The week's pick
Reseach Article
Peak Load Management of Plug-in Electric Vehicle: An Online Coordinated Charging Approach
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 186 - Number 13 |
| Year of Publication: 2024 |
| Authors: Seyed M.H. Nabavi, Somayeh Hajforoosh |
10.5120/ijca2024923494
|
Seyed M.H. Nabavi, Somayeh Hajforoosh . Peak Load Management of Plug-in Electric Vehicle: An Online Coordinated Charging Approach. International Journal of Computer Applications. 186, 13 ( Mar 2024), 1-7. DOI=10.5120/ijca2024923494
Abstract
Electric utilities are increasingly concerned about the disruptive effects of uncoordinated plug-in electric vehicle (PEV) charging on smart grids (SGs), especially during peak load periods. This paper presents the implementation of an online coordinated charging genetic algorithm (OL-CC-GA) for PEVs within SGs, capable of accommodating delayed charging scenarios (e.g., partial-overnight or full-overnight) to alleviate distribution transformer loading. The proposed algorithm aims to minimize total costs associated with energy generation and grid losses, while simultaneously maximizing the number of PEVs charged within each time interval (e.g., Δt=5min), accounting for distribution transformer loading and voltage regulation limits. Detailed simulations are conducted on a 19-node test feeder populated with PEVs using the OL-CC-GA method, and results are compared against uncoordinated and delayed charging strategies. The findings demonstrate the efficacy of the proposed OL-CC-GA approach in mitigating adverse impacts on SGs, enhancing grid stability, and optimizing PEV charging operations in a cost-effective manner. This research contributes to the ongoing discourse on sustainable transportation integration into smart grid frameworks, offering valuable insights for utilities and policymakers seeking to address the challenges posed by PEV adoption while maximizing grid efficiency and reliability.
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