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Quadratic Approximation PSO for Economic Dispatch Problems with Valve-Point Effects

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Book cover Swarm, Evolutionary, and Memetic Computing (SEMCCO 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6466))

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Abstract

Quadratic Approximation Particle Swarm Optimization (qPSO) is a variant of Particle Swarm Optimization (PSO) which hybridize Quadratic Approximation Operator (QA) with PSO. qPSO is already proven to be cost effective and reliable for the test problems of continuous optimization. Economic dispatch (ED) problem is one of the fundamental issues in power system operations. The problem of economic dispatch turns out to be a continuous optimization problem which is solved using original PSO and its variant qPSO in expectation of better results. Results are also compared with the earlier published results.

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Author information

Authors and Affiliations

  1. ABV- Indian Institute of Information Technology and Management, Gwalior, India

    Jagdish Chand Bansal

  2. Department of Mathematics, Indian Institute of Technology Roorkee, India

    Kusum Deep

Authors
  1. Jagdish Chand Bansal
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  2. Kusum Deep
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Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, Indian Institute of Technology, New Delhi, India

    Bijaya Ketan Panigrahi

  2. Department of Electronics and Communication Engineering, Jadavpur University, 700032, Kolkata, West Bengal, India

    Swagatam Das

  3. School of Electrical and Electronic Engineering, Nanyang Technological University, 639798, Singapore

    Ponnuthurai Nagaratnam Suganthan

  4. Department of Electrical and Electronics Engineering, SRM University, Chennai, Tamil Nadu, India

    Subhransu Sekhar Dash

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© 2010 Springer-Verlag Berlin Heidelberg

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Bansal, J.C., Deep, K. (2010). Quadratic Approximation PSO for Economic Dispatch Problems with Valve-Point Effects. In: Panigrahi, B.K., Das, S., Suganthan, P.N., Dash, S.S. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2010. Lecture Notes in Computer Science, vol 6466. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17563-3_55

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  • DOI: https://doi.org/10.1007/978-3-642-17563-3_55

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17562-6

  • Online ISBN: 978-3-642-17563-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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