IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v35y2021i10d10.1007_s11269-021-02901-8.html
   My bibliography  Save this article

Time-varying Decision-making Method for Multi-objective Regulation of Water Resources

Author

Listed:
  • Zengchuan Dong

    (Hohai University)

  • Xiaokuan Ni

    (Hohai University)

  • Mufeng Chen

    (Hohai University)

  • Hongyi Yao

    (Hohai University)

  • Wenhao Jia

    (Hohai University)

  • Jiaxing Zhong

    (Hohai University)

  • Li Ren

    (Hohai University)

Abstract

A decision-making method for water resource regulation that considers the multi-objective time-varying competition relationship is proposed, given the dynamic time-varying characteristics of the mutual feedback relationship and its strength as the main targets in the water resources scheduling cycle. With a focus on different dispatching periods, a time-varying multi-objective model of annual generation, annual ecology, period ecology is constructed. Dynamic decision weights are built using a method that combines entropy weight and FAHP, and then selects the dynamic preference scheme from the frontier cluster by weighted TOPSIS based on the weights. In this study the lower reaches of the Jinsha River are used as an example. The spatiotemporal variation relationship of the multi-objective is analyzed, the entire year is divided into three operation periods, and the Pareto frontier cluster is solved with a time-varying process. The results show that power generation is competitive with ecology on an annual scale. However, the relationship varies slightly in each period, being weakly cooperative in the flood period, not significant in the storage period, and competitive in the routine period. The decision method of focusing on the key period, considering time-varying demands and dynamic preferences, can obtain better annual power generation and ecological protection benefits than the traditional unified annual regulation method, and can improve the degree of guarantee of ecological demand in key areas during critical periods. Focusing on ecological protection during the routine period can achieve the best balance between power generation and ecological protection.

Suggested Citation

  • Zengchuan Dong & Xiaokuan Ni & Mufeng Chen & Hongyi Yao & Wenhao Jia & Jiaxing Zhong & Li Ren, 2021. "Time-varying Decision-making Method for Multi-objective Regulation of Water Resources," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(10), pages 3411-3430, August.
    • Handle: RePEc:spr:waterr:v:35:y:2021:i:10:d:10.1007_s11269-021-02901-8
    DOI: 10.1007/s11269-021-02901-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11269-021-02901-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11269-021-02901-8?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Feng, Zhong-kai & Niu, Wen-jing & Cheng, Chun-tian, 2018. "Optimization of hydropower reservoirs operation balancing generation benefit and ecological requirement with parallel multi-objective genetic algorithm," Energy, Elsevier, vol. 153(C), pages 706-718.
    2. Mohammad Hadi Afshar & R. Hajiabadi, 2018. "A Novel Parallel Cellular Automata Algorithm for Multi-Objective Reservoir Operation Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(2), pages 785-803, January.
    3. Omar A. de la Cruz Courtois & Maritza Liliana Arganis Juárez & Delva Guichard Romero, 2021. "Simulated Optimal Operation Policies of a Reservoir System Obtained with Continuous Functions Using Synthetic Inflows," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(7), pages 2249-2263, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mina Khosravi & Abbas Afshar & Amir Molajou, 2022. "Decision Tree-Based Conditional Operation Rules for Optimal Conjunctive Use of Surface and Groundwater," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(6), pages 2013-2025, April.
    2. Zhang, Shuo & Kang, Yan & Gao, Xuan & Chen, Peiru & Cheng, Xiao & Song, Songbai & Li, Lingjie, 2023. "Optimal reservoir operation and risk analysis of agriculture water supply considering encounter uncertainty of precipitation in irrigation area and runoff from upstream," Agricultural Water Management, Elsevier, vol. 277(C).
    3. Zhenyu Mu & Xueshan Ai & Jie Ding & Kui Huang & Senlin Chen & Jiajun Guo & Zuo Dong, 2022. "Risk Analysis of Dynamic Water Level Setting of Reservoir in Flood Season Based on Multi-index," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(9), pages 3067-3086, July.
    4. Bin Liu & Feilian Zhang & Feng-jang Hwang, 2021. "Comfort Value of Water: Natural-artificial Dual-structured Analytical Framework for Comfort Assessment of Regional Water Environment and Landscape System," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(14), pages 4747-4768, November.

    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. Feng, Zhong-kai & Niu, Wen-jing & Wang, Wen-chuan & Zhou, Jian-zhong & Cheng, Chun-tian, 2019. "A mixed integer linear programming model for unit commitment of thermal plants with peak shaving operation aspect in regional power grid lack of flexible hydropower energy," Energy, Elsevier, vol. 175(C), pages 618-629.
    2. Dan Wang & Shuanghu Zhang & Guoli Wang & Yin Liu & Hao Wang & Jingjing Gu, 2022. "Reservoir Regulation for Ecological Protection and Remediation: A Case Study of the Irtysh River Basin, China," IJERPH, MDPI, vol. 19(18), pages 1-24, September.
    3. Hu Hu & Kan Yang & Lyuwen Su & Zhe Yang, 2019. "A Novel Adaptive Multi-Objective Particle Swarm Optimization Based on Decomposition and Dominance for Long-term Generation Scheduling of Cascade Hydropower System," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(11), pages 4007-4026, September.
    4. Ali Zarei & Sayed-Farhad Mousavi & Madjid Eshaghi Gordji & Hojat Karami, 2019. "Optimal Reservoir Operation Using Bat and Particle Swarm Algorithm and Game Theory Based on Optimal Water Allocation among Consumers," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(9), pages 3071-3093, July.
    5. Zhong, Ruida & Zhao, Tongtiegang & Chen, Xiaohong, 2021. "Evaluating the tradeoff between hydropower benefit and ecological interest under climate change: How will the water-energy-ecosystem nexus evolve in the upper Mekong basin?," Energy, Elsevier, vol. 237(C).
    6. Kuriqi, Alban & Pinheiro, António N. & Sordo-Ward, Alvaro & Garrote, Luis, 2019. "Flow regime aspects in determining environmental flows and maximising energy production at run-of-river hydropower plants," Applied Energy, Elsevier, vol. 256(C).
    7. Abdelhady, Hazem U. & Imam, Yehya E. & Shawwash, Ziad & Ghanem, Ashraf, 2021. "Parallelized Bi-level optimization model with continuous search domain for selection of run-of-river hydropower projects," Renewable Energy, Elsevier, vol. 167(C), pages 116-131.
    8. Wang, Xianxun & Virguez, Edgar & Xiao, Weihua & Mei, Yadong & Patiño-Echeverri, Dalia & Wang, Hao, 2019. "Clustering and dispatching hydro, wind, and photovoltaic power resources with multiobjective optimization of power generation fluctuations: A case study in southwestern China," Energy, Elsevier, vol. 189(C).
    9. M. A. Bonora & G. Capano & A. Rango & Mario Maiolo, 2022. "Novel Eulerian Approach with Cellular Automata Modelling to Estimate Water Quality in a Drinking Water Network," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(15), pages 5961-5976, December.
    10. Dai, Min & Yang, Han & Yang, Fusheng & Zhang, Zaoxiao & Yu, Yunsong & Liu, Guilian & Feng, Xiao, 2022. "Multi-strategy Ensemble Non-dominated sorting genetic Algorithm-II (MENSGA-II) and application in energy-enviro-economic multi-objective optimization of separation for isopropyl alcohol/diisopropyl et," Energy, Elsevier, vol. 254(PA).
    11. Hao, Ying & Dong, Lei & Liang, Jun & Liao, Xiaozhong & Wang, Lijie & Shi, Lefeng, 2020. "Power forecasting-based coordination dispatch of PV power generation and electric vehicles charging in microgrid," Renewable Energy, Elsevier, vol. 155(C), pages 1191-1210.
    12. 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.
    13. Dengiz, Thomas & Jochem, Patrick & Fichtner, Wolf, 2021. "Demand response through decentralized optimization in residential areas with wind and photovoltaics," Energy, Elsevier, vol. 223(C).
    14. Wang, Jinwen & Chen, Cheng & Liu, Shuangquan, 2018. "A new field-levelling procedure to minimize spillages in hydropower reservoir operation," Energy, Elsevier, vol. 160(C), pages 979-985.
    15. Hamid Reza Yavari & Amir Robati, 2021. "Developing Water Cycle Algorithm for Optimal Operation in Multi-reservoirs Hydrologic System," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(8), pages 2281-2303, June.
    16. Abolfazl Baniasadi Moghadam & Hossein Ebrahimi & Abbas Khashei Siuki & Abolfazl Akbarpour, 2022. "Reliability-based Operation of Reservoirs Using Combined Monte Carlo Simulation Model and a Novel Nature-inspired Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(12), pages 4447-4468, September.
    17. Feng, Zhong-kai & Niu, Wen-jing & Cheng, Chun-tian, 2018. "Optimal allocation of hydropower and hybrid electricity injected from inter-regional transmission lines among multiple receiving-end power grids in China," Energy, Elsevier, vol. 162(C), pages 444-452.
    18. Feng, Zhong-kai & Niu, Wen-jing & Cheng, Chun-tian, 2019. "China’s large-scale hydropower system: operation characteristics, modeling challenge and dimensionality reduction possibilities," Renewable Energy, Elsevier, vol. 136(C), pages 805-818.
    19. Yang, Tongxu & Zhang, Limei & Zhen, Linteng & Liu, Yongfu & Song, Qianqian & Tang, Wei, 2021. "Fast microgrids formation of distribution network with high penetration of DERs considering reliability," Energy, Elsevier, vol. 236(C).
    20. El-Sayed, Wael T. & El-Saadany, Ehab F. & Zeineldin, Hatem H. & Al-Sumaiti, Ameena S., 2020. "Fast initialization methods for the nonconvex economic dispatch problem," Energy, Elsevier, vol. 201(C).

    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:spr:waterr:v:35:y:2021:i:10:d:10.1007_s11269-021-02901-8. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.