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Multi-Objective Reservoir Optimization Balancing Energy Generation and Firm Power

Author

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  • Fang-Fang Li

    (College of Water Resources & Civil Engineering, China Agricultural University, Beijing 100083, China)

  • Jun Qiu

    (Institute for Aero-Engine, School of Aerospace Engineering, Tsinghua University, Beijing 100084, China)

Abstract

To maximize annual power generation and to improve firm power are important but competing goals for hydropower stations. The firm power output is decisive for the installed capacity in design, and represents the reliability of the power generation when the power plant is put into operation. To improve the firm power, the whole generation process needs to be as stable as possible, while the maximization of power generation requires a rapid rise of the water level at the beginning of the storage period. Taking the minimal power output as the firm power, both the total amount and the reliability of the hydropower generation are considered simultaneously in this study. A multi-objective model to improve the comprehensive benefits of hydropower stations are established, which is optimized by Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The Three Gorges Cascade Hydropower System (TGCHS) is taken as the study case, and the Pareto Fronts in different search spaces are obtained. The results not only prove the effectiveness of the proposed method, but also provide operational references for the TGCHS, indicating that there is room of improvement for both the annual power generation and the firm power.

Suggested Citation

  • Fang-Fang Li & Jun Qiu, 2015. "Multi-Objective Reservoir Optimization Balancing Energy Generation and Firm Power," Energies, MDPI, vol. 8(7), pages 1-15, July.
    • Handle: RePEc:gam:jeners:v:8:y:2015:i:7:p:6962-6976:d:52367
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    References listed on IDEAS

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    2. Amir Hatamkhani & Mojtaba Shourian & Ali Moridi, 2021. "Optimal Design and Operation of a Hydropower Reservoir Plant Using a WEAP-Based Simulation–Optimization Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(5), pages 1637-1652, March.
    3. J. Yazdi & A. Moridi, 2018. "Multi-Objective Differential Evolution for Design of Cascade Hydropower Reservoir Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(14), pages 4779-4791, November.
    4. Yury Sekretarev & Tatyana Myateg & Aminjon Gulakhmadov & Murodbek Safaraliev & Sergey Mitrofanov & Natalya Zubova & Olga Atamanova & Xi Chen, 2022. "Models of Optimal Operating Modes of the Water-Economic Complex on the Basis of Hydro Resource Price Evaluation," Mathematics, MDPI, vol. 10(5), pages 1-30, February.
    5. Hatamkhani, Amir & Moridi, Ali & Yazdi, Jafar, 2020. "A simulation – Optimization models for multi-reservoir hydropower systems design at watershed scale," Renewable Energy, Elsevier, vol. 149(C), pages 253-263.
    6. Jianjian Shen & Xiufei Zhang & Jian Wang & Rui Cao & Sen Wang & Jun Zhang, 2019. "Optimal Operation of Interprovincial Hydropower System Including Xiluodu and Local Plants in Multiple Recipient Regions," Energies, MDPI, vol. 12(1), pages 1-19, January.
    7. Shuai Liu & Zhong-Kai Feng & Wen-Jing Niu & Hai-Rong Zhang & Zhen-Guo Song, 2019. "Peak Operation Problem Solving for Hydropower Reservoirs by Elite-Guide Sine Cosine Algorithm with Gaussian Local Search and Random Mutation," Energies, MDPI, vol. 12(11), pages 1-24, June.
    8. Ahmad, Shahryar Khalique & Hossain, Faisal, 2020. "Maximizing energy production from hydropower dams using short-term weather forecasts," Renewable Energy, Elsevier, vol. 146(C), pages 1560-1577.

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