ramasamy A.K. Marsadek M. Ahmed S.K. Comparison of Grid Reactive Voltage Regulation with Reconfiguration Network for Electric Vehicle Penetration |
| title | Comparison of Grid Reactive Voltage Regulation with Reconfiguration Network for Electric Vehicle Penetration |
| title_full | Comparison of Grid Reactive Voltage Regulation with Reconfiguration Network for Electric Vehicle Penetration |
| title_fullStr | Comparison of Grid Reactive Voltage Regulation with Reconfiguration Network for Electric Vehicle Penetration |
| title_full_unstemmed | Comparison of Grid Reactive Voltage Regulation with Reconfiguration Network for Electric Vehicle Penetration |
| title_short | Comparison of Grid Reactive Voltage Regulation with Reconfiguration Network for Electric Vehicle Penetration |
| title_sort | comparison of grid reactive voltage regulation with reconfiguration network for electric vehicle penetration |
| url_provider | http://dspace.uniten.edu.my/ |