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Article

An Ecology-Oriented Single–Multi-Objective Optimal Operation Modeling and Decision-Making Method in the Case of the Ganjiang River

1
School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
2
Hubei Key Laboratory of Digital River Basin Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China
3
Institute of Water Resources and Hydropower, Huazhong University of Science and Technology, Wuhan 430074, China
*
Author to whom correspondence should be addressed.
Water 2024, 16(7), 970; https://doi.org/10.3390/w16070970
Submission received: 26 February 2024 / Revised: 22 March 2024 / Accepted: 23 March 2024 / Published: 27 March 2024
(This article belongs to the Section Hydrology)

Abstract

Hydro power has provided significant economic benefits to society due to its cleanliness and convenience. As the number of hydropower stations has increased, many serious ecological issues have also emerged. This study uses Wan’an Reservoir as its research object and investigates single–multi-objective optimal operation and decision-making regarding reservoirs for ecology-oriented operation, to meet ecological water demand and seek the optimal operation schemes for energy generation and ecological benefits. The full-process research is conducted based on the “objective-modeling constraint optimization scheme decision-making” framework. The Mann–Kendall test and ordered clustering method were used to diagnose the hydrological variation in the basin. Based on this, a hierarchical and phased ecological flow process was derived. The objectives were defined according to the flow process, and optimal operation models were constructed. The differential evolution algorithm (DE) and improved non-dominated sorting genetic algorithm-II (NSGA-II) were used to solve the models. A non-fitting curve method was used to determine the approximate inflection point of the Pareto front curve, and the curve was fitted linearly according to the approximate inflection point to obtain the conversion formula between the objectives. Based on the coefficient of variation and Mahalanobis distance, a new multi-attribute decision-making method for reservoir operation, CV-ITOPSIS, was constructed by improving the traditional TOPSIS. The results show that: (1) There is a piecewise linear contradiction between energy generation and ecological objectives, and the contradiction intensifies with an increase in incoming water frequency. (2) Before the approximate inflection point, the head significantly influences the conversion rate from the energy generation to ecology, while the discharge flow is the major influencing factor after the inflection point. The inflection point and the formula for the piecewise straight line can reveal the conversion law between the two objectives. (3) CV-ITOPSIS considers the degree of differentiation of index data and fully considers the correlation between indicators while retaining the good evaluation performance of the traditional method. It recommends the optimal benefit scheme for a multi-objective non-inferior solution set. The research results provide a theoretical foundation and decision support for the optimal ecological operation of the Ganjiang River Basin.
Keywords: reservoir optimal operation; multi-objective optimization; conversion law; multi-attribute decision-making; TOPSIS; ecological flow reservoir optimal operation; multi-objective optimization; conversion law; multi-attribute decision-making; TOPSIS; ecological flow

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MDPI and ACS Style

Liu, Z.; Mo, L.; Lou, S.; Zhu, Y.; Liu, T. An Ecology-Oriented Single–Multi-Objective Optimal Operation Modeling and Decision-Making Method in the Case of the Ganjiang River. Water 2024, 16, 970. https://doi.org/10.3390/w16070970

AMA Style

Liu Z, Mo L, Lou S, Zhu Y, Liu T. An Ecology-Oriented Single–Multi-Objective Optimal Operation Modeling and Decision-Making Method in the Case of the Ganjiang River. Water. 2024; 16(7):970. https://doi.org/10.3390/w16070970

Chicago/Turabian Style

Liu, Zixuan, Li Mo, Sijing Lou, Yuxin Zhu, and Tong Liu. 2024. "An Ecology-Oriented Single–Multi-Objective Optimal Operation Modeling and Decision-Making Method in the Case of the Ganjiang River" Water 16, no. 7: 970. https://doi.org/10.3390/w16070970

APA Style

Liu, Z., Mo, L., Lou, S., Zhu, Y., & Liu, T. (2024). An Ecology-Oriented Single–Multi-Objective Optimal Operation Modeling and Decision-Making Method in the Case of the Ganjiang River. Water, 16(7), 970. https://doi.org/10.3390/w16070970

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