Optimization of Multiple Reservoirs Operation with Consideration to Sediment Evacuation

Rashid, Muhammad Usman; Shakir, Abdul Sattar; Khan, Noor Muhammad; Latif, Abid; Qureshi, Muhammad Mubashir

doi:10.1007/s11269-015-0951-9

Cited by 21 publications

(9 citation statements)

References 25 publications

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“…Evolutionary computation approaches, such as Genetic Algorithm (GA), overcome the limitations of conventional optimization techniques in reservoir system analysis, and deal with nonlinear, discontinuous, non-convex and multi-functions [37]. GA has been successfully applied worldwide for reservoir optimization [38]. GA has been found to be superior among other conventional methods in that it can get global or near global optimal solutions because of its search concept of population of solutions [39].…”

Section: Introductionmentioning

confidence: 99%

Optimal Operation of the Eastern Nile System Using Genetic Algorithm, and Benefits Distribution of Water Resources Development

Digna

Castro-Gama

Zaag

et al. 2018

Water

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The Eastern Nile Basin is facing a number of transboundary issues, including water resources development, and the associated impacts. The Nile Basin, particularly the Eastern Nile Sub-basin, is considered as one of a few international river systems of potential conflicts between riparian countries. The Eastern Nile is characterized by the high dependency of downstream countries on river water generated in upstream countries, with limited or no contribution to the runoff itself. The aim of this paper is to analyze optimal scenarios for water resources management in the Eastern Nile with regard to hydropower generation and irrigation development. A hydro-economic optimization model based on Genetic Algorithm has been used to determine the maximum benefits for two scenarios: (i) non-cooperative management of hydraulic infrastructure by the riparian countries (status quo), and (ii) cooperative water resources management among the riparian countries. The hydro-economic model is developed using a Genetic Algorithm and deterministic optimization approach covering all hydraulic infrastructures in the Eastern Nile, existing and planned, including the Grand Ethiopian Renaissance Dam (GERD). The results show that cooperative management yields an increase in hydro-energy returns for all countries compared to the status quo, with a very high increase in Ethiopian’s returns, as expected. Non-cooperative system management would negatively impact the hydro-energy of Egypt compared to the cooperative management (reduced by 11%), without a significant increase of hydro-energy for Ethiopia. For Sudan, the results show that hydropower generation benefits from the presence of GERD, in both management scenarios. Non-cooperative management of the system, along with the internal trade-off between irrigation and hydropower facilities, would negatively impact irrigation supply in Sudan. The findings support the argument of positive impact of GERD development on the three Eastern Nile riparian countries, Ethiopia, Sudan and Egypt, provided that the three countries agree to manage the system cooperatively.

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Section: Introductionmentioning

confidence: 99%

Optimal Operation of the Eastern Nile System Using Genetic Algorithm, and Benefits Distribution of Water Resources Development

Digna

Castro-Gama

Zaag

et al. 2018

Water

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“…The relation between reservoir operations and sedimentation processes along the river and/or within the reservoir was investigated by many researchers (i.e. Carriaga and Mays (1995a) ; Nicklow and Mays (2000); Bringer and Nicklow (2001); Rashid et al (2015); Bai et al, 2015). Carriaga and Mays (1995b) developed a mathematical model to determine the optimum single reservoir releases that minimize sediment scour and deposition in downstream river reaches.…”

Section: Reservoir Sedimentation Analysis Modelsmentioning

confidence: 99%

“…They used GA for rule curves optimization and simulation model for sediment evacuation modelling. An optimization-simulation with sediment evacuation model was also developed by Rashid et al (2015) using GA optimization technique and Tsinghua equation to optimize the operation of multi-objectives multiple reservors system on Indus River in Pakistan.…”

Section: Reservoir Sedimentation Analysis Modelsmentioning

confidence: 99%

Optimizing the Operation of a Multiple Reservoir System in the Eastern Nile Basin Considering Water and Sediment Fluxes

Digna¹

2021

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“…They concluded that with the same number of functional evaluations, the improved HBMO enhanced results by more than 8%. Furthermore, Khan and Tingsanchali (2009), Fowe et al (2015), and Rashid et al (2015) extracted rule curves with the RCGA. They concluded that the obtained rule curve improved the efficiency of the reservoir operation.…”

Section: The Constrained Genetic Algorithmmentioning

confidence: 99%

Application of non-animal–inspired evolutionary algorithms to reservoir operation: an overview

Jahandideh-Tehrani

Bozorg‐Haddad

Loáiciga

2019

Environ Monit Assess

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Evolutionary algorithms (EAs) have been widely used to search for optimal strategies for the planning and management of water resources systems, particularly reservoir operation. This study provides a comprehensive diagnostic assessment of state of the art of the non-animal-inspired EA applications to reservoir optimization. This type of EAs does not mimic biologic traits and group strategies of animal (wild) species. A search of pertinent papers was applied to the journal citation reports (JCRs). A bibliometric survey identified 14 pertinent non-animal-inspired EAs, such as the genetic algorithm (GA), simulated annealing (SA), and differential evolution (DE) algorithms, most of which have a number of modified versions. The characteristics of non-animal-inspired EAs and their modified versions were discussed to identify the difference between EAs and how each EA was improved. Additionally, the type of application of non-animal-inspired EAs to different case studies was investigated, and comparisons were made between the performance of the applied EAs in the studied literature. The survey revealed that the GA is the most frequently applied algorithm, followed by the DE algorithm. Non-animal-inspired EAs are superior to the classical methods of reservoir optimization (e.g., the non-linear programming and dynamic programming) due to faster convergence, diverse solution space, and efficient objective function evaluation. Several non-animal-inspired EAs of recent vintage have been shown to outperform the classic GA, which was the first evolutionary algorithm applied to reservoir operation.

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Optimization of Multiple Reservoirs Operation with Consideration to Sediment Evacuation

Cited by 21 publications

References 25 publications

Optimal Operation of the Eastern Nile System Using Genetic Algorithm, and Benefits Distribution of Water Resources Development

Optimal Operation of the Eastern Nile System Using Genetic Algorithm, and Benefits Distribution of Water Resources Development

Optimizing the Operation of a Multiple Reservoir System in the Eastern Nile Basin Considering Water and Sediment Fluxes

Application of non-animal–inspired evolutionary algorithms to reservoir operation: an overview

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