Congestion Management using Genetic Algorithm in Deregulated Power Environments | Zendy

Seyed Mohammad Hossein Nabavi | Zendy; A. Kazemi | Zendy; Mohammad A. S. Masoum | Zendy

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Congestion Management using Genetic Algorithm in Deregulated Power Environments

Author(s) -

Seyed Mohammad Hossein Nabavi,

A. Kazemi,

Mohammad A. S. Masoum

Publication year - 2011

Publication title -

international journal of computer applications

Language(s) - English

Resource type - Journals

ISSN - 0975-8887

DOI - 10.5120/2257-2894

Subject(s) - computer science , genetic algorithm , power (physics) , operations research , algorithm , machine learning , mathematics , physics , quantum mechanics

Congestion cost allocation is an important issue in congestion management. This paper presents a genetic algorithm (GA) to determine the optimal generation levels in a deregulated market. The main issue is congestion in lines, which limits transfer capability of a system with available generation capacity. Nodal pricing method is used to determine locational marginal price (LMP) of each generator at each bus. Simulation results based on the proposed GA and the Power World Simulator software is presented and compared for the IEEE 30-bus test system.

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