Biogeography-Based Optimization and the Solution of the Power Flow Problem

Rick Rarick; Daniel J. Simon; F. Eugenio Villaseca; B. Vyakaranam

doi:10.1109/ICSMC.2009.5346046

Biogeography-Based Optimization and the Solution of the Power Flow Problem

Rick Rarick
, Daniel J. Simon
, F. Eugenio Villaseca
, B. Vyakaranam

Cleveland State University

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

Abstract

Biogeography-based optimization (BBO) is a novel evolutionary algorithm that is based on the mathematics of biogeography. Biogeography is the study of the geographical distribution of biological organisms. In the BBO model, problem solutions are represented as islands, and the sharing of features between solutions is represented as immigration and emigration between the islands. This paper presents an application of the BBO algorithm to the power flow problem for an IEEE 30-bus Test Case system. The BBO solution is compared with the solution of the same problem using a genetic algorithm (GA). The results of Monte Carlo simulations indicate that the BBO algorithm consistently performs better than the GA

Original language	American English
Journal	IEEE International Conference on Systems, Man, and Cybernetics
DOIs	https://doi.org/10.1109/ICSMC.2009.5346046
State	Published - Oct 1 2009

Keywords

Biogeography-based optimization
power flow problem
genetic algorithms
evolutionary algorithms
power systems

Disciplines

Electrical and Computer Engineering

Access to Document

10.1109/ICSMC.2009.5346046License: CC BY

http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5346046

Cite this

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title = "Biogeography-Based Optimization and the Solution of the Power Flow Problem",

abstract = " Biogeography-based optimization (BBO) is a novel evolutionary algorithm that is based on the mathematics of biogeography. Biogeography is the study of the geographical distribution of biological organisms. In the BBO model, problem solutions are represented as islands, and the sharing of features between solutions is represented as immigration and emigration between the islands. This paper presents an application of the BBO algorithm to the power flow problem for an IEEE 30-bus Test Case system. The BBO solution is compared with the solution of the same problem using a genetic algorithm (GA). The results of Monte Carlo simulations indicate that the BBO algorithm consistently performs better than the GA",

keywords = "Biogeography-based optimization, power flow problem, genetic algorithms, evolutionary algorithms, power systems",

author = "Rick Rarick and Simon, \{Daniel J.\} and Villaseca, \{F. Eugenio\} and B. Vyakaranam",

note = "R. Rarick, D. Simon, F. Villaseca, and B. Vyakaranam. (2009). Biogeography-Based Optimization and the Solution of the Power Flow Problem. IEEE International Conference on Systems, Man, and Cybernetics, 1029-1034.",

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AU - Villaseca, F. Eugenio

AU - Vyakaranam, B.

N1 - R. Rarick, D. Simon, F. Villaseca, and B. Vyakaranam. (2009). Biogeography-Based Optimization and the Solution of the Power Flow Problem. IEEE International Conference on Systems, Man, and Cybernetics, 1029-1034.

PY - 2009/10/1

Y1 - 2009/10/1

N2 - Biogeography-based optimization (BBO) is a novel evolutionary algorithm that is based on the mathematics of biogeography. Biogeography is the study of the geographical distribution of biological organisms. In the BBO model, problem solutions are represented as islands, and the sharing of features between solutions is represented as immigration and emigration between the islands. This paper presents an application of the BBO algorithm to the power flow problem for an IEEE 30-bus Test Case system. The BBO solution is compared with the solution of the same problem using a genetic algorithm (GA). The results of Monte Carlo simulations indicate that the BBO algorithm consistently performs better than the GA

AB - Biogeography-based optimization (BBO) is a novel evolutionary algorithm that is based on the mathematics of biogeography. Biogeography is the study of the geographical distribution of biological organisms. In the BBO model, problem solutions are represented as islands, and the sharing of features between solutions is represented as immigration and emigration between the islands. This paper presents an application of the BBO algorithm to the power flow problem for an IEEE 30-bus Test Case system. The BBO solution is compared with the solution of the same problem using a genetic algorithm (GA). The results of Monte Carlo simulations indicate that the BBO algorithm consistently performs better than the GA

KW - Biogeography-based optimization

KW - power flow problem

KW - genetic algorithms

KW - evolutionary algorithms

KW - power systems

UR - https://engagedscholarship.csuohio.edu/enece_facpub/164

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DO - 10.1109/ICSMC.2009.5346046

M3 - Article

JO - IEEE International Conference on Systems, Man, and Cybernetics

JF - IEEE International Conference on Systems, Man, and Cybernetics

ER -

Biogeography-Based Optimization and the Solution of the Power Flow Problem

Abstract

Keywords

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