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Hydro-thermal Commitment Scheduling by Tabu Search Method with Cooling-Banking Constraints

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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

This paper presents a new approach for developing an algorithm for solving the Unit Commitment Problem (UCP) in a Hydro-thermal power system. Unit Commitment is a nonlinear optimization problem to determine the minimum cost turn on/off schedule of the generating units in a power system by satisfying both the forecasted load demand and various operating constraints of the generating units. The effectiveness of the proposed hybrid algorithm is proved by the numerical results shown comparing the generation cost solutions and computation time obtained by using Tabu Search Algorithm with other methods like Evolutionary Programming and Dynamic Programming in reaching proper unit commitment.

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References

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Author information

Authors and Affiliations

  1. Department of EEE, Sathyabama University, Chennai, 600 119, India

    Nimain Charan Nayak

  2. Department of EEE, Pondicherry Engg College, Pondicherry, 605 014, India

    C. Christober Asir Rajan

Authors
  1. Nimain Charan Nayak
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  2. C. Christober Asir Rajan
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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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Nayak, N.C., Rajan, C.C.A. (2010). Hydro-thermal Commitment Scheduling by Tabu Search Method with Cooling-Banking Constraints. 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_86

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  • DOI: https://doi.org/10.1007/978-3-642-17563-3_86

  • 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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