International Journal of Energy and Power Engineering

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Application of Artificial Intelligence Technique to Economic Load Dispatch of Thermal Power Generation Unit

Received: 05 November 2014    Accepted: 10 November 2014    Published: 12 November 2014
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Abstract

Economic Dispatch(ED) is one of the main problem of power system operation and control which determines the optimal real power settings of generating units with an objective of minimizing the total fuel cost, subjected to limits on generator real power output & transmission losses. In all practical cases, the fuel cost of generator can be represented as a quadratic function of real power generation. This paper describe and Introduce a new nature Inspired Artificial Intelligence method called Firefly Algorithm(FA). The Firefly Algorithm is a stochastic Meta heuristic approach based on the idealized behavior of the flashing characteristics of fireflies. The aim is to minimize the generating unit’s combined fuel cost having quadratic cost characteristics subjected to limits on generator real power output & transmission losses. This paper presents an application of the FA to ED with valve point loading for different Test Case system. The obtained solution quality and computation efficiency is compared to another artificial intelligence technique, called Genetic algorithm (GA) . The simulation results show that the proposed algorithm outperforms previous artificial intelligence method.

DOI 10.11648/j.ijepe.s.2014030602.13
Published in International Journal of Energy and Power Engineering (Volume 3, Issue 6-2, December 2014)

This article belongs to the Special Issue Distributed Energy Generation and Smart Grid

Page(s) 15-20
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This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Economic Dispatch, Firefly Algorithm, Genetic Algorithm

References
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[16] Pereira-Neto A, Unsihuay C, Saavedra OR. Efficient evolutionary strategy optimisation procedure to solve the nonconvex economic dispatch problem with generator constraints. IEEE Proc Gener Transm Distrib 2005;152(5):653–60.
[17] Fan JY, Zhang L. Real-time economic dispatch with line flow and emission constraints using quadratic programming. IEEE Trans Power Syst 1998;13(2):320–5.
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[19] Pereira-Neto A, Unsihuay C, Saavedra OR. Efficient evolutionary strategy optimisation procedure to solve the nonconvex economic dispatch problem with generator constraints. IEEE Proc Gener Transm Distrib 2005;152(5):653–60.
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Author Information
  • Engg Department, LNCT, Indore, India

  • Electrical Engg Department, SVITS, Indore, India

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  • APA Style

    Pragya Nema, Shraddha Gajbhiye. (2014). Application of Artificial Intelligence Technique to Economic Load Dispatch of Thermal Power Generation Unit. International Journal of Energy and Power Engineering, 3(6-2), 15-20. https://doi.org/10.11648/j.ijepe.s.2014030602.13

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    ACS Style

    Pragya Nema; Shraddha Gajbhiye. Application of Artificial Intelligence Technique to Economic Load Dispatch of Thermal Power Generation Unit. Int. J. Energy Power Eng. 2014, 3(6-2), 15-20. doi: 10.11648/j.ijepe.s.2014030602.13

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    AMA Style

    Pragya Nema, Shraddha Gajbhiye. Application of Artificial Intelligence Technique to Economic Load Dispatch of Thermal Power Generation Unit. Int J Energy Power Eng. 2014;3(6-2):15-20. doi: 10.11648/j.ijepe.s.2014030602.13

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  • @article{10.11648/j.ijepe.s.2014030602.13,
      author = {Pragya Nema and Shraddha Gajbhiye},
      title = {Application of Artificial Intelligence Technique to Economic Load Dispatch of Thermal Power Generation Unit},
      journal = {International Journal of Energy and Power Engineering},
      volume = {3},
      number = {6-2},
      pages = {15-20},
      doi = {10.11648/j.ijepe.s.2014030602.13},
      url = {https://doi.org/10.11648/j.ijepe.s.2014030602.13},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ijepe.s.2014030602.13},
      abstract = {Economic Dispatch(ED) is one of the main problem of power system operation and control which determines the optimal real power settings of generating units with an objective of minimizing the total fuel cost, subjected to limits on generator real power output & transmission losses. In all practical cases, the fuel cost of generator can be represented as a quadratic function of real power generation. This paper describe and Introduce a new nature Inspired Artificial Intelligence method called Firefly Algorithm(FA). The Firefly Algorithm is a stochastic Meta heuristic approach based on the idealized behavior of the flashing characteristics of fireflies. The aim is to minimize the generating unit’s combined fuel cost having quadratic cost characteristics subjected to limits on generator real power output & transmission losses. This paper presents an application of the FA to ED with valve point loading for different Test Case system. The obtained solution quality and computation efficiency is compared to another artificial intelligence technique, called Genetic algorithm (GA) . The simulation results show that the proposed algorithm outperforms previous artificial intelligence method.},
     year = {2014}
    }
    

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    T1  - Application of Artificial Intelligence Technique to Economic Load Dispatch of Thermal Power Generation Unit
    AU  - Pragya Nema
    AU  - Shraddha Gajbhiye
    Y1  - 2014/11/12
    PY  - 2014
    N1  - https://doi.org/10.11648/j.ijepe.s.2014030602.13
    DO  - 10.11648/j.ijepe.s.2014030602.13
    T2  - International Journal of Energy and Power Engineering
    JF  - International Journal of Energy and Power Engineering
    JO  - International Journal of Energy and Power Engineering
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    EP  - 20
    PB  - Science Publishing Group
    SN  - 2326-960X
    UR  - https://doi.org/10.11648/j.ijepe.s.2014030602.13
    AB  - Economic Dispatch(ED) is one of the main problem of power system operation and control which determines the optimal real power settings of generating units with an objective of minimizing the total fuel cost, subjected to limits on generator real power output & transmission losses. In all practical cases, the fuel cost of generator can be represented as a quadratic function of real power generation. This paper describe and Introduce a new nature Inspired Artificial Intelligence method called Firefly Algorithm(FA). The Firefly Algorithm is a stochastic Meta heuristic approach based on the idealized behavior of the flashing characteristics of fireflies. The aim is to minimize the generating unit’s combined fuel cost having quadratic cost characteristics subjected to limits on generator real power output & transmission losses. This paper presents an application of the FA to ED with valve point loading for different Test Case system. The obtained solution quality and computation efficiency is compared to another artificial intelligence technique, called Genetic algorithm (GA) . The simulation results show that the proposed algorithm outperforms previous artificial intelligence method.
    VL  - 3
    IS  - 6-2
    ER  - 

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