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Optimal short-term generation scheduling of hydrothermal systems by implementation of real-coded genetic algorithm based on improved Mühlenbein mutation

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  • Nazari-Heris, M.
  • Mohammadi-Ivatloo, B.
  • Haghrah, A.

Abstract

The short-term hydrothermal scheduling (STHS) problem is providing a daily planning of hydro and thermal generations, aiming to minimize the total fuel cost of thermal plants. The minimization of total operation cost of hydrothermal power system is considered as a complex nonlinear hard optimization problem with a series of several equality and inequality constraints. This paper proposes real-coded genetic algorithm with an improved Mühlenbein mutation (RCGA-IMM) for the solution of STHS optimization problem, considering the minimization of operation cost which satisfies hydraulic and electrical constraints. The proposed optimization procedure is employed on two test systems in which different constraints have been taken into account including valve point loading effect of thermal units and transmission losses. The provided optimal solutions have been compared with recent studies in this area, which manifest superiority of the proposed method. It is found that the proposed RCGA-IMM has the capability of obtaining better solutions with respect to other optimization methods which are implemented on STHS problem.

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  • Nazari-Heris, M. & Mohammadi-Ivatloo, B. & Haghrah, A., 2017. "Optimal short-term generation scheduling of hydrothermal systems by implementation of real-coded genetic algorithm based on improved Mühlenbein mutation," Energy, Elsevier, vol. 128(C), pages 77-85.
    • Handle: RePEc:eee:energy:v:128:y:2017:i:c:p:77-85
    DOI: 10.1016/j.energy.2017.04.007
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    References listed on IDEAS

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    1. Soroudi, Alireza, 2013. "Robust optimization based self scheduling of hydro-thermal Genco in smart grids," Energy, Elsevier, vol. 61(C), pages 262-271.
    2. Wang, Yongqiang & Zhou, Jianzhong & Mo, Li & Zhang, Rui & Zhang, Yongchuan, 2012. "Short-term hydrothermal generation scheduling using differential real-coded quantum-inspired evolutionary algorithm," Energy, Elsevier, vol. 44(1), pages 657-671.
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    Citations

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    Cited by:

    1. Omid Hoseynpour & Behnam Mohammadi-ivatloo & Morteza Nazari-Heris & Somayeh Asadi, 2017. "Application of Dynamic Non-Linear Programming Technique to Non-Convex Short-Term Hydrothermal Scheduling Problem," Energies, MDPI, vol. 10(9), pages 1-17, September.
    2. Lei, Kaixuan & Chang, Jianxia & Long, Ruihao & Wang, Yimin & Zhang, Hongxue, 2022. "Cascade hydropower station risk operation under the condition of inflow uncertainty," Energy, Elsevier, vol. 244(PA).
    3. Simab, Mohsen & Javadi, Mohammad Sadegh & Nezhad, Ali Esmaeel, 2018. "Multi-objective programming of pumped-hydro-thermal scheduling problem using normal boundary intersection and VIKOR," Energy, Elsevier, vol. 143(C), pages 854-866.
    4. Ghahramani, Mehrdad & Nazari-Heris, Morteza & Zare, Kazem & Mohammadi-Ivatloo, Behnam, 2022. "A two-point estimate approach for energy management of multi-carrier energy systems incorporating demand response programs," Energy, Elsevier, vol. 249(C).
    5. Suresh K. Damodaran & T. K. Sunil Kumar, 2018. "Hydro-Thermal-Wind Generation Scheduling Considering Economic and Environmental Factors Using Heuristic Algorithms," Energies, MDPI, vol. 11(2), pages 1-19, February.
    6. Nazari-Heris, Morteza & Babaei, Amir Fakhim & Mohammadi-Ivatloo, Behnam & Asadi, Somayeh, 2018. "Improved harmony search algorithm for the solution of non-linear non-convex short-term hydrothermal scheduling," Energy, Elsevier, vol. 151(C), pages 226-237.
    7. Maha Mohamed & Abdel-Raheem Youssef & Salah Kamel & Mohamed Ebeed & Ehab E. Elattar, 2021. "Optimal Scheduling of Hydro–Thermal–Wind–Photovoltaic Generation Using Lightning Attachment Procedure Optimizer," Sustainability, MDPI, vol. 13(16), pages 1-24, August.
    8. Ruhong Zhong & Chuntian Cheng & Shengli Liao & Zhipeng Zhao, 2020. "Short-Term Scheduling of Expected Output-Sensitive Cascaded Hydro Systems Considering the Provision of Reserve Services," Energies, MDPI, vol. 13(10), pages 1-15, May.
    9. Sakthivel, V.P. & Thirumal, K. & Sathya, P.D., 2022. "Quasi-oppositional turbulent water flow-based optimization for cascaded short term hydrothermal scheduling with valve-point effects and multiple fuels," Energy, Elsevier, vol. 251(C).
    10. 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).
    11. 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.
    12. Panda, Debashish & Ramteke, Manojkumar, 2019. "Preventive crude oil scheduling under demand uncertainty using structure adapted genetic algorithm," Applied Energy, Elsevier, vol. 235(C), pages 68-82.
    13. 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.
    14. Nazari-Heris, Morteza & Mohammadi-Ivatloo, Behnam & Zare, Kazem & Siano, Pierluigi, 2020. "Optimal generation scheduling of large-scale multi-zone combined heat and power systems," Energy, Elsevier, vol. 210(C).

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