Volume 21, Issue 2 (Special Issue on the 1st International Conference on ELECRiS 2024 Malaysia - June 2025)                   IJEEE 2025, 21(2): 3611-3611 | Back to browse issues page

XML Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Ahmad Sabri S, Abdul Rahim S R, Azmi A, Azmi S A, Hussain M H, Musirin I. A Comparative Study on DG Placement Using Marine Predator and Osprey Algorithms to Enhance Loss Reduction Index in the Distribution System. IJEEE 2025; 21 (2) :3611-3611
URL: http://ijeee.iust.ac.ir/article-1-3611-en.html
A Comparative Study on DG Placement Using Marine Predator and Osprey Algorithms to Enhance Loss Reduction Index in the Distribution System
Syazwan Ahmad Sabri , Siti Rafidah Abdul Rahim , Azralmukmin Azmi , Syahrul Ashikin Azmi , Muhamad Hatta Hussain , Ismail Musirin
Abstract:   (197 Views)
The Marine Predator Algorithm (MPA) and Osprey Optimization Algorithm (OOA) are nature-inspired metaheuristic techniques used for optimizing the location and sizing of distributed generation (DG) in power distribution systems. MPA simulates marine predators' foraging strategies through Lévy and Brownian movements, while OOA models the hunting and survival tactics of ospreys, known for their remarkable fishing skills. Effective placement and sizing of DG units are crucial for minimizing network losses and ensuring cost efficiency. Improper configurations can lead to overcompensation or undercompensation in the network, increasing operational costs. Different DG technologies, such as photovoltaic (PV), wind, microturbines, and generators, vary significantly in cost and performance, highlighting the importance of selecting the right models and designs. This study compares MPA and OOA in optimizing the placement of multiple DGs with two types of power injection which are active and reactive power. Simulations on the IEEE 69-bus reliability test system, conducted using MATLAB, demonstrated MPA’s superiority, achieving a 69% reduction in active power losses compared to OOA’s 61%, highlighting its potential for more efficient DG placement in power distribution systems. The proposed approach incorporates a DG model encompassing multiple technologies to ensure economic feasibility and improve overall system performance.
Keywords: Distributed Generation, Nature Inspired Algorithm, Marine Predator Algorithm, Osprey Optimization Algorithm, MATLAB, Power Distribution, IEEE 69-Bus, Loss Reduction Index.
Full-Text [PDF 986 kb]   (27 Downloads)    
Type of Study: Only For Articles of ELECRiS 2024 | Subject: Artificial Intelligence Techniques
Received: 2024/12/15 | Revised: 2025/03/13 | Accepted: 2025/02/20
Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Creative Commons License
© 2022 by the authors. Licensee IUST, Tehran, Iran. This is an open access journal distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.