Environmental impacts of increased hydroelectric development at existing dams

Railsback, Steven F.; Cada, G.F.; Petrich, Carl H.; Salé, Michael J.; Shaakir-Ali, J. A.; Watts, J.A.; Webb, J.W.

doi:10.2172/1218134

Cited by 3 publications

(5 citation statements)

References 12 publications

(17 reference statements)

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“…Understanding relationships between hydropower plant operations and ecosystem quality (Truffer et al 2003) and water quantity along with quality optimization are essential for changes in reservoir operating rules (Chaves et al 2004). Mitigation costs associated with water quality deterioration are reflected in diminished profits and reduced energy production (Railsback et al 1991). Pre-treatment or control of reservoir inflows; in-pool management or treatment techniques; management of reservoir outflows by controlling the outflow rate, outlet location, timing of releases, turbine operating schedule and treating the release, are some of the remedial activities that improve water quality.…”

Section: Reservoir Operation and Water Qualitymentioning

confidence: 99%

“…Pre-treatment or control of reservoir inflows; in-pool management or treatment techniques; management of reservoir outflows by controlling the outflow rate, outlet location, timing of releases, turbine operating schedule and treating the release, are some of the remedial activities that improve water quality. The last option is a common method of improving reservoir in-pool and released water quality (Railsback et al 1991, Shirangi et al 2008. Other strategies are control of reservoir releases, pollutant concentrations in reservoir releases and tributary inflows and increase the in-stream degradation rate of pollutants (Dhar and Datta 2008).…”

Section: Reservoir Operation and Water Qualitymentioning

confidence: 99%

“…Reservoir operations may alter or create an entirely new ecosystem (Dasic and Djordjevic 2002) in the impoundment, change flow regimes (Margeta and Fontane 1989), disrupt flow patterns of the river and negatively impact habitats and species downstream (Railsback et al 1991, Castelletti et al 2008. Operation of hydropower reservoirs need to incorporate all aspects related to water quality (Sechi andSulis 2007, Dhar andDatta 2008) and downstream water quality targets that need to be met should be incorporated in the optimization formulations.…”

Section: Water Quality Simulation Modelmentioning

confidence: 99%

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Partial constraint satisfaction approaches for optimal operation of a hydropower system

Ferreira¹,

Teegavarapu²

2012

Engineering Optimization

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Optimal operation models for a hydropower system using partial constraint satisfaction (PCS) approaches are proposed and developed in this study. The models use mixed integer nonlinear programming (MINLP) formulations with binary variables. The models also integrate a turbine unit commitment formulation along with water quality constraints used for evaluation of reservoir downstream water quality impairment. New PCS-based models for hydropower optimization formulations are developed using binary and continuous evaluator functions to maximize the constraint satisfaction. The models are applied to a reallife hydropower reservoir system in Brazil. Genetic Algorithms (GAs) are used to solve the optimization formulations. Decision maker's preferences towards power production targets and water quality improvements are incorporated using partial satisfaction constraints to obtain compromise operating rules for a multi-objective reservoir operation problem dominated by conflicting goals of energy production, water quality and consumptive water uses.

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Section: Reservoir Operation and Water Qualitymentioning

confidence: 99%

Section: Reservoir Operation and Water Qualitymentioning

confidence: 99%

Section: Water Quality Simulation Modelmentioning

confidence: 99%

See 1 more Smart Citation

Partial constraint satisfaction approaches for optimal operation of a hydropower system

Ferreira¹,

Teegavarapu²

2012

Engineering Optimization

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“…Water quantity and quality can be considered the main driving forces of reservoir operation, being such factors intrinsically related, as when water quality becomes an issue, its mitigation usually involves costs, such as reduced profits to developers and reduced energy production (Railsback et al 1991;Chaves et al 2004;Teegavarapu and Simonovic 2000;Teegavarapu and Simonovic, 2003). Even though there are a variety of techniques to improve water quality in water resources systems, most of them are very expensive (Shirangi et al 2008).…”

Section: Hydropower Optimization and Water Qualitymentioning

confidence: 99%

Optimal and Adaptive Operation of a Hydropower System with Unit Commitment and Water Quality Constraints

Ferreira

Teegavarapu

2011

Water Resour Manage

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Management of water resources has become more complex in recent years as a result of changing attitudes towards sustainability and the attribution of greater attention to environmental issues, especially under a scenario of water scarcity risk introduced by climate changes and anthropogenic pressures. This study addresses the optimal short-term operation of a multi-purpose hydropower system under an environment where objectives are conflicting. New optimization models using mixed integer nonlinear programming (MINLP) with binary variables adopted for incorporating unit commitment constraints and adaptive real-time operations are developed and applied to a real life hydropower reservoir in Brazil, utilizing evolutionary algorithms. These formulations address water quality concerns downstream of the reservoir and optimal operations for power generation in an integrated manner and deal with uncertain future flows due to climate change. Results obtained using genetic algorithm (GA) solvers were superior to gradient based methods, converging to superior optimal solutions especially due to computational intractability problems associated with combinatorial domain of integer variables in the unit commitment formulation. The adaptive operation formulation in conjunction with the solution of turbine unit commitment problem yielded more reliable solutions, reducing forecasting uncertainty and providing more flexible operational rules.

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“…[]. Reservoir operations may alter or create entirely new ecosystems in the impoundments, change flow regimes [ Margeta and Fontane , ], disrupt flow patterns of the river and negatively impact habitats and species downstream [ Railsback et al ., ]. It is essential for operation of hydropower reservoirs to incorporate all aspects related to water quality [ Sechi and Sulis , ] and downstream water quality targets that need to be met in the optimization formulations.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy multiobjective models for optimal operation of a hydropower system

Teegavarapu

Ferreira²,

Simonović́

2013

Water Resour. Res.

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[1] Optimal operation models for a hydropower system using new fuzzy multiobjective mathematical programming models are developed and evaluated in this study. The models use (i) mixed integer nonlinear programming (MINLP) with binary variables and (ii) integrate a new turbine unit commitment formulation along with water quality constraints used for evaluation of reservoir downstream impairment. Reardon method used in solution of genetic algorithm optimization problems forms the basis for development of a new fuzzy multiobjective hydropower system optimization model with creation of Reardon type fuzzy membership functions. The models are applied to a real-life hydropower reservoir system in Brazil. Genetic Algorithms (GAs) are used to (i) solve the optimization formulations to avoid computational intractability and combinatorial problems associated with binary variables in unit commitment, (ii) efficiently address Reardon method formulations, and (iii) deal with local optimal solutions obtained from the use of traditional gradient-based solvers. Decision maker's preferences are incorporated within fuzzy mathematical programming formulations to obtain compromise operating rules for a multiobjective reservoir operation problem dominated by conflicting goals of energy production, water quality and conservation releases. Results provide insight into compromise operation rules obtained using the new Reardon fuzzy multiobjective optimization framework and confirm its applicability to a variety of multiobjective water resources problems.Citation: Teegavarapu, R. S. V., A. R. Ferreira, and S. P. Simonovic (2013), Fuzzy multiobjective models for optimal operation of a hydropower system, Water Resour. Res., 49,[3180][3181][3182][3183][3184][3185][3186][3187][3188][3189][3190][3191][3192][3193]

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Environmental impacts of increased hydroelectric development at existing dams

Cited by 3 publications

References 12 publications

Partial constraint satisfaction approaches for optimal operation of a hydropower system

Partial constraint satisfaction approaches for optimal operation of a hydropower system

Optimal and Adaptive Operation of a Hydropower System with Unit Commitment and Water Quality Constraints

Fuzzy multiobjective models for optimal operation of a hydropower system

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