IDEAS home Printed from https://ideas.repec.org/a/spr/ijsaem/v13y2022i5d10.1007_s13198-022-01656-8.html
   My bibliography  Save this article

Buoyancy based optimization algorithm for real power loss diminution

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13198-022-01656-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s13198-022-01656-8?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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. 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.
    3. 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.
    4. 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.
    5. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lenin Kanagasabai, 2023. "Real power loss reduction by extreme learning machine based Panthera leo, chaotic based Jungle search and Quantum based Chipmunk search optimization algorithms," 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. 14(1), pages 55-78, March.
    2. Andrei M. Tudose & Irina I. Picioroaga & Dorian O. Sidea & Constantin Bulac, 2021. "Solving Single- and Multi-Objective Optimal Reactive Power Dispatch Problems Using an Improved Salp Swarm Algorithm," Energies, MDPI, vol. 14(5), pages 1-20, February.
    3. Lenin Kanagasabai, 2022. "Real power loss dwindling and voltage reliability enrichment by gradient based optimization algorithm," 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 2727-2742, October.
    4. Lenin Kanagasabai, 2022. "Mathematics based calculation and stemonitis inspired optimization algorithms for loss reduction and power solidity augmentation," 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 2710-2726, October.
    5. Sulaiman Z. Almutairi & Emad A. Mohamed & Fayez F. M. El-Sousy, 2023. "A Novel Adaptive Manta-Ray Foraging Optimization for Stochastic ORPD Considering Uncertainties of Wind Power and Load Demand," Mathematics, MDPI, vol. 11(11), pages 1-35, June.
    6. Peng Cheng & Zhiyu Xu & Ruiye Li & Chao Shi, 2022. "A Hybrid Taguchi Particle Swarm Optimization Algorithm for Reactive Power Optimization of Deep-Water Semi-Submersible Platforms with New Energy Sources," Energies, MDPI, vol. 15(13), pages 1-16, June.
    7. Mahmoud Hemeida & Tomonobu Senjyu & Salem Alkhalaf & Asmaa Fawzy & Mahrous Ahmed & Dina Osheba, 2022. "Reactive Power Management Based Hybrid GAEO," Sustainability, MDPI, vol. 14(11), pages 1-17, June.
    8. Lenin Kanagasabai, 2023. "Legislative optimization algorithm for real power loss diminishing and voltage reliability escalation," 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. 14(4), pages 1197-1207, August.
    9. Nasreddine Belbachir & Mohamed Zellagui & Samir Settoul & Claude Ziad El-Bayeh & Ragab A. El-Sehiemy, 2023. "Multi Dimension-Based Optimal Allocation of Uncertain Renewable Distributed Generation Outputs with Seasonal Source-Load Power Uncertainties in Electrical Distribution Network Using Marine Predator Al," Energies, MDPI, vol. 16(4), pages 1-24, February.
    10. Samson Ademola Adegoke & Yanxia Sun, 2023. "Diminishing Active Power Loss and Improving Voltage Profile Using an Improved Pathfinder Algorithm Based on Inertia Weight," Energies, MDPI, vol. 16(3), pages 1-14, January.
    11. Shahenda Sarhan & Ragab El-Sehiemy & Amlak Abaza & Mona Gafar, 2022. "Turbulent Flow of Water-Based Optimization for Solving Multi-Objective Technical and Economic Aspects of Optimal Power Flow Problems," Mathematics, MDPI, vol. 10(12), pages 1-22, June.
    12. Samson Ademola Adegoke & Yanxia Sun & Zenghui Wang, 2023. "Minimization of Active Power Loss Using Enhanced Particle Swarm Optimization," Mathematics, MDPI, vol. 11(17), pages 1-17, August.
    13. Muhammad, Yasir & Khan, Nusrat & Awan, Saeed Ehsan & Raja, Muhammad Asif Zahoor & Chaudhary, Naveed Ishtiaq & Kiani, Adiqa Kausar & Ullah, Farman & Shu, Chi-Min, 2022. "Fractional memetic computing paradigm for reactive power management involving wind-load chaos and uncertainties," Chaos, Solitons & Fractals, Elsevier, vol. 161(C).
    14. Shahenda Sarhan & Abdullah Shaheen & Ragab El-Sehiemy & Mona Gafar, 2023. "An Augmented Social Network Search Algorithm for Optimal Reactive Power Dispatch Problem," Mathematics, MDPI, vol. 11(5), pages 1-42, March.
    15. Chaudhary, Naveed Ishtiaq & Raja, Muhammad Asif Zahoor & Khan, Zeshan Aslam & Mehmood, Ammara & Shah, Syed Muslim, 2022. "Design of fractional hierarchical gradient descent algorithm for parameter estimation of nonlinear control autoregressive systems," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
    16. Lenin Kanagasabai, 2022. "Jerusalem artichoke algorithm for power loss reduction and power stability enhancement," 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(4), pages 1788-1800, August.
    17. Umar Waleed & Abdul Haseeb & Muhammad Mansoor Ashraf & Faisal Siddiq & Muhammad Rafiq & Muhammad Shafique, 2022. "A Multiobjective Artificial-Hummingbird-Algorithm-Based Framework for Optimal Reactive Power Dispatch Considering Renewable Energy Sources," Energies, MDPI, vol. 15(23), pages 1-23, December.
    18. Salah K. ElSayed & Ehab E. Elattar, 2021. "Slime Mold Algorithm for Optimal Reactive Power Dispatch Combining with Renewable Energy Sources," Sustainability, MDPI, vol. 13(11), pages 1-25, May.
    19. Vanalakshmi, R. & Maragathasundari, S. & Dhanalakshmi, K.S., 2022. "Queuing system in VLSI physical design," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 201(C), pages 755-768.
    20. Ashraf Ramadan & Mohamed Ebeed & Salah Kamel & Almoataz Y. Abdelaziz & Hassan Haes Alhelou, 2021. "Scenario-Based Stochastic Framework for Optimal Planning of Distribution Systems Including Renewable-Based DG Units," Sustainability, MDPI, vol. 13(6), pages 1-23, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:ijsaem:v:13:y:2022:i:5:d:10.1007_s13198-022-01656-8. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.