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Hybrid Methodology for Optimal Allocation of Synchronous Generator-Based DG

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Ambient Communications and Computer Systems

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 696))

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Abstract

In this paper, a hybrid methodology is implemented for optimal allocation of synchronous generator-based dispersed generation, for minimization of power losses in distribution system considering voltage dependent practical loads. The proposed hybrid approach is a combination of equivalent current injection-based sensitivity factor and particle swarm optimization. Sensitivity factors advantages in reducing the search space and optimal allocation of synchronous generator-based DG are obtained by particle swarm optimization for the diminution of power losses. The suggested method is validated on 33-bus and 69-bus radial distribution system. The results show significant improvement in voltage profile of all buses after optimal allocation of DG in distribution system.

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Authors and Affiliations

  1. Department of Electrical and Instrumentation Engineering, Thapar University, Patiala, India

    Navdeep Kaur & Sanjay Kumar Jain

Authors
  1. Navdeep Kaur
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  2. Sanjay Kumar Jain
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Correspondence to Navdeep Kaur .

Editor information

Editors and Affiliations

  1. University of Murcia, Murcia, Spain

    Gregorio Martinez Perez

  2. Department of Computer Science and Engineering, ABES Engineering College, Ghaziabad, Uttar Pradesh, India

    Shailesh Tiwari

  3. Department of Computer Science and Engineering, ABES Engineering College, Ghaziabad, Uttar Pradesh, India

    Munesh C. Trivedi

  4. Department of Computer Science and Engineering, Motilal Nehru National Institute of Technology, Allahabad, Uttar Pradesh, India

    Krishn K. Mishra

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Kaur, N., Jain, S.K. (2018). Hybrid Methodology for Optimal Allocation of Synchronous Generator-Based DG. In: Perez, G., Tiwari, S., Trivedi, M., Mishra, K. (eds) Ambient Communications and Computer Systems. Advances in Intelligent Systems and Computing, vol 696. Springer, Singapore. https://doi.org/10.1007/978-981-10-7386-1_8

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  • DOI: https://doi.org/10.1007/978-981-10-7386-1_8

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-7385-4

  • Online ISBN: 978-981-10-7386-1

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