Hybrid GA and PSO Approach for Transmission Expansion Planning

  • Shilpi Sisodia
  • Yogendra Kumar
  • Arun Kumar Wadhwani
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 381)


Metaheuristic techniques are enormously being used nowadays for their applications in field like Power system and are being applied to many optimization problems of power system due to difficult approach of classical methods. Transmission expansion planning (TEP) is a challenging task to deal in power system. A new approach, hybrid genetic algorithm particle swarm optimization (HGAPSO) for solving TEP problem, is introduced to eliminate the drawback of GA and PSO. Problems of immature convergence in particle swarm optimization (PSO) and low convergence speed in genetic algorithm (GA) mitigate to the hybridization of both techniques. Proposed HGAPSO Algorithm is tested for three standard electric test systems for TEP problem in MATLAB tool. Experimental results found by HGAPSO are compared with GA and PSO Algorithm to test its performance for TEP problem.


Metaheuristic GA HGAPSO PSO TEP 


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Copyright information

© Springer India 2016

Authors and Affiliations

  • Shilpi Sisodia
    • 1
  • Yogendra Kumar
    • 2
  • Arun Kumar Wadhwani
    • 3
  1. 1.Electrical Engineering DepartmentRajiv Gandhi Proudyogiki Vishwavidhalaya UniversityBhopalIndia
  2. 2.Department of Electrical EngineeringMaulana Azad National Institute of TechnologyBhopalIndia
  3. 3.Department of Electrical EngineeringMadhav Institute of Technology and ScienceGwaliorIndia

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