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The Cascade Reservoirs Multi-Objective Ecological Operation Optimization Considering Different Ecological Flow Demand

Author

Listed:
  • Zhe Yang

    (Hohai University)

  • Kan Yang

    (Hohai University)

  • Hu Hu

    (Hohai University)

  • Lyuwen Su

    (Hohai University)

Abstract

In order to coordinate the power generation and downstream ecological protection benefits,the optimal ecological scheduling of cascade reservoirs is pivotal. In current paper, an improved chaotic normal cloud shuffling frog leaping algorithm (CNSFLA) based on chaotic initialization, cloud model evolution strategy and heuristic frog activation mechanism is proposed to overcome defects of conventional SFLA. Moreover, the multi-objective ecological scheduling model for Qingjiang cascade reservoirs is established with consideration of basic, suitable and ideal ecological flow requirements in Geheyan and Gaobazhou control sections. Afterwards, the model established is applied to cascade reservoirs ecological scheduling in Qingjiang. The water level corridor and penalty function are used to handle constraints. The scheduling results for long series indicate that benefits of power generation and basic ecology flow requirement in downstream control sections are fulfilled completely. While for suitable and ideal ecology flow requirements, 98.33%, 99.17 and 86.33%, 88.17% guarantee rate corresponding to Geheyan and Gaobazhou control sections can be achieved during whole scheduling periods. In terms of typical dry year, the less inflow makes it hard to reach the ideal ecology flow requirement in control sections during several periods even though the scheduling by CNSFLA. The guarantee rates and mean monthly ecological flow shortage are 66.67%, 66.67% and 71, 36 m3/s, respectively. Finally, performance analysis of CNSFLA verifies its effective search ability with high quality & stability results. The cascade power generation obtained by CNSFLA in long series scheduling is 75.45(108 kW·h), corresponding guarantee rates of ideal ecological flow requirement are 86.33 and 88.17%.

Suggested Citation

  • Zhe Yang & Kan Yang & Hu Hu & Lyuwen Su, 2019. "The Cascade Reservoirs Multi-Objective Ecological Operation Optimization Considering Different Ecological Flow Demand," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(1), pages 207-228, January.
    • Handle: RePEc:spr:waterr:v:33:y:2019:i:1:d:10.1007_s11269-018-2097-z
    DOI: 10.1007/s11269-018-2097-z
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    References listed on IDEAS

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    1. Mojtaba Moravej & Seyed-Mohammad Hosseini-Moghari, 2016. "Large Scale Reservoirs System Operation Optimization: the Interior Search Algorithm (ISA) Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(10), pages 3389-3407, August.
    2. Ping Sun & Zhi-qiang Jiang & Ting-ting Wang & Yan-ke Zhang, 2016. "Research and Application of Parallel Normal Cloud Mutation Shuffled Frog Leaping Algorithm in Cascade Reservoirs Optimal Operation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(3), pages 1019-1035, February.
    3. Seyed-Mohammad Hosseini-Moghari & Reza Morovati & Mohammad Moghadas & Shahab Araghinejad, 2015. "Optimum Operation of Reservoir Using Two Evolutionary Algorithms: Imperialist Competitive Algorithm (ICA) and Cuckoo Optimization Algorithm (COA)," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(10), pages 3749-3769, August.
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    1. Yang, Zhe & Yang, Kan & Wang, Yufeng & Su, Lyuwen & Hu, Hu, 2021. "Long-term multi-objective power generation operation for cascade reservoirs and risk decision making under stochastic uncertainties," Renewable Energy, Elsevier, vol. 164(C), pages 313-330.
    2. Cong-Min Liu & Jun Qiu & Fang-Fang Li, 2019. "Recovery Degree of the Natural Flow Regimes and the Corresponding Economic Costs for Reservoir Operation in Fish Spawning Seasons," IJERPH, MDPI, vol. 16(10), pages 1-15, May.
    3. Yang, Zhe & Wang, Yufeng & Yang, Kan, 2022. "The stochastic short-term hydropower generation scheduling considering uncertainty in load output forecasts," Energy, Elsevier, vol. 241(C).

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