Title: Comparative Analysis of Different Optimization Algorithms on Transmission Expansion Planning Problem


Authors:

Akash Saxena

aakash.saxena@hotmail.com
Department of Electrical Engineering, Swami Keshvanand Institute of Technology, Management &Gramothan, Jaipur-302017 (INDIA),

Jitesh Jangid

jj90946@gmail.com
Department of Electrical Engineering, Swami Keshvanand Institute of Technology, Management & Gramothan, Jaipur-302017 (INDIA),

Aishwarya Mehta

aishu.sharma.0786@gmail.com
Department of Electrical Engineering, Swami Keshvanand Institute of Technology, Management &Gramothan, Jaipur-302017 (INDIA),

S.L. Surana

sls@skit.ac.in
Department of Electrical Engineering, Swami Keshvanand Institute of Technology, Management &Gramothan, Jaipur-302017 (INDIA),

Shalini Shekhawat

shekhawatshalini17@gmail.com
Department of Mathematics, Swami Keshvanand Institute of Technology, Management &Gramothan, Jaipur-302017 (INDIA)


Abstract:

Transmission expansion planning problem is a crit¬ical issue in power system due to competitive business environ¬ment and escalating power demand. Power system is expanding with every passing day from both generation and distribution side. However, for matching the demand, expansion plan of transmission network has been addressed in previous researches. This paper presents comparative analysis of recently published application of swarm algorithms for carrying out the expansion plan of a power network. These algorithms are namely Crow Search Algorithm (CSA), Moth Flame Optimization Algorithm (MFO), Artificial Bee colony Algorithm (ABC), Teaching Learn¬ing Based Optimization Algorithm (TLBO), Grey Wolf Algorithm (GWO) and Whale Optimization Algorithm (WOA). These algorithms are tested on two different power networks and a decisive evaluation of the optimization performance of algorithms are carried out. It has been observed that performance of CSA is found superior to other algorithms.

Keywords:
Network Expansion, Graver 6-Bus System, Brazilian 46-Bus System, Meta-Heuristics, Optimisation