Control models for hydroelectric energy optimization

Georgakakos, Aris P.; Yao, Haiyuan; Yu, Yan

doi:10.1029/97wr01714

Cited by 18 publications

(11 citation statements)

References 2 publications

(3 reference statements)

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“…Depending on power system requirements, this decision level should consider dependable capacity commitments (hours during which the plant is committed to operate at capacity), minimum flow requirements, and energy prices as a function of power demand. Two common management objectives are to maximize the value of daily energy (Georgakakos et al, 1997c) or to maximize the daily energy itself (Georgakakos et al, 1997b) subject to all relevant operational requirements. The present study uses the second objective due to the unavailability of the…”

Section: Short-range Decision Modelmentioning

confidence: 99%

Assessment of Folsom Lake response to historical and potential future climate scenarios

Yao¹,

Georgakakos²

2000

Open-File Report

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116

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An integrated forecast-decision system for Folsom Lake (California) is developed and used to assess the sensitivity of reservoir performance to various forecast-management schemes under historical and future climate scenarios. The assessments are based on various combinations of inflow forecasting models, decision rules, and climate scenarios and demonstrate that (1) reliable inflow forecasts and adaptive decision systems can substantially benefit reservoir performance and (2) dynamic operational procedures represent effective climate change coping strategies.

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Section: Short-range Decision Modelmentioning

confidence: 99%

Assessment of Folsom Lake response to historical and potential future climate scenarios

Yao¹,

Georgakakos²

2000

Open-File Report

Self Cite

116

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“…During this specific period, must-run constraints are automatically satisfied or can be relaxed because priority for water use would be given to the power sector. This explains why we have neglected their representation in problems (1) or (2).…”

Section: Critical Periodmentioning

confidence: 92%

“…The allocations for a case with only two plants are then (4) where , are the dual variables associated to maximum storage and turbining limits for the two plants in model (2).…”

Section: B Allocation By Marginal Benefits (Mb)mentioning

confidence: 99%

“…]. Problem (2), which will be used in the following developments, is a large-scale LP optimization problem that can be solved by available commercial solvers.…”

Section: B Problem Formulation-a Set Of Hydro Plantsmentioning

confidence: 99%

“…This introduced the concept of the calculation of the FE for the entire hydro system, where the operation of several plants (fill-up, depletion, turbined outflow) is centrally coordinated by a system operator in order to maximize the total energy that can be continuously produced [2]- [4].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Allocation of Firm-Energy Rights Among Hydro Plants: An Aumann–Shapley Approach

Faria

Barroso²,

Kelman³

et al. 2009

IEEE Trans. Power Syst.

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The firm energy of generation plants is a critical component in some electricity markets. It is usually calculated by the regulator and sets a cap to the amount a plant can trade in capacity markets (or auctions), in order to avoid free-riding behaviors. Firm energy is a systemic property and, in case of hydro plants, a synergy is observed whenever a cooperative operation occurs, i.e., the firm energy of a system is greater than the sum of the individual plants. This immediately raises the question of how to divide the system's firm energy among the individual hydro plants. The objective of this work is to investigate the application of different allocation methods of firm energy rights among hydro plants using a game-theoretic framework. It is shown that there is not an optimal and unique approach to make this allocation. The paper investigates the advantages and disadvantages of different methods, such as marginal allocation, average production during the critical period, incremental allocation, finally recommending the Aumann-Shapley as the allocation method. This method is tested for the Brazilian power system, which has around 100 hydro plants. The results obtained are compared with the current allocation adopted by the electricity regulatory agency of Brazil.

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Decision support systems for integrated water resources management with an application to the nile basin

Georgakakos

2007

Topics on System Analysis and Integrated Water Resources Management

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Control models for hydroelectric energy optimization

Cited by 18 publications

References 2 publications

Assessment of Folsom Lake response to historical and potential future climate scenarios

Assessment of Folsom Lake response to historical and potential future climate scenarios

Allocation of Firm-Energy Rights Among Hydro Plants: An Aumann–Shapley Approach

Decision support systems for integrated water resources management with an application to the nile basin

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