Reservoir operations optimization via fuzzy criterion decision processes

Esogbue, Augustine O.; Liu, Baoding

doi:10.1007/s10700-006-0015-y

Cited by 8 publications

(5 citation statements)

References 22 publications

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“…Subsequent research basically used model results to support decision/policy-making, optimize the allocation of water resources, and efficiently collect and utilize water resources [8][9][10][11][12][13][14][15][16][17][18][19]. In terms of the large-scale multi-objective model and the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) method, most of the research is focused on water resource management [20][21][22][23][24][25][26][27][28][29][30][31][32][33][34]. Unfortunately, nearly all the risk decision analyses on water resource systems have primarily focused on flood control systems and reservoir operation [35].…”

Section: Introductionmentioning

confidence: 99%

Application of NSGA-II and Improved Risk Decision Method for Integrated Water Resources Management of Malian River Basin

Gao

Zhang²,

Zhang

et al. 2019

Water

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The Malian River Basin is the Longdong grain elevator and a new oil and energy base of East Gansu Province. Limited water resources programming utilization is a key for the development of the socio-economic and energy industry, as well as the improvement of the ecological environment. An analytical framework for assessing socioeconomic development, rational allocation of water resources, and guiding policy development is proposed in this study. A decision tree method was used in the risk analysis and was improved by introducing the expert advisory probabilistic method into the sensitivity analysis to reduce cognitive bias. A large-system multi-objective model was developed to solve the problem of the rational allocation of available water resources and for benefit maximization among water users. The Non-dominated Sorting Genetic Algorithm-Ⅱ (NSGA-II) method was used to generate a solution. The water supply amount within the basin was 8.69 × 108 m3 and the water shortage rate was 15.90%. The optimization model method had better distribution results than the weights method without new water supply. Through the model method results, the water saving potential was found and the related policies were proposed. The framework and methods can further provide a reference for both the planning of water resources and the formulation of regulatory policies and will greatly alleviate water crises in semi-arid areas.

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Section: Introductionmentioning

confidence: 99%

Application of NSGA-II and Improved Risk Decision Method for Integrated Water Resources Management of Malian River Basin

Gao

Zhang²,

Zhang

et al. 2019

Water

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“…When we talk about "those young students are tall", we should know the individual feature data of all students, for example, 185), (25,190), (26,184), (26,170), (27,187), (27,188) (28,160), (30,190), (32,185), (33,176), (35,185), (36,188) (38,164), (38,178), (39,182), (40,186), (42,165), (44,170)    (10.5) whose elements are ages and heights in years and centimeters, respectively. When we talk about "those young students are tall", we should know the individual feature data of all students, for example, 185), (25,190), (26,184), (26,170), (27,187), (27,188) ...…”

Section: Individual Feature Datamentioning

confidence: 99%

Uncertainty Theory

Liu

2015

Springer Uncertainty Research

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861

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“…Furthermore, several efforts were made to modify the performance of Fuzzy logic models by developing new algorithms, tools, and techniques. Esogbue & Liu [18] suggested a new tool of fuzzy criterion decision processes for the treatment of complex reservoir operation problems. Akbari et al [19] developed a new method to predict river flow using a fuzzy rule-based model with a modified algorithm which improves the performance of the model as new data becomes accessible.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Logic Model for Optimal Operation of Darbandikhan Reservoir, Iraq

Faris¹,

Ibrahim²,

Abdulrahman³

et al. 2021

IJDNE

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The operating system of a reservoir is a significant contributor to its success in water resources management. For a multi-purpose reservoir, an ideal operating system determines output characteristics that take account of all objectives. In this study, a new model to optimize Darbandikhan reservoir system operation in Iraq is proposed, based on a fuzzy logic controller. The aim of the new system is to maximize hydropower production while satisfying all downstream water demands. The proposal was tested on flow and other data in 324 monthly time steps, from January 1992 to December 2018, using a simulation model based on the Simulink technique of MATLAB software. Trial and error showed that membership functions of the Gaussian shape were most appropriate. For comparison purposes, Discrete Differential Dynamic Programming (DDDP), Nonlinear Programming (NLP) and Linear Programming (LP) optimization models were developed and applied to operate the reservoir. The results for turbine operation show that, relative to actual power produced, average monthly hydropower generation is increased by 32.2% (fuzzy logic), 51.4% (DDDP), 29.3% (NLP), 27.4% (LP). Although the dynamic programming method generated more hydropower, the fuzzy logic controller avoided complex optimization procedures, making it more flexible and more acceptable to operators. Moreover, the fuzzy approach provides an opportunity for reservoir operators to develop and apply more convenient operating rules, which in itself is a valuable alternative to conventional optimization techniques.

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Reservoir operations optimization via fuzzy criterion decision processes

Cited by 8 publications

References 22 publications

Application of NSGA-II and Improved Risk Decision Method for Integrated Water Resources Management of Malian River Basin

Application of NSGA-II and Improved Risk Decision Method for Integrated Water Resources Management of Malian River Basin

Uncertainty Theory

Fuzzy Logic Model for Optimal Operation of Darbandikhan Reservoir, Iraq

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