Syed Nasir, Syed Norazizul and Jamian, Jasrul Jamani and Ayop, Razman (2021) Minimizing power loss considering bulk uncoordinated charging station operation. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12 (8). pp. 2019-2026. ISSN 1309-4653
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Official URL: https://turcomat.org/index.php/turkbilmat/article/...
Abstract
The widespread usage of electric vehicles (EV) carries a negative impact on the distribution network. Higher penetration of uncoordinated charging station (CS) that used to charge the EV may boost the capacity of demand, especially during off-peak. Next, an increase in power loss may occur since the bulk operation of CS causes a higher power flow at existing networks. Furthermore, the CS varying demand usually challenging to handle, uniquely for the load that has various behaviour. From repetitious researchers, the CS operation often installs at the residency, parking lot and specific station. Then, the charging power requirement is different between EV's, which depend on battery size and characteristic. This research focuses on power loss parameters at the distribution network for uncoordinated CS operation. The analysis will be based on the 48-bus radial distribution system with two residential blocks using MATLAB environment. Then, suitable sizing and placement of multiple passive filters used to minimize power loss with assistance metaheuristic technique and multi-objective approach. From the result, propose method able to improve up to 8.03% compared to existing power loss after implement optimal sizing and placement of passive filter. The proposed method is useful to assist utility owner in reducing power loss issues at a distribution system that cause by extensive uncoordinated CS operation.
Item Type: | Article |
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Additional Information: | 10.17762/turcomat.v12i8.3408 DOI not found |
Uncontrolled Keywords: | electric vehicles (EV), charging station (CS) |
Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
Divisions: | Electrical Engineering |
ID Code: | 97772 |
Deposited By: | Yanti Mohd Shah |
Deposited On: | 31 Oct 2022 08:37 |
Last Modified: | 31 Oct 2022 08:37 |
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