IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i20p7779-d948658.html
   My bibliography  Save this article

Research on Operation Mode of the Yalong River Cascade Reservoirs Based on Improved Stochastic Fractal Search Algorithm

Author

Listed:
  • Ailing Xu

    (School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Li Mo

    (School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Qi Wang

    (China Three Gorges Corporation, Yichang 443133, China)

Abstract

With the completion of the Lianghekou Reservoir, with a multiyear regulation capacity, the operation relationship of the cascade reservoirs in the Yalong River is becoming increasingly complex. In order to study an optimal operation mode of the cascade reservoirs in the Yalong River under different inflow frequencies, based on the shortcomings of the existing single reservoir operation mode and the local joint operation mode of the cascade reservoirs, this paper first proposed a global joint operation mode for the cascade reservoirs to develop the power generation potential of daily regulating reservoirs and then gave a solution method for the cascade reservoirs’ operational model based on an improved stochastic fractal search (ISFS) algorithm. Finally, taking the maximum power generation as the goal and the inflow data of five typical years as the model inputs, this paper analyzed the differences in the power generation and water abandonment results of the cascade reservoirs in the middle and lower reaches of the Yalong River under the above three operation modes. The results show that (1) compared with the stochastic fractal search (SFS) algorithm and the particle swarm optimization (PSO) algorithm, the ISFS algorithm had faster convergence speed and higher precision; (2) the global joint operation mode had a more significant optimization effect in the year with more inflow, followed by the local joint operation mode, and the single reservoir operation mode had the worst; however, the difference in the results of the three operation modes gradually decreased as the inflows gradually decreased.

Suggested Citation

  • Ailing Xu & Li Mo & Qi Wang, 2022. "Research on Operation Mode of the Yalong River Cascade Reservoirs Based on Improved Stochastic Fractal Search Algorithm," Energies, MDPI, vol. 15(20), pages 1-19, October.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:20:p:7779-:d:948658
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/20/7779/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/15/20/7779/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yi Liu & Zhiqiang Jiang & Zhongkai Feng & Yuyun Chen & Hairong Zhang & Ping Chen, 2019. "Optimization of Energy Storage Operation Chart of Cascade Reservoirs with Multi-Year Regulating Reservoir," Energies, MDPI, vol. 12(20), pages 1-20, October.
    2. Changming Ji & Chuangang Li & Boquan Wang & Minghao Liu & Liping Wang, 2017. "Multi-Stage Dynamic Programming Method for Short-Term Cascade Reservoirs Optimal Operation with Flow Attenuation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(14), pages 4571-4586, November.
    3. 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.
    4. Suiling Wang & Zhiqiang Jiang & Yi Liu, 2022. "Dimensionality Reduction Method of Dynamic Programming under Hourly Scale and Its Application in Optimal Scheduling of Reservoir Flood Control," Energies, MDPI, vol. 15(3), pages 1-17, January.
    5. Zhiqiang Jiang & Peibing Song & Xiang Liao, 2020. "Optimization of Year-End Water Level of Multi-Year Regulating Reservoir in Cascade Hydropower System Considering the Inflow Frequency Difference," Energies, MDPI, vol. 13(20), pages 1-20, October.
    6. Xinyu Wu & Rui Guo & Xilong Cheng & Chuntian Cheng, 2021. "Combined Aggregated Sampling Stochastic Dynamic Programming and Simulation-Optimization to Derive Operation Rules for Large-Scale Hydropower System," Energies, MDPI, vol. 14(3), pages 1-15, January.
    7. Xuerong Li & Faliang Gui & Qingpeng Li, 2019. "Can Hydropower Still Be Considered a Clean Energy Source? Compelling Evidence from a Middle-Sized Hydropower Station in China," Sustainability, MDPI, vol. 11(16), pages 1-13, August.
    8. Shenglian Guo & Jionghong Chen & Yu Li & Pan Liu & Tianyuan Li, 2011. "Joint Operation of the Multi-Reservoir System of the Three Gorges and the Qingjiang Cascade Reservoirs," Energies, MDPI, vol. 4(7), pages 1-15, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Alireza Taheri Dehkordi & Mohammad Javad Valadan Zoej & Hani Ghasemi & Ebrahim Ghaderpour & Quazi K. Hassan, 2022. "A New Clustering Method to Generate Training Samples for Supervised Monitoring of Long-Term Water Surface Dynamics Using Landsat Data through Google Earth Engine," Sustainability, MDPI, vol. 14(13), pages 1-24, June.
    2. Yuxin Zhu & Jianzhong Zhou & Yongchuan Zhang & Zhiqiang Jiang & Benjun Jia & Wei Fang, 2022. "Optimal Energy Storage Operation Chart and Output Distribution of Cascade Reservoirs Based on Operating Rules Derivation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(14), pages 5751-5766, November.
    3. 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.
    4. Sakthivel, V.P. & Thirumal, K. & Sathya, P.D., 2022. "Short term scheduling of hydrothermal power systems with photovoltaic and pumped storage plants using quasi-oppositional turbulent water flow optimization," Renewable Energy, Elsevier, vol. 191(C), pages 459-492.
    5. Rongqi Zhang & Shanghong Zhang & Xiaoxiong Wen & Zhu Jing, 2023. "Refined Scheduling Based on Dynamic Capacity Model for Short-term Hydropower Generation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(1), pages 21-35, January.
    6. Tao Bai & Lianzhou Wu & Jian-xia Chang & Qiang Huang, 2015. "Multi-Objective Optimal Operation Model of Cascade Reservoirs and Its Application on Water and Sediment Regulation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(8), pages 2751-2770, June.
    7. Wang Zhang & Pan Liu & Xizhen Chen & Li Wang & Xueshan Ai & Maoyuan Feng & Dedi Liu & Yuanyuan Liu, 2016. "Optimal Operation of Multi-reservoir Systems Considering Time-lags of Flood Routing," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(2), pages 523-540, January.
    8. Houeida Hedfi & Ahlem Dakhlaoui & Abdessalem Abbassi, 2020. "Dynamic Behaviour of Hydro/Thermal Electrical Operators Under an Environmental Policy Targeting to Preserve Ecosystems Integrity and Air Quality," Working Papers halshs-02523330, HAL.
    9. Gejirifu De & Zhongfu Tan & Menglu Li & Liling Huang & Xueying Song, 2018. "Two-Stage Stochastic Optimization for the Strategic Bidding of a Generation Company Considering Wind Power Uncertainty," Energies, MDPI, vol. 11(12), pages 1-21, December.
    10. Li, Chaoshun & Wang, Wenxiao & Chen, Deshu, 2019. "Multi-objective complementary scheduling of hydro-thermal-RE power system via a multi-objective hybrid grey wolf optimizer," Energy, Elsevier, vol. 171(C), pages 241-255.
    11. Zida Song & Quan Liu & Zhigen Hu & Chunsheng Zhang & Jinming Ren & Zhexin Wang & Jianhai Tian, 2020. "Construction Diversion Risk Assessment for Hydropower Development on Sediment-Rich Rivers," Energies, MDPI, vol. 13(4), pages 1-20, February.
    12. Liping Li & Pan Liu & David Rheinheimer & Chao Deng & Yanlai Zhou, 2014. "Identifying Explicit Formulation of Operating Rules for Multi-Reservoir Systems Using Genetic Programming," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(6), pages 1545-1565, April.
    13. Xiong, Hualin & Egusquiza, Mònica & Alberg Østergaard, Poul & Pérez-Díaz, Juan I. & Sun, Guoxiu & Egusquiza, Eduard & Patelli, Edoardo & Xu, Beibei & Duan, Hongjiang & Chen, Diyi & Luo, Xingqi, 2021. "Multi-objective optimization of a hydro-wind-photovoltaic power complementary plant with a vibration avoidance strategy," Applied Energy, Elsevier, vol. 301(C).
    14. Perica Ilak & Slavko Krajcar & Ivan Rajšl & Marko Delimar, 2014. "Pricing Energy and Ancillary Services in a Day-Ahead Market for a Price-Taker Hydro Generating Company Using a Risk-Constrained Approach," Energies, MDPI, vol. 7(4), pages 1-26, April.
    15. Chen, Shuang & Hu, Minghui & Guo, Shanqi, 2023. "Fast dynamic-programming algorithm for solving global optimization problems of hybrid electric vehicles," Energy, Elsevier, vol. 273(C).
    16. Krešimir Fekete & Srete Nikolovski & Zvonimir Klaić & Ana Androjić, 2019. "Optimal Re-Dispatching of Cascaded Hydropower Plants Using Quadratic Programming and Chance-Constrained Programming," Energies, MDPI, vol. 12(9), pages 1-25, April.
    17. Xinyu Wu & Rui Guo & Xilong Cheng & Chuntian Cheng, 2021. "Combined Aggregated Sampling Stochastic Dynamic Programming and Simulation-Optimization to Derive Operation Rules for Large-Scale Hydropower System," Energies, MDPI, vol. 14(3), pages 1-15, January.
    18. Bin Xu & Ping-An Zhong & Xinyu Wan & Weiguo Zhang & Xuan Chen, 2012. "Dynamic Feasible Region Genetic Algorithm for Optimal Operation of a Multi-Reservoir System," Energies, MDPI, vol. 5(8), pages 1-17, August.
    19. Liping Wang & Minghao Liu & Boquan Wang & Jiajie Wu & Chuangang Li, 2017. "Study on Nested-Structured Load Shedding Method of Thermal Power Stations Based on Output Fluctuations," Energies, MDPI, vol. 10(10), pages 1-16, September.
    20. Zhiqiang Jiang & Peibing Song & Xiang Liao, 2020. "Optimization of Year-End Water Level of Multi-Year Regulating Reservoir in Cascade Hydropower System Considering the Inflow Frequency Difference," Energies, MDPI, vol. 13(20), pages 1-20, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:20:p:7779-:d:948658. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.