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Buoyancy based optimization algorithm for real power loss diminution

Author

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  • Lenin Kanagasabai

    (Prasad V. Potluri Siddhartha Institute of Technology)

Abstract

This paper proposes Buoyancy based Optimization (BO) algorithm for actual power loss lessening. Important goals of the paper are Voltage constancy augmentation, voltage deviance minimization and Actual power loss lessening. Buoyancy is an ascending power exercised by a liquid that compete with the heaviness of a partly or completely engrossed entity. In a pole of liquid, stress upsurges with depth as a consequence of the heaviness of the superimposing liquid. Therefore the stress at the lowest of a pole of liquid is superior to at the topmost of the pole. Likewise, the stress at the lowermost of an entity immersed in a liquid is superior to topmost of the entity. The stress alteration has outcomes as ascending power on the entity. Buoyancy based optimization (BO) algorithm begins exploration procedure with preliminary population of entities (which are candidate solutions) with arbitrary dimensions, thicknesses, and spurts. At this period, every entity is also primed with its arbitrary location in liquid. Subsequently assessing the fitness value of preliminary population will be done. In all, iterations Buoyancy based optimization (BO) algorithm modernizes the thickness and capacity of each entity. Proposed Buoyancy based Optimization (BO) algorithm is substantiated in IEEE 30 bus system and IEEE 14, 30, 57, 118, 300 bus test systems without considering the voltage constancy index. True power loss lessening, voltage divergence decreasing, and voltage constancy index amplification has been attained.

Suggested Citation

  • Lenin Kanagasabai, 2022. "Buoyancy based optimization algorithm for real power loss diminution," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(5), pages 2442-2457, October.
    • Handle: RePEc:spr:ijsaem:v:13:y:2022:i:5:d:10.1007_s13198-022-01656-8
    DOI: 10.1007/s13198-022-01656-8
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    References listed on IDEAS

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    1. Zahir Sahli & Abdellatif Hamouda & Abdelghani Bekrar & Damien Trentesaux, 2018. "Reactive Power Dispatch Optimization with Voltage Profile Improvement Using an Efficient Hybrid Algorithm †," Energies, MDPI, vol. 11(8), pages 1-21, August.
    2. Mohamed Ebeed & Ayman Alhejji & Salah Kamel & Francisco Jurado, 2020. "Solving the Optimal Reactive Power Dispatch Using Marine Predators Algorithm Considering the Uncertainties in Load and Wind-Solar Generation Systems," Energies, MDPI, vol. 13(17), pages 1-19, August.
    3. Mini Vishnu & Sunil Kumar T. K., 2020. "An Improved Solution for Reactive Power Dispatch Problem Using Diversity-Enhanced Particle Swarm Optimization," Energies, MDPI, vol. 13(11), pages 1-21, June.
    4. Omar Abu Arqub & Zaer Abo-Hammour & Shaher Momani & Nabil Shawagfeh, 2012. "Solving Singular Two-Point Boundary Value Problems Using Continuous Genetic Algorithm," Abstract and Applied Analysis, Hindawi, vol. 2012, pages 1-25, November.
    5. Xinna Mao & Zhao Guoxi & Mohammad Fallah & S. A. Edalatpanah, 2020. "A Neutrosophic-Based Approach in Data Envelopment Analysis with Undesirable Outputs," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-8, July.
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