You are in:Home/Publications/M.M. SALAMA, M.M. ELGAZAR, S.M. ABDELMAKSOUD, H.A. HENRY, "Short Term Optimal Generation Scheduling of Fixed Head Hydrothermal System Using Genetic Algorithm and Constriction Factor Based Particle Swarm Optimization Technique", INTERNATIONAL JOURNAL OF SCIENTIFIC AND RESEARCH PUBLICATIONS, VOLUME 3, ISSUE 5, MAY 2013, ISSN 2250-3153.

Prof. Mohamed Moenes Mohamed Salama :: Publications:

Title:
M.M. SALAMA, M.M. ELGAZAR, S.M. ABDELMAKSOUD, H.A. HENRY, "Short Term Optimal Generation Scheduling of Fixed Head Hydrothermal System Using Genetic Algorithm and Constriction Factor Based Particle Swarm Optimization Technique", INTERNATIONAL JOURNAL OF SCIENTIFIC AND RESEARCH PUBLICATIONS, VOLUME 3, ISSUE 5, MAY 2013, ISSN 2250-3153.
Authors: M.M. SALAMA*, M.M. ELGAZAR**, S.M. ABDELMAKSOUD*, H.A. HENRY*
Year: 2013
Keywords: Not Available
Journal: INTERNATIONAL JOURNAL OF SCIENTIFIC AND RESEARCH PUBLICATIONS, ISSN 2250-3153.
Volume: VOLUME 3
Issue: ISSUE 5
Pages: Not Available
Publisher: Not Available
Local/International: International
Paper Link: Not Available
Full paper Mohamed Moenes Mohamed Salama _Short T O G S of Fixed H.pdf
Supplementary materials Not Available
Abstract:

Abstract- In this paper, a genetic algorithm (GA) and constriction factor based particle swarm optimization technique are proposed for solving the short term fixed head hydrothermal scheduling problem with transmission line losses. The performance efficiency of the proposed techniques is demonstrated on hydrothermal test system comprising of three thermal units and one hydro power plant. A wide range of thermal and hydraulic constraints such as real power balance constraint, minimum and maximum limits of thermal and hydro units, water availability limit and discharge rate limits are taken into account. The simulation results obtained from the constriction factor based particle swarm optimization technique are compared with the outcomes obtained from the genetic algorithm to reveal the validity and verify the feasibility of the proposed methods. The test results show that the constriction factor based particle swarm optimization approach give the same solution as obtained by genetic algorithm but the computation time of the constriction factor based particle swarm optimization method is less than genetic algorithm. Index Terms- Hydrothermal Generation Scheduling, Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Constriction Factor (CF)

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