Open AccessOptimal DG Integration Using Artificial Ecosystem-Based Optimization (AEO) Algorithm
Author(s) -
Djedidi Imene,
Djemai Naimi,
Shabbir Ahmed,
Bouhanik Anes
Publication year - 2022
Publication title -
european journal of electrical engineering
Language(s) - English
Resource type - Journals
eISSN - 2116-7109
pISSN - 2103-3641
DOI - 10.18280/ejee.240103
Subject(s) - sizing , robustness (evolution) , mathematical optimization , minification , computation , convergence (economics) , computer science , electric power system , voltage , optimization problem , power (physics) , algorithm , mathematics , engineering , art , biochemistry , chemistry , physics , quantum mechanics , electrical engineering , economics , visual arts , gene , economic growth
This paper presents a novel and efficient optimization approach based on the Artificial Ecosystem Optimization (AEO) algorithm to solve the problem of finding optimal location and sizing of Distributed Generation (DGs) in radial distribution systems. The objective is to satisfy a fluctuating demand in a constant and instantaneous way while respecting the requirements of power loss reduction, operating cost minimization and voltage profile improvement within the equality and inequality constraints. The robustness of the proposed technique in terms of solution quality and convergence characteristics is evaluated using the IEEE-33 bus radial distribution network test system. The simulation results are compared with those of other methods recently used in the literature for the same test system. The experimental outcomes show that the proposed AEO approach is comparatively able to achieve a higher quality solution within a timeliness of computation.