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Intelligent Genetic Algorithm for Generation Scheduling under Deregulated Environment

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Swarm, Evolutionary, and Memetic Computing (SEMCCO 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7076))

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Abstract

This paper presents an Intelligent Genetic Algorithm (IGA) solution to Generation Scheduling (GS) problem under deregulated environment. In the deregulated market, generating companies (Gencos) will operate with an objective of maximizing their profit, while satisfying the system constraints. Using an intelligent encoding scheme, the minimum up/down time constraints are easily satisfied. Performance of the algorithm is tested on a 10-unit 24-hour unit commitment test system. It is observed from the results, the profit obtained by the proposed algorithm is encouraging to the Gencos.

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Author information

Authors and Affiliations

  1. Kalasalingam University, Anand Nagar, Krishnankoil, India

    Sundararajan Dhanalakshmi & Subramanian Kannan

  2. Thiagarajar College of Engineering, Madurai, India

    Subramanian Baskar

  3. PSNACollege of Engineering and Technology, Dindugal, India

    Krishnan Mahadevan

Authors
  1. Sundararajan Dhanalakshmi
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  2. Subramanian Kannan
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  3. Subramanian Baskar
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  4. Krishnan Mahadevan
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Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, IIT Delhi, India

    Bijaya Ketan Panigrahi

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

    Ponnuthurai Nagaratnam Suganthan

  3. Department of Electronics and Telecommunications, Jadavpur University, 700032, Kolkata, India

    Swagatam Das

  4. ANITS, Visakhapatnam, India

    Suresh Chandra Satapathy

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© 2011 Springer-Verlag Berlin Heidelberg

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Dhanalakshmi, S., Kannan, S., Baskar, S., Mahadevan, K. (2011). Intelligent Genetic Algorithm for Generation Scheduling under Deregulated Environment. In: Panigrahi, B.K., Suganthan, P.N., Das, S., Satapathy, S.C. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2011. Lecture Notes in Computer Science, vol 7076. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27172-4_35

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  • DOI: https://doi.org/10.1007/978-3-642-27172-4_35

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-27171-7

  • Online ISBN: 978-3-642-27172-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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