Rachid HABACHI
Laboratory of Engineering, of Industrial Management and Innovation The Faculty of Sciences and Technology, Hassan 1st University

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Solving economic dispatch and unit commitment problem in smart grid system using eagle strategy based crow search algorithm Rachid HABACHI; Achraf Touil; Abdellah Boulal; Abdelkabir Charkaoui; Abdelwahed Echchatbi
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 3: June 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v14.i3.pp1087-1096

Abstract

The economic dispatch problem of power plays a very important role in the exploitation of electro-energy systems to judiciously distribute power generated by all plants. The Unit commitment problem (UCP) is mainly finding the minimum cost schedule to a set of generators by turning each one either on or off over a given time horizon to meet the demand load and satisfy different operational constraints. This research article integrates the crow search algorithm as a local optimizer of Eagle strategy to solve economic dispatch and unit commitment problem in smart grid system.
Resolution of economic dispatch problem of the morocco network using crow search algorithm Rachid HABACHI; Achraf Touil; Abdellah Boulal; Abdelkabir Charkaoui; Abdelwahed Echchatbi
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 1: January 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i1.pp347-353

Abstract

The economic dispatch problem of power plays a very important role in the exploitation of electro-energy systems to judiciously distribute power generated by all plants. This paper proposes use of Crow Search Algorithm (CSA), for solving the economic dispatch of two electricity networks: a testing system 6 units and the morocco network the crow search algorithm (CSA) is a recently developed metaheuristic search algorithm inspired by the intelligent behavior of crows..The results obtained by CSA are compared with various results obtained in the literature. Simulation results shows that using CSA can lead to finding stable and adequate power generated that can fulfill the need of both the civil and industrial areas.
Eagle Strategy based Crow Search Algorithm for solving Unit Commitment Problem Rachid Habachi; Achraf Touil; Abdelkabir Charkaoui; Abdelwahed Echchatbi
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 1: October 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i1.pp17-29

Abstract

Eagle strategy is a two-stage optimization strategy, which is inspired by the observation of the hunting behavior of eagles in nature. In this two-stage strategy, the first stage explores the search space globally by using a Levy flight; if it finds a promising solution, then an intensive local search is employed using a more efficient local optimizer, such as hillclimbing and the downhill simplex method. Then, the two-stage process starts again with new global exploration, followed by a local search in a new region. One of the remarkable advantages of such a combina-tion is to use a balanced tradeoff between global search (which is generally slow) and a rapid local search. The crow search algorithm (CSA) is a recently developed metaheuristic search algorithm inspired by the intelligent behavior of crows.This research article integrates the crow search algorithm as a local optimizer of Eagle strategy to solve unit commitment (UC) problem. The Unit commitment problem (UCP) is mainly finding the minimum cost schedule to a set of generators by turning each one either on or off over a given time horizon to meet the demand load and satisfy different operational constraints. There are many constraints in unit commitment problem such as spinning reserve, minimum up/down, crew, must run and fuel constraints. The proposed strategy ES-CSA is tested on 10 to 100 unit systems with a 24-h scheduling horizon. The effectiveness of the proposed strategy is compared with other well-known evolutionary, heuristics and meta-heuristics search algorithms, and by reported numerical results, it has been found that proposed strategy yields global results for the solution of the unit commitment problem.