Alam, Mohammad Khurshed and Sulaiman, Mohd Herwan and Ferdowsi, Asma and Sayem, MD Shaoran and Ringku, Md Mahfuzer Akter and Foysal, Md. (2024) The superiority of feasible solutions-moth flame optimizer using valve point loading. Results in Control and Optimization, 17 (100465). pp. 1-19. ISSN 2666-7207. (In Press / Online First) (In Press / Online First)
|
Pdf
The superiority of feasible solutions-moth flame optimizer using valve point loading.pdf - Accepted Version Available under License Creative Commons Attribution. Download (815kB) | Preview |
|
|
Pdf
The superiority of feasible solutions-moth flame optimizer using valve point loading.pdf Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (4MB) | Preview |
Abstract
The optimal power flow (OPF) problem deals with large-scale, nonlinear, and non-convex optimization challenges, often accompanied by stringent constraints. Apart from the primary operational objectives of an energy system, ensuring load bus voltages remain within acceptable ranges is essential for providing high-quality consumer services. The Moth-Flame Optimizer (MFO) method is inspired by the unique night flight characteristics of moths. Moths, much like butterflies, undergo two distinct life stages: larval and mature. They have evolved the ability to navigate at night using a technique called transverse orientation. This article presents a methodology for determining the optimal energy transmission system configuration by integrating power producers. The MFO, Grey Wolf Optimizer (GWO), Success-history-based Parameter Adaptation Technique of Differential Evolution - Superiority of Feasible Solutions (SHADE-SF), and Superiority of Feasible Solutions-Moth Flame Optimizer (SF-MFO) algorithms are applied to address the OPF problem with two objective functions: (1) reducing energy production costs and (2) minimizing power losses. The efficiency of MFO, SF-MFO, SHADE-SF, and GWO for the OPF challenge is evaluated using IEEE 30-feeder and IEEE 57-feeder systems. Based on the collected data, SF-MFO demonstrated the best performance across all simulated instances. For instance, the electricity production costs generated by SF-MFO are $845.521/hr and $25,908.325/hr for the IEEE 30-feeder and IEEE 57-feeder systems, respectively. This represents a cost savings of 0.37% and 0.36% per hour, respectively, compared to the lowest values obtained by other comparative methods.
| Item Type: | Article |
|---|---|
| Additional Information: | Indexed by Scopus |
| Uncontrolled Keywords: | Moth -Flame Optimization (MFO), Grey Wolf Optimization (GWO), Superiority of Feasible Solutions-Moth Flame Optimizer (SF-MFO), Valve Point Loading. |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Faculty/Division: | Institute of Postgraduate Studies Faculty of Electrical and Electronic Engineering Technology |
| Depositing User: | Miss Amelia Binti Hasan |
| Date Deposited: | 25 Sep 2024 07:51 |
| Last Modified: | 25 Nov 2024 06:05 |
| URI: | http://umpir.ump.edu.my/id/eprint/42670 |
| Download Statistic: | View Download Statistics |
Actions (login required)
 |
View Item |