Fuzzy Multi-Objective Optimal Power Flow Using Genetic Algorithms Applied to Algerian Electrical Network | Zendy

Ahmed Salhi | Zendy; Djemai Naimi | Zendy; Tarek Bouktir | Zendy

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Fuzzy Multi-Objective Optimal Power Flow Using Genetic Algorithms Applied to Algerian Electrical Network

Author(s) -

Ahmed Salhi,

Djemai Naimi,

Tarek Bouktir

Publication year - 2013

Publication title -

advances in electrical and electronic engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.225

H-Index - 19

eISSN - 1804-3119

pISSN - 1336-1376

DOI - 10.15598/aeee.v11i6.832

Subject(s) - power flow , genetic algorithm , fuzzy logic , computer science , flow (mathematics) , algorithm , power (physics) , power network , mathematical optimization , electric power system , mathematics , artificial intelligence , machine learning , physics , geometry , quantum mechanics

This paper presents a mathematical model for solving Multi-Objective Optimal Power Flow problem considering uncertainties modeled by fuzzy numbers aecting three objective functions given by total generation cost, total gas emission and voltage profle index. The presented resolution approach is based on Genetic Algorithm (GA), where the parameters of this algorithm are determined and optimized after many tests of execution. A model for analyzing trade-off between profit and security constraint is developed. The probabilities of crossover and mutation optimized for GA parameters, dedicated to the presented approach are used to demonstrate a performance and effectiveness of the algorithm compared to other approaches mentioned in this paper. The mathematic model is applied in the Algerian electrical network for 59-bus test system.

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