A Factorial-based Dynamic Analysis Method for Reservoir Operation Under Fuzzy-stochastic Uncertainties

Fu, Dianzheng; Li, Y. P.; Huang, Guohe

doi:10.1007/s11269-013-0429-6

Cited by 18 publications

(6 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…If the total reservoir release water cannot be met, chance-constraint programming can be applied to obtain the expected net benefits [22]. Nevertheless, in the progress of RO, alternations were made by decision makers with different goals; probabilities of different inflow levels could not exactly reflect randomness of inflows alone [23]. Thus, the probabilities may own the fuzzy information based on the decision maker's judgment, leading to fuzzy stochastic characteristic.…”

Section: Introductionmentioning

confidence: 99%

Monthly Optimal Reservoirs Operation for Multicrop Deficit Irrigation under Fuzzy Stochastic Uncertainties

Zhang

Guo

Fang

et al. 2014

Journal of Applied Mathematics

View full text Add to dashboard Cite

An uncertain monthly reservoirs operation and multicrop deficit irrigation model was proposed under conjunctive use of underground and surface water for water resources optimization management. The objective is to maximize the total crop yield of the entire irrigation districts. Meanwhile, ecological water remained for the downstream demand. Because of the shortage of water resources, the monthly crop water production function was adopted for multiperiod deficit irrigation management. The model reflects the characteristics of water resources repetitive transformation in typical inland rivers irrigation system. The model was used as an example for water resources optimization management in Shiyang River Basin, China. Uncertainties in reservoir management shown as fuzzy probability were treated through chance-constraint parameter for decision makers. Necessity of dominance(ND)was used to analyse the advantages of the method. The optimization results including reservoirs real-time operation policy, deficit irrigation management, and the available water resource allocation could be used to provide decision support for local irrigation management. Besides, the strategies obtained could help with the risk analysis of reservoirs operation stochastically.

show abstract

Section: Introductionmentioning

confidence: 99%

Monthly Optimal Reservoirs Operation for Multicrop Deficit Irrigation under Fuzzy Stochastic Uncertainties

Zhang

Guo

Fang

et al. 2014

Journal of Applied Mathematics

View full text Add to dashboard Cite

show abstract

“…With such a scenario-based approach, the resulting mathematical problem can become too large to be applied to large-scale real-world problems. The same problem has been mentioned among others in [12][13][14][15]. Moreover, the random variables (mainly the water inflows) are assumed to take on discrete distributions, such that the study can be solved through linear programming method.…”

Section: Limitations Of the Applied Methodology And Corresponding Chamentioning

confidence: 98%

“…Also in this case a scenario-based approach sets limitations when the study system is very large and complicated. In reference [14], a method is developed for tackling multiple uncertainties through integration of stochastic dynamic programming, fuzzy-Markov chain, vertex analysis and factorial analysis techniques. It may have, though, computational (among others) difficulties to handle many other uncertain parameters (such as interval or dual-probabilities) that exist in large-scale practical problems.…”

mentioning

confidence: 99%

Optimizing Water Allocation under Uncertain System Conditions for Water and Agriculture Future Scenarios in Alfeios River Basin (Greece)—Part B: Fuzzy-Boundary Intervals Combined with Multi-Stage Stochastic Programming Model

Bekri

Disse

Yannopoulos

2015

Water

View full text Add to dashboard Cite

Abstract:Optimal water allocation within a river basin still remains a great modeling challenge for engineers due to various hydrosystem complexities, parameter uncertainties and their interactions. Conventional deterministic optimization approaches have given their place to stochastic, fuzzy and interval-parameter programming approaches and their hybrid combinations for overcoming these difficulties. In many countries, including Mediterranean countries, water resources management is characterized by uncertain, imprecise and limited data because of the absence of permanent measuring systems, inefficient river monitoring and fragmentation of authority responsibilities. A fuzzy-boundary-interval linear programming methodology developed by Li et al. (2010) is selected and applied in the Alfeios river basin (Greece) for optimal water allocation under uncertain system conditions. This methodology combines an ordinary multi-stage stochastic programming with uncertainties expressed as fuzzy-boundary intervals. Upper-and lower-bound solution intervals for optimized water allocation targets and probabilistic water allocations and shortages are estimated under a baseline scenario and four water and agricultural policy future scenarios for an optimistic and a pessimistic attitude of the decision makers. In this OPEN ACCESSWater 2015, 7 6428 work, the uncertainty of the random water inflows is incorporated through the simultaneous generation of stochastic equal-probability hydrologic scenarios at various inflow positions instead of using a scenario-tree approach in the original methodology.

show abstract

“…The main objective of the optimization model is to meet the demand and minimize the total pumping cost for monthly operation considering the uncertainty in reservoir inflow under climate change. Firstorder Markov chain is most commonly used to handle uncertainty in reservoir operation (Fu et al, 2013;Liu et al, 2014). However, in the present study, an alternative approach based on future climate input was employed to handle uncertainty in reservoir inflow.…”

Section: Methodsmentioning

confidence: 99%

Development of an optimal reservoir pumping operation for adaptation to climate change

et al. 2016

View full text Add to dashboard Cite

Optimization of operation rule curve of Layang reservoir located in southern part of peninsular Malaysia under climate change uncertainties has been presented in this study. Downscaled climate data were incorporated in a lumped rainfall-runoff model to project daily reservoir inflow, which was then used to determine the reservoir operation rule curves to minimize the operation cost. The results reveal that climatic change will cause a rise of temperature in the range of 1.5-2.9 o C, but decrease in rainfall in most of the months in the end of this century which will casue a change in the seasonal pattern of inflow to reservoir. Comparison of historical and model generated operation costs indicates that annual savings of 23% and 33% is possible with optimized reservoir operation rule curves. Assessment of the performance of the optimized operation curve under climate change scenarios shows that it will be able to cope with the changing pattern of reservoir inflow with proper adjustment. It is expected that the method presented in this paper to derive pumping operation curves to optimize the total volume of water to be pumped from various sources to reservoir can be useful for reservoir operators in the context of climate change.

show abstract

A Factorial-based Dynamic Analysis Method for Reservoir Operation Under Fuzzy-stochastic Uncertainties

Cited by 18 publications

References 41 publications

Monthly Optimal Reservoirs Operation for Multicrop Deficit Irrigation under Fuzzy Stochastic Uncertainties

Monthly Optimal Reservoirs Operation for Multicrop Deficit Irrigation under Fuzzy Stochastic Uncertainties

Optimizing Water Allocation under Uncertain System Conditions for Water and Agriculture Future Scenarios in Alfeios River Basin (Greece)—Part B: Fuzzy-Boundary Intervals Combined with Multi-Stage Stochastic Programming Model

Development of an optimal reservoir pumping operation for adaptation to climate change

Contact Info

Product

Resources

About