Knacks of marine predator heuristics for distributed energy source-based power systems harmonics estimation
Khalid Mehmood Cheema,
Khizer Mehmood,
Naveed Ishtiaq Chaudhary,
Zeshan Aslam Khan,
Muhammad Asif Zahoor Raja,
Ahmed M. El-Sherbeeny,
Ahmed Nadeem,
Zaki Ud din
Affiliations
Khalid Mehmood Cheema
Department of Electronic Engineering, Fatima Jinnah Women University, Rawalpindi 46000, Pakistan
Khizer Mehmood
Department of Electrical and Computer Engineering, International Islamic University, Islamabad, Pakistan
Naveed Ishtiaq Chaudhary
Future Technology Research Center, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan; Corresponding author.
Zeshan Aslam Khan
Department of Electrical and Computer Engineering, International Islamic University, Islamabad, Pakistan; International Graduate Institute of Artificial Intelligence, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin, 64002, Taiwan
Muhammad Asif Zahoor Raja
Future Technology Research Center, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin 64002, Taiwan
Ahmed M. El-Sherbeeny
Industrial Engineering Department, College of Engineering, King Saud University, Riyadh 11451, Saudi Arabia
Ahmed Nadeem
Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, Riyadh, 11451, Saudi Arabia
Zaki Ud din
Department of Engineering, Lancaster University, LA1 4YR, United Kingdom
The power system incorporates renewable energy resources into the main utility grid, which possesses low or no inertia, and these systems generate harmonics due to the utilization of power electronic equipment. The precise and effective assessment of harmonic characteristics is necessary for maintaining power quality in distributed power systems. In this paper, the Marine Predator Algorithm (MPA) that mimics the hunting behavior of predators is exploited for harmonics estimation. The MPA utilizes the concepts of Levy and Brownian motions to replicate the movement of predators as they search for prey. The identification model for parameter estimation of harmonics is presented, and an objective function is developed that minimizes the difference between the real and predicted harmonic signals. The efficacy of the MPA is assessed for different levels of noise, population sizes, and iterations. Further, the comparison of the MPA is conducted with a recent metaheuristic of the Reptile Search Algorithm (RSA). The statistical analyses through sufficient autonomous executions established the accurate, stable, reliable and robust behavior of MPA for all variations. The substantial enhancement in estimation accuracy indicates that MPA holds great potential as a strategy for estimating harmonic parameters in distributed power systems.
