A New Strategy for Potential Smart Grids to Alleviate Heavy EV Charging Demand in Residential Areas Piyush Kaloriya, Nikhil Gupta, Shakti Vashisth, K. R. Niazi, Anil Swarnkar Department of Electrical Engineering, Malaviya National Institute of Technology Jaipur Email: kaloriyapiyush27@gmail.com, nikhilgupta.ee@mnit.ac.in, shaktivashistha@gmail.com, krniazi.ee@mnit.ac.in, mnit.anil@gmail.com Abstract—The overwhelming response to electric vehicles (EVs) shall lead to faster replacement of personal and commercial gasoline vehicles. The study shows that most of the EV owners prefer home charging during the evening hours. The significant EV charging load may coincide with the peak demand of the residential area. This may adversely affect the planning and operation of local distribution grids. This paper addresses coordinated home charging of EVs to minimize its impact on the residential area and grid. The proposed method employs a definite delay among all EV charging results in maintaining the peak demand and smoothing the demand profile without using distributed energy resources, complex charging strategies, or high-level artificial intelligence while relaxing the EV owners. The simulation results on a standard test distribution system reveal that more EVs can be accommodated for home charging without altering the peak demand of the residential area and the grid. Index Terms—Distribution systems, electric vehicles, home charging, residential area NOMENCLATURE E(i, k) Charging energy of the ith EV at the kth residential node (kWh) N EV Total number of EVs in the residential area N R Total number of residential nodes in the distribution system P EV (i, k, t) Power demand of the ith EV at the kth residential node at time t (kW) P EV (t) Total power demand of EVs at time t (kW) P r (i, k) Charger rating of the ith EV feeding from the kth residential node (kW) SOC AR (i, k) Arrival SOC level of the ith EV at the kth residential node SOC (i, k, t) SOC level of the ith EV at the kth residential node at time t SOC F Maximum SOC level of EVs SOC REQ (i, k) Required SOC level of the ith EV charg- ing at the kth residential node SOC min AR /SOC max AR Lower/Upper bound of the arrival SOC level of EVs T AR (i, k) Arrival time of the ith EV at the kth residential node (min) T min AR /T max AR Lower/Upper bound of the arrival time of EVs (min) T C (i, k) Total charging time taken by the ith EV at the kth residential node (min) T S (i, k)/T E (i, k) Initial/Final charging time of the ith EV at the kth residential node (min) T D Delay time (min) t C Fictitious arrival time of the ith EV at the kth residential node considering delay time (min) β(i, k) Battery capacity of the ith EV charging at the kth residential node (kWh) η CH Charging efficiency of EV battery μ AR Mean arrival time of all EVs in the residential area (min) μ SOC AR Mean SOC level of all EVs in the resi- dential area σ AR Standard deviation of all EVs in the residential area (min) σ SOC AR Standard deviation of arrival SOC levels of all EVs in the residential area τ a /τ b Lower/Upper bound of the EV arrival (min) I. I NTRODUCTION Electric vehicles (EVs) have been gaining significant atten- tion due to their potential to address the global energy crisis and reduce greenhouse gas emissions [1]. The recent devel- opment in electric motor design and control and the declining trend in EV battery cost would increase EV penetration level in transport systems. Electric Power Research Institute esti- mates that the EV penetration level in transportation systems can reach 35%, 51%, and 62% by 2020, 2030, and 2050, respectively [2]. But, this proliferation of EVs will impose significant power demand on the distribution systems. The EVs will be connected to the local grid via public or private chargers, and the existing grid will likely be used to support the EV charging demand in residential areas [3]. However, EV charging demand is usually much more significant than general household appliances, most of which are concentrated in residential areas during night hours. Without EV charging coordination, residential peak demand hours will overlap with IEEE - 56998 14th ICCCNT IEEE Conference July 6-8, 2023 IIT - Delhi, Delhi th 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT) | 979-8-3503-3509-5/23/$31.00 ©2023 IEEE | DOI: 10.1109/ICCCNT56998.2023.10307293 Authorized licensed use limited to: Malaviya National Institute of Technology Jaipur. Downloaded on December 15,2023 at 18:52:54 UTC from IEEE Xplore. Restrictions apply.