Bachir Bentouati

Work place: Electrical Engineering Department, LMSF Laboratory, Amar Telidji University of Laghouat, Algeria



Research Interests: Combinatorial Optimization, Data Structures and Algorithms, Artificial Intelligence, Computer systems and computational processes


Bentouati Bachir was born in Laghouat, Algeria, on August 22, 1990. He received license, master and doctor degrees in Electrotechnic and Electrical Power System in 2010, 2012 and 2018 respectively from Laghouat university. His areas of research include optimal power flow, Artificial intelligence and optimization techniques.

Author Articles
A Novel Hybrid Method based on Krill Herd and Cuckoo Search for Optimal Power Flow Problem

By Aboubakr Khelifi Bachir Bentouati Saliha Chettih Ragab A. El-Sehiemy

DOI:, Pub. Date: 8 Sep. 2019

Solving the Optimal power flow (OPF) problem is an urgent task for power system operators. It aims at finding the control variables’ optimal scheduling subjected to several operational constraints to achieve certain economic, technical and environmental benefits. The OPF problem is mathematically expressed as a nonlinear optimization problem with contradictory objectives and subordinated to both constraints of equality and inequality. In this work, a new hybrid optimization technique, that integrates the merits of cuckoo search (CS) optimizer, is proposed to ameliorate the krill herd algorithm (KHA)'s poor efficiency. The proposed hybrid CS-KHA has been expanded for solving for single and multi-objective frameworks of the OPF problem through 11 case studies. The studied cases reflect various economic, technical and environmental requirements. These cases involve the following objectives: minimization of non- smooth generating fuel cost with valve-point loading effects, emission reduction, voltage stability enhancement and voltage profile improvement. The CS-KHA presents krill updating (KU) and krill abandoning (KA) operator derived from cuckoo search (CS) amid the procedure when the krill updating in order to extraordinarily improve its adequacy and dependability managing OPF problem. The viability of these improvements is examined on IEEE 30-bus, IEEE 57-bus and IEEE 118-bus test system. The experimental results prove the greatest ability of the proposed hybrid meta-heuristic CS-KHA compared to other famous methods.

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