Improve power quality of charging station unit using African vulture optimization algorithm

Saleh Masoud Abdallah Altbawi (Universiti Teknologi Malaysia)
Saifulnizam Abdul Khalid (Universiti Teknologi Malaysia)
Ahmad Safawi Mokhtar (Universiti Teknologi Malaysia)
Rayan Hamza Alsisi (Islamic University of Madinah)
Zeeshan Ahmad Arfeen (The Islamia University of Bahawalpur)
Hussain Shareef (United Arab Emirates University)
Mehreen Kausar Azam (Institute of Business Management Sindh)

Bulletin of Electrical Engineering and Informatics
Vol 12, No 5: October 2023

In recent years, there is growth in acceptance to consume fewer fossil fuels globally and the manufacturing of electric vehicles (EVs) has become more popular. However, the increase in the number of systems connected to the grid that contain EVs with a huge power capacity leads to unstable working in the power system. To assess the stability of the electric charging station several control approaches in AC part and DC parts during charging mode and discharging modes are tested. African vulture optimization algorithm (AVOA) has been utilized to tune the system controllers (proportional integral derivative (PID)/tilt integral derivative (TID) controllers). The superiority of AVOA is confirmed by comparing the performance with the genetic algorithm (GA). Two objective functions have been used i.e. integral time absolute error (ITAE) and integral square time error (ISTE). AVOA-tuned TID controllers using ISTE were found to be the best to contain the frequency deviations. The results have shown of the AC part and DC part is within an acceptable limit recommended by IEEE standard. Further, maximum peak overshoot, undershoot, and settle time obtained by AVOA-tuned PID and TID controllers are found the best. Finally, the improvement of the performance index obtained by AVOA over its counterpart GA is confirmed.