Stochastic Programming with a Joint Chance Constraint Model for Reservoir Refill Operation Considering Flood Risk

Xu, Bin; Boyce, S. E.; Zhang, Yu; Liu, Qiang; Le, Guo; Zhong, Ping‐an

doi:10.1061/(asce)wr.1943-5452.0000715

Cited by 40 publications

(16 citation statements)

References 33 publications

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“…Chance-constrained programming Eisel (1972), Houck (1979), Revelle, Joeres, and Kirby (1969), Sahinidis (2004), Sreekanth, Datta, and Mohapatra (2012), Xu et al (2017), Zeng, Wu, Cheng, and Wang (2013)…”

Section: Examples Of Applicationsmentioning

confidence: 99%

Inferring efficient operating rules in multireservoir water resource systems: A review

Macian-Sorribes

Pulido-Velázquez

2019

WIREs Water

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Coordinated and efficient operation of water resource systems becomes essential to deal with growing demands and uncertain resources in water‐stressed regions. System analysis models and tools help address the complexities of multireservoir systems when defining operating rules. This paper reviews the state of the art in developing operating rules for multireservoir water resource systems, focusing on efficient system operation. This review focuses on how optimal operating rules can be derived and represented. Advantages and drawbacks of each approach are discussed. Major approaches to derive optimal operating rules include direct optimization of reservoir operation, embedding conditional operating rules in simulation‐optimization frameworks, and inferring rules from optimization results. Suggestions on which approach to use depend on context. Parametrization–simulation–optimization or rule inference using heuristics are promising approaches. Increased forecasting capabilities will further benefit the use of model predictive control algorithms to improve system operation. This article is categorized under: Engineering Water > Water, Health, and Sanitation Engineering Water > Methods

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Section: Examples Of Applicationsmentioning

confidence: 99%

Inferring efficient operating rules in multireservoir water resource systems: A review

Macian-Sorribes

Pulido-Velázquez

2019

WIREs Water

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“…In the field of mathematical optimization, stochastic optimization is a framework for modeling optimization problems that involve uncertainties. Stochastic optimization has applications in a broad range of areas, ranging from finance to transportation to energy optimization [27][28][29][30][31]. Stochastic optimization has been found to be an effective tool to address uncertainties within the model and provide a better understanding of optimization results.…”

Section: Introductionmentioning

confidence: 99%

Risk Analysis for Reservoir Real-Time Optimal Operation Using the Scenario Tree-Based Stochastic Optimization Method

Sun

Zhu

Chen

et al. 2018

Water

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The inherent uncertainty of inflow forecasts hinders the reservoir real-time optimal operation. This paper proposes a risk analysis model for reservoir real-time optimal operation using the scenario tree-based stochastic optimization method. We quantify the probability distribution of inflow forecast uncertainty by developing the relationship between two forecast accuracy metrics and the standard deviation of relative forecast error. An inflow scenario tree is generated via Monte Carlo simulation to represent the uncertain inflow forecasts. We establish a scenario tree-based stochastic optimization model to explicitly incorporate inflow forecast uncertainty into the stochastic optimization process. We develop a risk analysis model based on the principle of maximum entropy (POME) to evaluate the uncertainty propagation process from flood forecasts to optimal operation. We apply the proposed methodology to a flood control system in the Daduhe River Basin, China. In addition, numerical experiments are carried out to investigate the effect of two different forecast accuracy metrics and different forecast accuracy levels on reservoir optimal flood control operation as well as risk analysis. The results indicate that the proposed methods can provide decision-makers with valuable risk information for guiding reservoir real-time optimal operation and enable risk-informed decisions to be made with higher reliabilities.

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“…Existing studies developed various optimal hydropower operation models under a regulated market using elaborated methodologies [3,4] and algorithms [5,6] for modeling and solving the problem of revenue maximization [7] or cost minimization [8,9] related to energy production. The revenue or energy production maximization models for a regulated market often assume a market that dominates power sources, wherein the energy produced from power producers can be entirely consumed by the market.…”

Section: Introductionmentioning

confidence: 99%

Analysis of a Stochastic Programming Model for Optimal Hydropower System Operation under a Deregulated Electricity Market by Considering Forecasting Uncertainty

Zhong

Du³

et al. 2018

Water

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In a deregulated electricity market, optimal hydropower operation should be achieved through informed decisions to facilitate the delivery of energy production in forward markets and energy purchase level from other power producers within real-time markets. This study develops a stochastic programming model that considers the influence of uncertain streamflow on hydropower energy production and the effect of variable spot energy prices on the cost of energy purchase (energy shortfall). The proposed model is able to handle uncertainties expressed by both a probability distribution and discretized scenarios. Conflicting decisions are resolved by maximizing the expected value of net revenue, which jointly considers benefit and cost terms under uncertainty. Methodologies are verified using a case study of the Three Gorges cascade hydropower system. The results demonstrate that optimal operation policies are derived based upon systematic evaluations on the benefit and cost terms that are affected by multiple uncertainties. Moreover, near-optimal operation policy under the case of inaccurate spot price forecasts is also analyzed. The results also show that a proper policy for guiding hydropower operation seeks the best compromise between energy production and energy purchase levels, which explores their nonlinear tradeoffs over different time periods.

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Stochastic Programming with a Joint Chance Constraint Model for Reservoir Refill Operation Considering Flood Risk

Cited by 40 publications

References 33 publications

Inferring efficient operating rules in multireservoir water resource systems: A review

Inferring efficient operating rules in multireservoir water resource systems: A review

Risk Analysis for Reservoir Real-Time Optimal Operation Using the Scenario Tree-Based Stochastic Optimization Method

Analysis of a Stochastic Programming Model for Optimal Hydropower System Operation under a Deregulated Electricity Market by Considering Forecasting Uncertainty

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