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A Biologically Inspired Modified Flower Pollination Algorithm for Solving Economic Dispatch Problems in Modern Power Systems

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Abstract

Gradient-based traditional algorithms fail to locate optimal solutions for real-world problems with non-differentiable/discontinuous objective functions. But biologically inspired optimization algorithms, due to their unconventional random search capability, provide good solutions within finite time to multimodal and non-convex problems. The search capability of these methods largely depends on their exploration and exploitation potential. This paper presents a modified flower pollination algorithm (MFPA) in which (1) the local pollination of FPA is controlled by a scaling factor and (2) an intensive exploitation phase is added to tune the best solution. The effectiveness of MFPA is tested on some mathematical benchmarks and four large practical power system test cases.

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Authors and Affiliations

  1. Department of Electrical Engineering, Madhav Institute of Technology and Science, Gwalior, M.P., India

    Hari Mohan Dubey & Manjaree Pandit

  2. Department of Electrical Engineering, Indian Institute of Technology, Hauz Khas, New Delhi, India

    B. K. Panigrahi

Authors
  1. Hari Mohan Dubey
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  2. Manjaree Pandit
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  3. B. K. Panigrahi
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Correspondence to Manjaree Pandit.

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Dubey, H.M., Pandit, M. & Panigrahi, B.K. A Biologically Inspired Modified Flower Pollination Algorithm for Solving Economic Dispatch Problems in Modern Power Systems. Cogn Comput 7, 594–608 (2015). https://doi.org/10.1007/s12559-015-9324-1

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  • DOI: https://doi.org/10.1007/s12559-015-9324-1

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