Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Dynamic population artificial bee colony algorithm for multi-objective optimal power flow.

Man Ding1, Hanning Chen2, Na Lin3

  • 1School of Architecture and Art Design, Hebei University of Technology, Tianjin 300130, China.

Saudi Journal of Biological Sciences
|April 8, 2017
PubMed
Summary

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

[Intelligence level and structure in school age children with fetal growth restriction].

Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics·2009
Same author

Uncoupling the D1-N-methyl-D-aspartate (NMDA) receptor complex promotes NMDA-dependent long-term potentiation and working memory.

Biological psychiatry·2009
Same author

A phospho-directed macroporous alumina-silica nanoreactor with multi-functions.

ACS nano·2009
Same author

Subintimal angioplasty for below-the-ankle arterial occlusions in diabetic patients with chronic critical limb ischemia.

Journal of endovascular therapy : an official journal of the International Society of Endovascular Specialists·2009
Same author

Natural killer/T cell lymphoma initiating with pleural effusion: the significance of MICM combined techniques for the diagnosis.

Zhongguo shi yan xue ye xue za zhi·2009
Same author

[Advance of study on animal models of lymphoma].

Zhongguo shi yan xue ye xue za zhi·2009
Same journal

Deregulation of <i>TWIST1</i> expression by promoter methylation in gastrointestinal cancers.

Saudi journal of biological sciences·2024
Same journal

Gene-gene and gene-environmental interaction of dopaminergic system genes in Pakistani children with attention deficit hyperactivity disorder.

Saudi journal of biological sciences·2024
Same journal

Isolation of 6-gingerol and semi-synthesis of 1,4-benzodiazepines derivatives: An in-situ pharmacokinetics properties, molecular docking and molecular dynamics simulation assessments.

Saudi journal of biological sciences·2024
Same journal

Impact of CeO<sub>2</sub> modified cathode and PANI modified anode on tannery wastewater fed microbial fuel cell performance.

Saudi journal of biological sciences·2024
Same journal

Exploring the Global Trends of <i>Bacillus</i>, <i>Trichoderma</i> and Entomopathogenic Fungi for Pathogen and Pest Control in Chili Cultivation.

Saudi journal of biological sciences·2024
Same journal

LC-MS metabolomics and molecular docking approaches to identify antihyperglycemic and antioxidant compounds from <i>Melastoma malabathricum</i> L. Leaf.

Saudi journal of biological sciences·2024
See all related articles
This summary is machine-generated.

A novel artificial bee colony algorithm with dynamic population (ABC-DP) enhances realism by allowing bees to reproduce and die dynamically. This optimized algorithm effectively solves the optimal power flow problem in power systems.

Area of Science:

  • Artificial Intelligence
  • Optimization Algorithms
  • Power Systems Engineering

Background:

  • The optimal power flow (OPF) problem is crucial for efficient power system operation.
  • Existing algorithms may struggle to balance exploration and exploitation effectively.
  • Realistic modeling of natural processes can improve algorithm performance.

Purpose of the Study:

  • To introduce a novel artificial bee colony algorithm with dynamic population (ABC-DP).
  • To enhance the realism of the artificial bee colony algorithm by incorporating dynamic population changes.
  • To apply the ABC-DP algorithm to solve the multi-objective optimal power flow problem.

Main Methods:

  • Developed the artificial bee colony algorithm with dynamic population (ABC-DP) based on an extended life-cycle evolving model.
Keywords:
Artificial bee colony algorithmLife-cycle evolving modelMulti-objective optimizationOptimal power flow

Related Experiment Videos

  • Implemented dynamic reproduction and death of artificial bees during the foraging process, allowing population size variation.
  • Utilized ABC-DP to address the optimal power flow problem considering cost, loss, and emission impacts.

    • Main Results:

    • The proposed ABC-DP algorithm demonstrated effectiveness in solving the optimal power flow problem.
    • Simulation results on the 30-bus IEEE test system validated the algorithm's performance.
    • Comparisons with nondominated sorting genetic algorithm II (NSGAII) and multi-objective ABC (MOABC) showed superior results for ABC-DP.

    Conclusions:

    • The ABC-DP algorithm provides a more realistic and effective approach to optimization problems.
    • Dynamic population adjustment in ABC-DP improves the balance between exploration and exploitation.
    • ABC-DP is a robust and efficient method for solving the optimal power flow problem in power systems.