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ACOPF-Based Transmission Network Expansion Planning Using Grey Wolf Optimization Algorithm

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Soft Computing for Problem Solving

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 816))

Abstract

Transmission network expansion planning problem (TNEP) is extensive, complicated, nonlinear programmable issue. A cost-effective result of TNEP is required to get the power generation pattern with load demand in economical and reliable manner. In this paper, AC optimal power flow-based TNEP is solved using a recent nature-inspired algorithm, namely grey wolf optimization algorithm (GWO). The GWO is tested to this TNEP for solution of six bus Graver’s system and 24 bus IEEE system. The reported outcomes reveal that GWO is cost-effective and more accurate strategy to solve this TNEP.

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Authors and Affiliations

  1. Rajasthan Technical University, Kota, India

    Ashish Khandelwal, Annapurna Bhargava & Harish Sharma

  2. Government Engineering College, Jhalawar, India

    Ajay Sharma

Authors
  1. Ashish Khandelwal
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  2. Annapurna Bhargava
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  3. Ajay Sharma
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  4. Harish Sharma
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Corresponding author

Correspondence to Ashish Khandelwal .

Editor information

Editors and Affiliations

  1. Department of Mathematics, South Asian University New Delhi , New Delhi, India

    Jagdish Chand Bansal

  2. Department of Mathematics, National Institute Of Technology Silchar Department of Mathematics, Silchar, Assam, India

    Kedar Nath Das

  3. Department of Mathematics and Computer Science, Faculty of Science, , Liverpool Hope University, Liverpool, UK

    Atulya Nagar

  4. Department of Mathematics, Indian Institute of Technology Roor Department of Mathematics, Roorkee, Uttarakhand, India

    Kusum Deep

  5. School of Basic Sciences, Indian Institute of Technology Bhubanesw School of Basic Sciences, Bhubaneswar, Odisha, India

    Akshay Kumar Ojha

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Khandelwal, A., Bhargava, A., Sharma, A., Sharma, H. (2019). ACOPF-Based Transmission Network Expansion Planning Using Grey Wolf Optimization Algorithm. In: Bansal, J., Das, K., Nagar, A., Deep, K., Ojha, A. (eds) Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 816. Springer, Singapore. https://doi.org/10.1007/978-981-13-1592-3_13

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