A Novel Beluga Whale-Jaya Optimization for Effective EV Charge Scheduling in Power Generation

While considering the provision of the safest environment, it leads to the rapid growth of Electric Vehicles (EVs) that spread over the markets based on features like improvement of charging stations, economy, battery technology, and price. Moreover, the EV charging station placement issues are rega...

Full description

Bibliographic Details
Published in:2023 IEEE 14th International Conference on Power Electronics and Drive Systems (PEDS)
Main Authors: Sagar A., Padmanaban S., Bertoluzzo M.
Other Authors: Sagar, A., Padmanaban, S., Bertoluzzo, M.
Format: Conference Object
Language:English
Published: Institute of Electrical and Electronics Engineers Inc. 2023
Subjects:
Online Access:https://hdl.handle.net/11577/3498940
https://doi.org/10.1109/PEDS57185.2023.10246690
Description
Summary:While considering the provision of the safest environment, it leads to the rapid growth of Electric Vehicles (EVs) that spread over the markets based on features like improvement of charging stations, economy, battery technology, and price. Moreover, the EV charging station placement issues are regarded as facility location issues. In addition, EV charging station placement issues have concerns about the electric distribution systems, the system losses, and the total number of convergences over the traffic network for voltage deviations. The voltage profile enhancement and loss minimization are considered two major issues obtained over the distributed model and are commonly equipped along with the shunt capacitors for reactive power compensations. A novel EV charging model is developed based on hybrid optimization approaches to tackle the issue. The charge level parameters of regional EV charging schedules are tuned with the help of a developed hybrid approach named Beluga Whale-Jaya Optimization (BWJO) derived via Beluga whale optimization (BWO) and JAYA optimization (JA) to attain the minimization of greenhouse gas emission acquired from electricity. Thus, the developed model has offered an enhanced performance rate when contrasted with conventional EV charging schedules schemes.