Optimal Overcurrent Relay Solutions for Protection Coordination Using Metaheuristics Approaches with Penalty Function Method

Authors

  • Noor Zaihah Jamal Faculty of Electrical & Electronics Engineering Technology, Universiti Malaysia Pahang Al-Sultan Abdullah, 26600 Pekan, Pahang, Malaysia
  • Mohd Herwan Sulaiman Faculty of Electrical & Electronics Engineering Technology, Universiti Malaysia Pahang Al-Sultan Abdullah, 26600 Pekan, Pahang, Malaysia
  • Abdul Nasir Faculty of Electrical & Electronics Engineering Technology, Universiti Malaysia Pahang Al-Sultan Abdullah, 26600 Pekan, Pahang, Malaysia
  • Waheb A. Jabbar College of Engineering, Faculty of Computing, Engineering and the Built Environment, Birmingham City University, Birmingham B4 7XG, West Midlands, England, United Kingdom

DOI:

https://doi.org/10.37934/araset.49.1.245271

Keywords:

Time multiplier setting (TMS);, plug setting (PS);, Metaheuristic algorithm, Overcurrent relays, protection coordination, Optimal relay operating time

Abstract

This paper presents the development of overcurrent relay coordination (OCRC) problem formulation by implementing five well known metaheuristic algorithms that are Ant Lion Optimizer (ALO), Moth Flame Optimizer (MFO), Grey Wolf Optimizer (GWO), Particles Swarm Optimizer (PSO) and Barnacles Matting Optimizer (BMO). The algorithms are assisted with penalty function method during the selection of new agents/ offsprings to confirm the generations that violated the constraints are superseded during the next generation selection. The OCRC is established by manipulating the current known as plus setting (PS) and time delay known as time multiplier setting (TMS) parameters. The optimized value of the TMS and PS will be selected using the algorithms to ensure the minimize result of the objective function. The algorithms are tested to three test systems which are IEEE 3 bus, 8 bus and 15 bus system to validate the efficiency and superiority of the proposed algorithms. The obtained results from those five algorithms are then compared. The simulation results show that MFO, BMO and GWO perform better objective function result and efficiently optimize the TMS and PS value of the OCRC problem without neglecting the inequality constraints.

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Author Biographies

Noor Zaihah Jamal, Faculty of Electrical & Electronics Engineering Technology, Universiti Malaysia Pahang Al-Sultan Abdullah, 26600 Pekan, Pahang, Malaysia

zaihah@ump.edu.my

Mohd Herwan Sulaiman, Faculty of Electrical & Electronics Engineering Technology, Universiti Malaysia Pahang Al-Sultan Abdullah, 26600 Pekan, Pahang, Malaysia

herwan@umpsa.edu.my

Abdul Nasir, Faculty of Electrical & Electronics Engineering Technology, Universiti Malaysia Pahang Al-Sultan Abdullah, 26600 Pekan, Pahang, Malaysia

abdnasir@umpsa.edu.my

Waheb A. Jabbar, College of Engineering, Faculty of Computing, Engineering and the Built Environment, Birmingham City University, Birmingham B4 7XG, West Midlands, England, United Kingdom

waheb.abdullah@bcu.ac.uk

Published

2024-07-28

Issue

Section

Articles