Metaheuristic Algorithms for Evaluating the Effect of Electric Vehicle Charging Infrastructures in Distribution Networks

Abstract

To address the effect of electric vehicle (EV) load on distribution system efficient optimization techniques are required. In this paper, an attempt is made to work with various new optimization techniques for minimizing the detrimental effect of EV charging station (EVCS) load on the electrical network. The operating conditions of the distribution network, that is, voltage stability, reliability and power loss (VRP) index are optimized in this work in a framework of multiple objectives with various technical constraints. Although many optimization approaches have been developed in recent years, eight well-known techniques are employed in the present work such as modified teaching-learner-based optimization (MTLBO), JAYA, modified JAYA (MJAYA), ant–lion optimization (ALO), whale optimization technique (WOT), grasshopper optimization technique (GOT), modified whale optimization algorithm (MWOA), and hybrid whale particle swarm optimization (HWPSOA). All the eight techniques’ performance is compared under two different cases of operations by testing the objective function on the modified IEEE 33 bus distribution system using MATLAB software. The numerical solutions obtained by the HWPSOA indicate the suitability and effectiveness for optimizing the specified complex multi-objective function compared to other techniques.

Keywords:

• optimization
• electric vehicle charging station
• renewable energy sources
• VRP index
• metaheuristic techniques

DISCLOSURE STATEMENT

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Additional information

Notes on contributors

Nandini K. K.

Nandini K. K. received her B.E. degree in Electrical and Electronics Engineering from UBDT College of Engineering, Davangere, India and M.Tech. in Energy Systems Engineering from NMAMIT, Nitte, Karnataka, India. Presently, she is employed as a Full Time Research Scholar, pursuing PhD in the Department of Electrical and Electronics Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, India. Also, she is a student member of IEEE, PES and Young Professional, Bangalore Section, Women in Engineering (WiE) and life time member of the Institute of Engineers, India. Her research interests include electric vehicles and their charging infrastructure, power quality and mitigation, and integration of renewables into the grid.

Jayalakshmi N. S.

Jayalakshmi N. S. received her B.E. degree in Electrical Engineering from M.S.R.I.T., Bangalore, India, and M. Tech. in Power Systems from National Institute of Engineering, Mysore, India in 1991 and 1999 respectively. She received her Ph. D. degree from the Department of Electrical and Electronics Engineering, National Institute of Technology, Karnataka, Surathkal, India. Presently, she is working as Professor in the Department of Electrical and Electronics Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, India. She has published more than 80 technical papers in reputed international journals and conferences. She is senior member of IEEE, PES and life member of ISTE, system society of India. Her research areas include distributed generation systems, power system operation and control, operation and control of microgrid, electric vehicles.

Vinay Kumar Jadoun

Vinay Kumar Jadoun is currently an Associate Professor in the Department of Electrical & Electronics Engineering, Manipal Institute of Technology, MAHE, Manipal, India. He has received a B.E. from SATI, Vidisha, M. P., India. He received M. Tech. and Ph. D. from the Department of Electrical Engineering, Malaviya National Institute of Technology (MNIT), Jaipur, India. He is a Senior Member of IEEE, PES, and Smart Grid Community. His areas of interest are economic operation of power system, renewable power generation, micro grid, smart grid, electric vehicles, cybersecurity, application of AI-ML with IOT in healthcare, DGA and soft computing techniques.