An Advanced High Dimensional Power System of Optimization Problems Algorithm

Main Article Content

Hayder H. Safi, Eman. Abbas Ali Al-Khaffaf, Hussein Faris Saeed

Abstract

New Evolutionary Algorithm-based for High-Dimensional Power System Optimization Problems and Modern power system optimization problems face growing challenges as there are numerous decision variables and unbiased functions. Multi-objective evolutionary algorithms (MOEAs) basically are popularly applied for solving and dealing with such complicated problems in substantial power systems that have several objective functions. However, customary MOEAs works appropriately when the number of objective features comes to be less than three. Generally, the effectiveness of MOEAs begins to decrease apparently with an increase in the number of unbiased functions. This study is devoted to applying an authentic gradable evolutionary algorithm for the purpose of solving power system optimization issues which manifest numerous objective functions. In particular, this seeks an algorithm based upon NSGA-II algorithm dedicated for an efficient solution of multi-objective optimization problems. Here, we attempt to modify NSGA-II algorithm to effectively solve many target optimization problems. A novel effective grouping method is applied in the proposed algorithm in similar to the non-dominant grouping method of NSGA-II algorithm to accelerate decision convergence action in POF. The recommended algorithm is compared with modern numerous objective optimization algorithms following three test problems. The findings reveal that as the number of unbiased functions is noticeably large, the algorithm that we propose is significantly superior to other algorithms.

Article Details

How to Cite
Hayder H. Safi, et al. (2023). An Advanced High Dimensional Power System of Optimization Problems Algorithm. International Journal on Recent and Innovation Trends in Computing and Communication, 11(10), 1663–1669. https://doi.org/10.17762/ijritcc.v11i10.8728
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Articles
Author Biography

Hayder H. Safi, Eman. Abbas Ali Al-Khaffaf, Hussein Faris Saeed

Hayder H. Safi1, Eman. Abbas Ali Al-Khaffaf2, Hussein Faris Saeed3

1Department of Computer, College of Basic Education

Mustansiriyah University

Baghdad, Iraq

hayder.h.safi@uomustansiriyah.edu.iq

2College of Basic Education-Mustansiriyah University, Baghdad, Iraq

Iman3w@yahoo.com

3College of Basic Education-Mustansiriyah University, Baghdad, Iraq.

huseenfars036@gmail.com