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GA Based Multi-stage Transmission Network Expansion Planning

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Soft Computing Applications (SOFA 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 633))

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Abstract

The paper is focusing on dynamic transmission network expansion planning (DTNEP). The DTNEP problem has been approached from the retrospective and prospective point of view. To achieve this goal, the authors are developing two software tools in Matlab environment. Power flow computing is performed using conventional methods. Optimal power flow and network expansion are performed using artificial intelligence methods. Within this field, two techniques have been tackled: particle swarm optimization (PSO) and genetic algorithms (GA). The case study refers to a real power system modeled on the Center, Northern, Eastern and Southern parts of the Romanian Power System.

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Author information

Authors and Affiliations

  1. Power Systems Department, Power Systems Analysis and Optimization Research Center, Politehnica University Timisoara, 2, Pta. Victoriei, Timisoara, Romania

    A. Simo, St. Kilyeni & C. Barbulescu

Authors
  1. A. Simo
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  2. St. Kilyeni
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  3. C. Barbulescu
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Corresponding author

Correspondence to C. Barbulescu .

Editor information

Editors and Affiliations

  1. Department of Automatics and Applied Informatics, Faculty of Engineering, Aurel Vlaicu University of Arad, Arad, Romania

    Valentina Emilia Balas

  2. University of Canberra, Canberra, Aust Capital Terr, Australia

    Lakhmi C. Jain

  3. Department of Automatics and Applied Informatics, Faculty of Engineering, Aurel Vlaicu University of Arad, Arad, Romania

    Marius Mircea Balas

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Simo, A., Kilyeni, S., Barbulescu, C. (2018). GA Based Multi-stage Transmission Network Expansion Planning. In: Balas, V., Jain, L., Balas, M. (eds) Soft Computing Applications. SOFA 2016. Advances in Intelligent Systems and Computing, vol 633. Springer, Cham. https://doi.org/10.1007/978-3-319-62521-8_5

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  • DOI: https://doi.org/10.1007/978-3-319-62521-8_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-62520-1

  • Online ISBN: 978-3-319-62521-8

  • eBook Packages: EngineeringEngineering (R0)

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