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Short-Term Scheduling of Expected Output-Sensitive Cascaded Hydro Systems Considering the Provision of Reserve Services

Author

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  • Ruhong Zhong

    (Institute of Hydropower System & Hydroinformatics, Dalian University of Technology, Dalian 116024, China)

  • Chuntian Cheng

    (Institute of Hydropower System & Hydroinformatics, Dalian University of Technology, Dalian 116024, China
    Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education, Dalian University of Technology, Dalian 116024, China)

  • Shengli Liao

    (Institute of Hydropower System & Hydroinformatics, Dalian University of Technology, Dalian 116024, China
    Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education, Dalian University of Technology, Dalian 116024, China)

  • Zhipeng Zhao

    (Institute of Hydropower System & Hydroinformatics, Dalian University of Technology, Dalian 116024, China)

Abstract

The integration of large-scale wind and solar power into the power grid brings new challenges to the security and stability of power systems because of the uncertainty and intermittence of wind and solar power. This sensitive expected output has real implications for short-term hydro scheduling (STHS), which provides reserve services to alleviate electrical perturbations from wind and solar power. This paper places an emphasis on the sensitive expected output characteristics of hydro plants and their effect on reserve services. The multi-step progressive optimality algorithm (MSPOA) is used for the STHS problem. An iterative approximation method is proposed to determine the forebay level and output under the condition of the sensitive expected output. Cascaded hydro plants in the Wujiang River are selected as an example. The results illustrate that the method can achieve good performance for peak shaving and reserve services. The proposed approach is both accurate and computationally acceptable so that the obtained hydropower schedules are in accordance with practical circumstances and the reserve can cope with renewable power fluctuations effectively.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:10:p:2477-:d:358030
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    References listed on IDEAS

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    1. Sedghi, Mahdi & Ahmadian, Ali & Aliakbar-Golkar, Masoud, 2016. "Assessment of optimization algorithms capability in distribution network planning: Review, comparison and modification techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 415-434.
    2. Yong-Gi Park & Jong-Bae Park & Namsu Kim & Kwang Y. Lee, 2017. "Linear Formulation for Short-Term Operational Scheduling of Energy Storage Systems in Power Grids," Energies, MDPI, vol. 10(2), pages 1-16, February.
    3. Hamid Bashiri-Atrabi & Kourosh Qaderi & David Rheinheimer & Erfaneh Sharifi, 2015. "Application of Harmony Search Algorithm to Reservoir Operation Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(15), pages 5729-5748, December.
    4. 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.
    5. Wang, Xianxun & Mei, Yadong & Kong, Yanjun & Lin, Yuru & Wang, Hao, 2017. "Improved multi-objective model and analysis of the coordinated operation of a hydro-wind-photovoltaic system," Energy, Elsevier, vol. 134(C), pages 813-839.
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