Open AccessOptimal EV Charging Strategy for Distribution Networks Load Balancing In a Smart Grid Using Dynamic Charging Price
Author(s) -
Leloko J. Lepolesa,
Kayode E. Adetunji,
Khmaies Ouahada,
Zhenqing Liu,
Ling Cheng
Publication year - 2024
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2024.3382124
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
The adoption of electric vehicles (EVs) promises a reduction of carbon emissions and a crucial step towards a cleaner environment. While more EVs are expected to replace internal combustion engine vehicles to operate on the road worldwide, their adoption is inhibited by factors such as high power demand. Unregulated or poorly regulated charging of EVs can cause grid instability, especially in grids that were not initially designed to handle the charging of EVs. This calls for leveraging the available grid resources to control the charging of EVs in a manner that ensures optimal grid operation. This work proposes a distribution network-level dynamic pricing strategy for charging EVs to optimally utilize the distribution network and balance the load between residential and commercial/industrial distribution networks. Different EV charging probabilities that cause the EV load to differ from the optimal state with a mean average percentage error (MAPE) as high as 30% are explored. Simulation results show that with the dynamic pricing strategy as an incentive to the EVs users, EVs charging load will contribute to the optimal grid resources utilization.