Volume 20, Issue 3 (September 2024)                   IJEEE 2024, 20(3): 106-116 | Back to browse issues page

XML Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Cong Chinh N. A Novel Meta-Heuristic Optimization Algorithm to Determine Optimal Access Point and Generation of Distributed Generators for Maximizing Economic and Technical Benefits. IJEEE 2024; 20 (3) :106-116
URL: http://ijeee.iust.ac.ir/article-1-3327-en.html
A Novel Meta-Heuristic Optimization Algorithm to Determine Optimal Access Point and Generation of Distributed Generators for Maximizing Economic and Technical Benefits
Nguyen Cong Chinh
Abstract:   (968 Views)
This paper presents an intelligent meta-heuristic algorithm, named improved equilibrium optimizer (IEO), for addressing the optimization problem of multi-objective simultaneous integration of distributed generators at unity and optimal power factor in a distribution system. The main objective of this research is to consider the multi-objective function for minimizing total power loss, improving voltage deviation, and reducing integrated system operating costs with strict technical constraints. An improved equilibrium optimizer is an enhanced version of the equilibrium optimizer that can provide better performance, stability, and convergence characteristics than the original algorithm. For evaluating the effectiveness of the suggested method, the IEEE 69-bus radial distribution system is chosen as a test system, and simulation results from this method are also compared fairly with many previously existing methods for the same targets and constraints. Thanks to its ability to intelligently expand the search space and avoid local traps, the suggested method has become a robust stochastic optimization method in tackling complex optimization tasks.
Keywords: Meta-heuristic algorithm, Improved equilibrium optimizer, Voltage deviation, Total power loss, Distributed generator
Full-Text [PDF 540 kb]   (326 Downloads)    
Type of Study: Research Paper | Subject: Distributed Generation/Integration of Renewables
Received: 2024/06/10 | Revised: 2024/10/06 | Accepted: 2024/07/23
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.