IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/93971.html
   My bibliography  Save this paper

Fast Security Constraint Unit Commitment by Utilizing Chaotic Crow Search Algorithm

Author

Listed:
  • Patel, Abhishek
  • Anand, Rajesh

Abstract

This paper investigates the optimal operation of security constraint unit commitment (SCUC) as one of the most important concern in power system operation. SCUC is a mixed integer nonlinear problem (MINLP) which is hard to solve and also the optimal solution is not guarantee. To overcome this drawback, a new evolutionary method known as the chaotic crow search algorithm is developed. The proposed problem includes some significant constraints such as spinning reserve, generators ramp rate, load balance, and power limits. Finally, the proposed method is examined on a 10-unit distribution network. The results show the effectiveness and merit of the proposed technique.

Suggested Citation

  • Patel, Abhishek & Anand, Rajesh, 2019. "Fast Security Constraint Unit Commitment by Utilizing Chaotic Crow Search Algorithm," MPRA Paper 93971, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:93971
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/93971/1/MPRA_paper_93971.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ashkaboosi, Maryam & Ashkaboosi, Farnoosh & Nourani, Seyed Mehdi, 2016. "The Interaction of Cybernetics and Contemporary Economic Graphic Art as "Interactive Graphics"," MPRA Paper 72717, University Library of Munich, Germany.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Khazaei, Ehsan & Jamaledini, Ashkan & Soltani, Ali, 2020. "Economic Operation of Islanded Microgrids Based on the Region Search Evolutionary Algorithm," MPRA Paper 102092, University Library of Munich, Germany.
    2. Mirzaei, Farzad & Ashkaboosi, Farnoosh & Mahdavi, Sadegh, 2016. "Economic Based Neural Control Switching of TCR and TSC for Optimal Reactive Power Flow and Harmonic Minimization with Fuzzy-Genetic," MPRA Paper 73480, University Library of Munich, Germany.
    3. Bayat, Alireza & Khazaei, Ehsan & Mahdavi, Sadegh, 2019. "Economic-Based Synchronization and Control of New Fractional-Order Chaotic System Based on Lyapunov Theorem," MPRA Paper 95394, University Library of Munich, Germany.
    4. Jamaledini, Ashkan & Khazaei, Ehsan & Bitaraf, Mohammd, 2019. "Solving the Grid-Connected Microgrid Operation by JAYA Algorithm," MPRA Paper 94277, University Library of Munich, Germany.
    5. Patel, Abhishek & Anand, Rajesh, 2019. "Particle Swarm Optimization-Based Multispectral Image Fusion for Minimizing Spectral Loss," MPRA Paper 94006, University Library of Munich, Germany.
    6. Tavakoli, Amir & Mirzaei, Farzad & Tashakori, Sajad, 2018. "A New Optimal Operation Structure For Renewable- Based Microgrid Operation based On Teaching Learning Based Optimization Algorithm," MPRA Paper 89203, University Library of Munich, Germany.
    7. Khazaei, Ehsan & Jamaledini, Ashkan, 2019. "Islanded Microgrid Operation Based on the Chaotic Crow Search Algorithm," MPRA Paper 94278, University Library of Munich, Germany.
    8. Jamaledini, Ashkan & Soltani, Ali & Khazaei, Ehsan, 2020. "Region Search Optimization Algorithm for Economic Energy Management of Grid-Connected Mode Microgrid," MPRA Paper 102094, University Library of Munich, Germany.
    9. Seruca, Manuel & Mota, Andrade & Rodrigues, David, 2019. "Solving the Economic Scheduling of Grid-Connected Microgrid Based on the Strength Pareto Approach," MPRA Paper 95391, University Library of Munich, Germany.
    10. Wei Hou & Rita Yi Man Li & Thanawan Sittihai, 2022. "Management Optimization of Electricity System with Sustainability Enhancement," Sustainability, MDPI, vol. 14(11), pages 1-17, May.
    11. Jamaledini, Ashkan & Khazaei, Ehsan & Bitaraf, Mohammad, 2019. "Solving the Grid-Connected Microgrid Operation by Teaching Learning Based Optimization Algorithm," MPRA Paper 94276, University Library of Munich, Germany.
    12. Bayat, Alireza & Mahdavi, Sadegh & Mirzaei, Farzad, 2019. "Self- Supplied Microgrid Economic Scheduling Based on Modified Multiverse Evolutionary Algorithm," MPRA Paper 95892, University Library of Munich, Germany.
    13. Mirzaei, Farzad & Mahdavi, Sadegh & Bayat, Alireza, 2019. "Economic Operation of Unit Commitment Using Multiverse Optimization Algorithm," MPRA Paper 95894, University Library of Munich, Germany.
    14. Jian Xiao & Wei Hou, 2022. "Cost Estimation Process of Green Energy Production and Consumption Using Probability Learning Approach," Sustainability, MDPI, vol. 14(12), pages 1-14, June.
    15. Soltani, Ali & Tashakor, Behnam, 2019. "A New Nonconvex quadratic programming Technique: Practical and Fast Solver Method," MPRA Paper 94335, University Library of Munich, Germany.
    16. Jamaledini, Ashkan & Khazaei, Ehsan & Toran, Mehdi, 2018. "Modified Genetic Algorithm Framework for Optimal Scheduling of Single Microgrid Combination with Distribution System Operator," MPRA Paper 89411, University Library of Munich, Germany.
    17. Mahdavi, Sadegh & Bayat, Alireza & Khazaei, Ehsan & Jamaledini, Ashkan, 2019. "Economic Operation of Self-Sustained Microgrid Optimal Operation by Multiobjective Evolutionary Algorithm Based on Decomposition," MPRA Paper 95393, University Library of Munich, Germany.
    18. Khazaei, Ehsan & Jamaledini, Ashkan, 2019. "Optimal Operation of Islanded Microgrid Operation Based on the JAYA Optimization Algorithm," MPRA Paper 94279, University Library of Munich, Germany.
    19. Rodrigues, David & Seruca, Manuel, 2019. "A Novel Practical and Fast Economic Method Based on Nonconvex Quadratic Programming," MPRA Paper 95392, University Library of Munich, Germany.

    More about this item

    Keywords

    Control and Optimization; Evolutionary Algorithm; Power systems; Reliability; Unit Commitment;
    All these keywords.

    JEL classification:

    • C0 - Mathematical and Quantitative Methods - - General
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • Z0 - Other Special Topics - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:93971. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.