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Real power loss dwindling and voltage reliability enrichment by gradient based optimization algorithm

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  • Lenin Kanagasabai

    (Prasad V Potluri Siddhartha Institute of Technology)

Abstract

This paper proposes Gradient based Optimization (GO) Algorithm for genuine loss lessening. Important goals of the paper are Power fidelity extension, power eccentricity minimization and genuine loss lessening. In the proposed Gradient based Optimization (GO) Algorithm, gradient and populace grounded approaches, the exploration way are quantified by the Newton’s technique to discover the examination area by employing gradient exploration canon and confined evasion operatives. The Newton’s technique is a dominant process to mathematically decipher the calculations. This technique is an origin discovery procedure that engages the preliminary rapports of the Taylor sequences. This technique starts with a distinct fact and at that moment expenditures the Taylor sequences evaluated at fact for guesstimating alternative fact that is adjacent to the elucidation. In the gradient exploration canon, the drive of vectors is organised to enhanced exploration in the possible area and attain superior locations. Goal is to augment the examination propensity and quickening the conjunction. The derivative is premeditated by employing the Taylor sequences. Proposed Gradient based Optimization (GO) Algorithm is corroborated in Garver’s 6-bus test system, IEEE 30, 57, 118, 300, 354 bus test systems and Practical system—WDN 220 kV (Unified Egyptian Transmission Network (UETN)). Loss lessening, voltage divergence curtailing, and voltage constancy index augmentation has been attained.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:ijsaem:v:13:y:2022:i:5:d:10.1007_s13198-022-01743-w
    DOI: 10.1007/s13198-022-01743-w
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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. 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. Sirote Khunkitti & Apirat Siritaratiwat & Suttichai Premrudeepreechacharn, 2021. "Multi-Objective Optimal Power Flow Problems Based on Slime Mould Algorithm," Sustainability, MDPI, vol. 13(13), pages 1-21, July.
    4. 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.
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