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A Rigid Cuckoo Search Algorithm for Solving Short-Term Hydrothermal Scheduling Problem

Author

Listed:
  • Cui Zheyuan

    (School of Computer Science, Baoji University of Arts and Sciences, Baoji 721007, China
    Faculty of Management and Economics, Universiti Pendidikan Sultan Idris, Tanjong Malim 35900, Malaysia
    Both have contributed equally (first and co-first author).)

  • Ali Thaeer Hammid

    (Computer Engineering Techniques Department, Faculty of Information Technology, Imam Ja’afar Al-Sadiq University, Baghdad 10012, Iraq
    Both have contributed equally (first and co-first author).)

  • Ali Noori Kareem

    (Computer Engineering Department, Bilad Alrafidain University College, Ba’aqubah, Diyala 32001, Iraq)

  • Mingxin Jiang

    (Faculty of Electronic Information Engineering, Huaiyin Institute of Technology, Huaian 223003, China)

  • Muamer N. Mohammed

    (Information Technology Department, Community College of Qatar (CCQ), Doha 00974, Qatar)

  • Nallapaneni Manoj Kumar

    (School of Energy and Environment, City University of Hong Kong, Kowloon, Hong Kong, China)

Abstract

The key criteria of the short-term hydrothermal scheduling (StHS) problem is to minimize the gross fuel cost for electricity production by scheduling the hydrothermal power generators considering the constraints related to power balance; the gross release of water, and storage limitations of the reservoir, and the operating limitations of the thermal generators and hydropower plants. For addressing the same problem, numerous algorithms were being used, and related studies exist in the literature; however, they possess limitations concerning the solution state and the number of iterations it takes to reach the solution state. Hence, this article proposes using an enhanced cuckoo search algorithm (CSA) called the rigid cuckoo search algorithm (RCSA), a modified version of the traditional CSA for solving the StHS problem. The proposed RCSA improves the solution state and decreases the iteration numbers related to the CSA with a modified Lévy flight. Here, the movement distances are divided into multiple possible steps, which has infinite diversity. The effectiveness of RCSA has been validated by considering the hydrothermal power system. The observed results reveal the superior performance of RCSA among all other compared algorithms that recently have been used for the StHS problem. It is also observed that the RCSA approach has achieved minimum gross costs than other techniques. Thus, the proposed RCSA proves to be a highly effective and convenient approach for addressing the StHS problems

Suggested Citation

  • Cui Zheyuan & Ali Thaeer Hammid & Ali Noori Kareem & Mingxin Jiang & Muamer N. Mohammed & Nallapaneni Manoj Kumar, 2021. "A Rigid Cuckoo Search Algorithm for Solving Short-Term Hydrothermal Scheduling Problem," Sustainability, MDPI, vol. 13(8), pages 1-14, April.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:8:p:4277-:d:534645
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    References listed on IDEAS

    as
    1. Nguyen, Thang Trung & Vo, Dieu Ngoc & Dinh, Bach Hoang, 2018. "An effectively adaptive selective cuckoo search algorithm for solving three complicated short-term hydrothermal scheduling problems," Energy, Elsevier, vol. 155(C), pages 930-956.
    2. Zhujun Zhang & Wei Fan & Weicheng Bao & Chen-Tung A Chen & Shuo Liu & Yong Cai, 2020. "Recent Developments of Exploration and Detection of Shallow-Water Hydrothermal Systems," Sustainability, MDPI, vol. 12(21), pages 1-17, November.
    3. Nguyen, Thang Trung & Vo, Dieu Ngoc & Truong, Anh Viet, 2014. "Cuckoo search algorithm for short-term hydrothermal scheduling," Applied Energy, Elsevier, vol. 132(C), pages 276-287.
    4. Liu Xinchun & Kang Yongde & Chen Hongna & Lu Hui, 2021. "Hydrothermal Effects of Freeze-Thaw in the Taklimakan Desert," Sustainability, MDPI, vol. 13(3), pages 1-12, January.
    5. Ali Thaeer Hammid & Omar I. Awad & Mohd Herwan Sulaiman & Saraswathy Shamini Gunasekaran & Salama A. Mostafa & Nallapaneni Manoj Kumar & Bashar Ahmad Khalaf & Yasir Amer Al-Jawhar & Raed Abdulkareem A, 2020. "A Review of Optimization Algorithms in Solving Hydro Generation Scheduling Problems," Energies, MDPI, vol. 13(11), pages 1-21, June.
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