Optimal power flow using GA with a new multi-parent crossover considering: prohibited zones, valve-point effect, multi-fuels and emission

H. R.E.H. Bouchekara; A. E. Chaib; M. A. Abido

doi:10.1007/s00202-016-0488-9

Optimal power flow using GA with a new multi-parent crossover considering: prohibited zones, valve-point effect, multi-fuels and emission

H. R.E.H. Bouchekara^*, A. E. Chaib, M. A. Abido

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

36 Scopus citations

Abstract

In this paper, a genetic algorithm with new multi-parent crossover (GA-MPC) is used for solving the optimal power flow problem. This method is tested on the IEEE 30-bus test system for 10 different cases where, in addition to the total fuel cost, different complexities and constraints like: emission, multi-fuels, valve-point effect and prohibited zones are considered. The effectiveness and robustness of the GA-MPC method are assessed using a statistical study and a comparative study with some well-known optimization methods. The obtained results along with the comparison study indicate that the GA-MPC method provides effective and high-quality solution when solving the optimal power flow problem even for complicated and highly constrained working conditions.

Original language	English
Pages (from-to)	151-165
Number of pages	15
Journal	Electrical Engineering
Volume	100
Issue number	1
DOIs	https://doi.org/10.1007/s00202-016-0488-9
State	Published - 1 Mar 2018

Bibliographical note

Publisher Copyright:
© 2016, Springer-Verlag Berlin Heidelberg.

Keywords

Genetic algorithm with multi-parent crossover
Optimal power flow
Power system optimization

ASJC Scopus subject areas

Electrical and Electronic Engineering
Applied Mathematics

Access to Document

10.1007/s00202-016-0488-9

Cite this

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title = "Optimal power flow using GA with a new multi-parent crossover considering: prohibited zones, valve-point effect, multi-fuels and emission",

abstract = "In this paper, a genetic algorithm with new multi-parent crossover (GA-MPC) is used for solving the optimal power flow problem. This method is tested on the IEEE 30-bus test system for 10 different cases where, in addition to the total fuel cost, different complexities and constraints like: emission, multi-fuels, valve-point effect and prohibited zones are considered. The effectiveness and robustness of the GA-MPC method are assessed using a statistical study and a comparative study with some well-known optimization methods. The obtained results along with the comparison study indicate that the GA-MPC method provides effective and high-quality solution when solving the optimal power flow problem even for complicated and highly constrained working conditions.",

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doi = "10.1007/s00202-016-0488-9",

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AU - Abido, M. A.

PY - 2018/3/1

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N2 - In this paper, a genetic algorithm with new multi-parent crossover (GA-MPC) is used for solving the optimal power flow problem. This method is tested on the IEEE 30-bus test system for 10 different cases where, in addition to the total fuel cost, different complexities and constraints like: emission, multi-fuels, valve-point effect and prohibited zones are considered. The effectiveness and robustness of the GA-MPC method are assessed using a statistical study and a comparative study with some well-known optimization methods. The obtained results along with the comparison study indicate that the GA-MPC method provides effective and high-quality solution when solving the optimal power flow problem even for complicated and highly constrained working conditions.

AB - In this paper, a genetic algorithm with new multi-parent crossover (GA-MPC) is used for solving the optimal power flow problem. This method is tested on the IEEE 30-bus test system for 10 different cases where, in addition to the total fuel cost, different complexities and constraints like: emission, multi-fuels, valve-point effect and prohibited zones are considered. The effectiveness and robustness of the GA-MPC method are assessed using a statistical study and a comparative study with some well-known optimization methods. The obtained results along with the comparison study indicate that the GA-MPC method provides effective and high-quality solution when solving the optimal power flow problem even for complicated and highly constrained working conditions.

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Optimal power flow using GA with a new multi-parent crossover considering: prohibited zones, valve-point effect, multi-fuels and emission

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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