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An effectively adaptive selective cuckoo search algorithm for solving three complicated short-term hydrothermal scheduling problems

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  • Nguyen, Thang Trung
  • Vo, Dieu Ngoc
  • Dinh, Bach Hoang

Abstract

This paper proposes an effectively adaptive selective cuckoo search algorithm (ASCSA) for solving short-term hydrothermal scheduling problems with available water constraint, reservoir volume constraints, and transmission network constraints. The proposed ASCSA is a newly improved version of the conventional cuckoo search algorithm to enhance the solution quality and reduce the maximum number of iterations based on two new techniques including the new ratio of the difference between the fitness function values and the integration of solutions into one group. The effectiveness of ASCSA has been validated via eight hydrothermal systems, in which the last two systems consisting of the IEEE 30-bus and IEEE 118-bus systems are considered with a set of constraints in the transmission network. To investigate the performance of ASCSA, several algorithms are also implemented in the paper such as conventional cuckoo search algorithm, modified cuckoo search algorithm, particle swarm optimization, global vision of particle swarm optimization with inertia weight, differential evolution, and improved differential evolution. From result comparisons of the test systems, the proposed ASCSA method has obtained lower total costs than other methods implemented for solving the problems. Therefore, the proposed ASCSA is a very efficient and favorable method for solving the considered hydrothermal scheduling problems.

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  • 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.
    • Handle: RePEc:eee:energy:v:155:y:2018:i:c:p:930-956
    DOI: 10.1016/j.energy.2018.05.037
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    References listed on IDEAS

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    Cited by:

    1. Basu, Mousumi, 2022. "Fuel constrained short-term hydrothermal generation scheduling," Energy, Elsevier, vol. 239(PD).
    2. Thuan Thanh Nguyen & Bach Hoang Dinh & Thai Dinh Pham & Thang Trung Nguyen, 2020. "Active Power Loss Reduction for Radial Distribution Systems by Placing Capacitors and PV Systems with Geography Location Constraints," Sustainability, MDPI, vol. 12(18), pages 1-30, September.
    3. 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.
    4. Saqib Akram & Muhammad Salman Fakhar & Syed Abdul Rahman Kashif & Ghulam Abbas & Nasim Ullah & Alsharef Mohammad & Mohamed Emad Farrag, 2022. "Introducing Adaptive Machine Learning Technique for Solving Short-Term Hydrothermal Scheduling with Prohibited Discharge Zones," Sustainability, MDPI, vol. 14(18), pages 1-18, September.
    5. Yin, Hao & Wu, Fei & Meng, Xin & Lin, Yicheng & Fan, Jingmin & Meng, Anbo, 2020. "Crisscross optimization based short-term hydrothermal generation scheduling with cascaded reservoirs," Energy, Elsevier, vol. 203(C).
    6. Chuanxiong Kang & Shaofei Wu & Eid Gul & Xiang Yu & Pingan Ren, 2022. "A 1D linearization–based MILP–NLP method for short-term hydrothermal operation [Hybrid generation of renewables increases the energy system’s robustness in a changing climate]," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 17, pages 540-549.
    7. Razavi, Seyed-Ehsan & Esmaeel Nezhad, Ali & Mavalizadeh, Hani & Raeisi, Fatima & Ahmadi, Abdollah, 2018. "Robust hydrothermal unit commitment: A mixed-integer linear framework," Energy, Elsevier, vol. 165(PB), pages 593-602.
    8. Jian, Jinbao & Pan, Shanshan & Yang, Linfeng, 2019. "Solution for short-term hydrothermal scheduling with a logarithmic size mixed-integer linear programming formulation," Energy, Elsevier, vol. 171(C), pages 770-784.

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