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Real-Power Rescheduling of Generators for Congestion Management Using a Novel Satin Bowerbird Optimization Algorithm

Author

Listed:
  • Jagadeeswar Reddy Chintam

    (Electrical and Electronics Engineering, Government College of Technology, Coimbatore, Tamilnadu 641013, India)

  • Mary Daniel

    (Electrical and Electronics Engineering, Government College of Technology, Coimbatore, Tamilnadu 641013, India)

Abstract

In this paper, an efficient meta-heuristic satin bowerbird optimization (SBO) algorithm is presented for congestion management (CM) in the deregulated power system. The main objective of CM is to relieve congestion in the transmission lines using a generation rescheduling-based approach, while satisfying all the constraints with minimum congestion cost. The SBO is a nature-inspired algorithm, developed based on the ‘male-attracts-the-female for breeding’ principle of the specialized stick structure mechanism of satin birds. The proposed approach is effectively tested on small and large test systems, namely, modified IEEE 30-bus, modified IEEE 57-bus, and IEEE 118-bus test systems. The constraints like line loading, line limits, generator limits, and bus voltage impact, etc., are incorporated into this study. The proposed technique gives superior results with regards to congestion cost and losses compared with various recent optimization algorithms.

Suggested Citation

  • Jagadeeswar Reddy Chintam & Mary Daniel, 2018. "Real-Power Rescheduling of Generators for Congestion Management Using a Novel Satin Bowerbird Optimization Algorithm," Energies, MDPI, vol. 11(1), pages 1-16, January.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:1:p:183-:d:126726
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    References listed on IDEAS

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    1. Seth W. Coleman & Gail L. Patricelli & Gerald Borgia, 2004. "Variable female preferences drive complex male displays," Nature, Nature, vol. 428(6984), pages 742-745, April.
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    Cited by:

    1. Hossein Moayedi & Amir Mosavi, 2021. "Electrical Power Prediction through a Combination of Multilayer Perceptron with Water Cycle Ant Lion and Satin Bowerbird Searching Optimizers," Sustainability, MDPI, vol. 13(4), pages 1-18, February.
    2. Anurag Gautam & Ibraheem & Gulshan Sharma & Mohammad F. Ahmer & Narayanan Krishnan, 2023. "Methods and Methodologies for Congestion Alleviation in the DPS: A Comprehensive Review," Energies, MDPI, vol. 16(4), pages 1-28, February.
    3. Hegazy Rezk & Ahmed Fathy & Ahmed A. Zaki Diab & Mujahed Al-Dhaifallah, 2019. "The Application of Water Cycle Optimization Algorithm for Optimal Placement of Wind Turbines in Wind Farms," Energies, MDPI, vol. 12(22), pages 1-19, November.

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