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Constrained optimal power flow and optimal TCSC allocation using hybrid cuckoo search and ant lion optimizer

Author

Listed:
  • Sheila Mahapatra

    (Alliance University)

  • Nitin Malik

    (The NorthCap University)

  • Saurav Raj

    (Marathwada Campus)

  • Mohan Krishna Srinivasan

    (Alliance University)

Abstract

This paper works on the solution to Voltage Constrained Optimal Power Flow (VCOPF) problem with the requisite allocation of thyristor-controlled series compensator (TCSC) in IEEE 6-bus and 14-bus transmission network to cut down system power losses and to revamp bus voltage profile. The Newton–Raphson algorithm computes the power flow under normal and overloaded operating conditions. The optimal TCSC location is identified by the Cuckoo Search algorithm (CS) and optimal size is determined using an ant-lion optimizer (ALO). The quadratic fuel cost is chosen as the objective and is subjugated to the equality and inequality constraints. The proposed methodology is validated by contrasting the results to the other hybrid methods such as Fuzzy-Gravitational search algorithm (F-GSA), Improved GSA-Firefly algorithm (IGSA-FA) and Radial basis function neural network-GSA (RBFNN-GSA). The statistical analysis is also carried out for validating the efficacy of the algorithm when compared with other reported methods in the literature. The simulation results obtained on standard test systems manifest the improved performance of proposed hybrid cuckoo search and ant lion optimizer (CS-ALO) in comparison with the other optimization techniques that have emerged in the recent state-of-the-art-literature.

Suggested Citation

  • Sheila Mahapatra & Nitin Malik & Saurav Raj & Mohan Krishna Srinivasan, 2022. "Constrained optimal power flow and optimal TCSC allocation using hybrid cuckoo search and ant lion optimizer," 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(2), pages 721-734, April.
    • Handle: RePEc:spr:ijsaem:v:13:y:2022:i:2:d:10.1007_s13198-021-01334-1
    DOI: 10.1007/s13198-021-01334-1
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    References listed on IDEAS

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    1. Nguyen, Thang Trung, 2019. "A high performance social spider optimization algorithm for optimal power flow solution with single objective optimization," Energy, Elsevier, vol. 171(C), pages 218-240.
    2. Saurav Raj & Sheila Mahapatra & Chandan Kumar Shiva & Biplab Bhattacharyya, 2021. "Implementation and Optimal Sizing of TCSC for the Solution of Reactive Power Planning Problem Using Quasi-Oppositional Salp Swarm Algorithm," International Journal of Energy Optimization and Engineering (IJEOE), IGI Global, vol. 10(2), pages 74-103, April.
    3. Zhang, Jingrui & Wang, Silu & Tang, Qinghui & Zhou, Yulu & Zeng, Tao, 2019. "An improved NSGA-III integrating adaptive elimination strategy to solution of many-objective optimal power flow problems," Energy, Elsevier, vol. 172(C), pages 945-957.
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    Cited by:

    1. Mousumi Banerjee & Vanita Garg & Kusum Deep, 2023. "Solving structural and reliability optimization problems using efficient mutation strategies embedded in sine cosine 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. 14(1), pages 307-327, March.

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