A Load Power Distribution Optimization based on Improving Biogeography-Based Optimization

A Load Power Distribution Optimization based on Improving Biogeography-Based Optimization

A popular optimizer algorithm inspired by biogeography theory BBO (Bio-geography-based optimization) has advantages, e.g., fewer parameters and easy implementation. Still, some drawbacks exist, e.g., the imbalance between the global and the local search potential optimization and dropping local opti...

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Bibliographic Details
Published in:2021 IEEE International Conference on Machine Learning and Applied Network Technologies (ICMLANT) pp. 1 - 5
Main Authors: Nguyen, Trong-The, Nguyen, Trinh-Dong, Ngo, Truong-Giang, Dao, Thi-Kien
Format: Conference Proceeding
Language:English
Published: IEEE 16-12-2021
Subjects:
Biogeographic algorithm
Constrained optimization
Costs
Differential evolution
Dispatching
Economic load distribution
Machine learning algorithms
Power distribution
Search problems
Simulation
Valves
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Summary:A popular optimizer algorithm inspired by biogeography theory BBO (Bio-geography-based optimization) has advantages, e.g., fewer parameters and easy implementation. Still, some drawbacks exist, e.g., the imbalance between the global and the local search potential optimization and dropping local optimal when dealing with complex problems. This study suggests an improving BBO (IBBO) with differential evolution (DE) for a dispatching economic load power distribution. A power loads distribution is modeled by considering the fuel cost, the valve stage's effect, the environment's cost, and its various constraints. Simulation results of the IBBO show that the proposed scheme provides more robust convergence, efficiency optimization, and superiority in solving economic load distribution problems.
DOI:10.1109/ICMLANT53170.2021.9690539