Multi-objective optimal electric power planning in the power system using Gaussian bare-bones imperialist competitive algorithm

•Multi-objective optimal electric power planning.•Considered fuel cost, active power loss, gaze emission and voltage deviation.•Proposed MGBICA algorithm was successfully implemented for multi-objective OPF. In this paper, a Gaussian Bare-bones multi-objective Imperialist Competitive Algorithm (GBIC...

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Bibliographic Details
Published in:Information sciences Vol. 294; pp. 286 - 304
Main Authors: Ghasemi, Mojtaba, Ghavidel, Sahand, Ghanbarian, Mohammad Mehdi, Gitizadeh, Mohsen
Format: Journal Article
Language:English
Published: Elsevier Inc 10.02.2015
Subjects:
Algorithms
Borides
Electric power
Gaussian
Gaussian bare-bones imperialist competitive algorithm
Magnesium compounds
Multi-objective optimal electric power planning
Multi-objective optimization algorithm
Optimization
Reactive power
Multi-objective optimization algorithm
Gaussian bare-bones imperialist competitive algorithm
Multi-objective optimal electric power planning
ISSN:0020-0255, 1872-6291
Online Access:Get full text
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Summary:•Multi-objective optimal electric power planning.•Considered fuel cost, active power loss, gaze emission and voltage deviation.•Proposed MGBICA algorithm was successfully implemented for multi-objective OPF. In this paper, a Gaussian Bare-bones multi-objective Imperialist Competitive Algorithm (GBICA) and its Modified version (MGBICA) are presented for the optimal electric power planning in the electric power system. Two sub-problems of multi-objective optimal electric power planning namely Optimal Power Flow (OPF) and Optimal Reactive Power Dispatch (ORPD) problems are considered. The OPF and ORPD problems are formulated as a nonlinear constrained multi-objective optimization problem with competing objectives. The performance of multi-objective algorithms are studied and evaluated on the standard IEEE 30-bus and IEEE 57-bus test systems. The proposed algorithm provides better results compared with the other algorithms as demonstrated by simulation results.
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ISSN:0020-0255
1872-6291
DOI:10.1016/j.ins.2014.09.051