Real-Time Operation of Reservoir System by Genetic Programming

Fallah-Mehdipour, Elahe; Bozorg‐Haddad, Omid; Mariňo, Miguel A.

doi:10.1007/s11269-012-0132-z

Cited by 121 publications

(24 citation statements)

References 26 publications

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“…is also includes prevention of overflow situation in the reservoir [4]. e reservoir rule curves have been improved to provide the optimal solution for long-term operation.…”

Section: Introductionmentioning

confidence: 99%

Development of Future Rule Curves for Multipurpose Reservoir Operation Using Conditional Genetic and Tabu Search Algorithms

Kangrang

Prasanchum

Hormwichian

2018

Advances in Civil Engineering

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Optimal rule curves are necessary guidelines in the reservoir operation that have been used to assess performance of any reservoir to satisfy water supply, irrigation, industrial, hydropower, and environmental conservation requirements. is study applied the conditional genetic algorithm (CGA) and the conditional tabu search algorithm (CTSA) technique to connect with the reservoir simulation model in order to search optimal reservoir rule curves. e Ubolrat Reservoir located in the northeast region of ailand was an illustrative application including historic monthly inflow, future inflow generated by the SWAT hydrological model using 50-year future climate data from the PRECIS regional climate model in case of B2 emission scenario by IPCC SRES, water demand, hydrologic data, and physical reservoir data. e future and synthetic inflow data of reservoirs were used to simulate reservoir system for evaluating water situation. e situations of water shortage and excess water were shown in terms of frequency magnitude and duration. e results have shown that the optimal rule curves from CGA and CTSA connected with the simulation model can mitigate drought and flood situations than the existing rule curves. e optimal future rule curves were more suitable for future situations than the other rule curves.

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“…is also includes prevention of overflow situation in the reservoir [4]. e reservoir rule curves have been improved to provide the optimal solution for long-term operation.…”

Section: Introductionmentioning

confidence: 99%

Development of Future Rule Curves for Multipurpose Reservoir Operation Using Conditional Genetic and Tabu Search Algorithms

Kangrang

Prasanchum

Hormwichian

2018

Advances in Civil Engineering

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“…For instance, Sarangi et al [] applied an ANN model to predict the runoff and sediment yield in a Canadian watershed, and Nayak et al [] used a neuro‐fuzzy model for short‐term flood forecasting. Kisi and Cimen [] developed a hybrid model that combines the wavelet transform with SVR for monthly streamflow forecasting, and Fallah‐Mehdipour et al [] examined the real‐time operation of a reservoir system using GP.…”

Section: Introductionmentioning

confidence: 99%

A multivariate conditional model for streamflow prediction and spatial precipitation refinement

et al. 2015

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The effective prediction and estimation of hydrometeorological variables are important for water resources planning and management. In this study, we propose a multivariate conditional model for streamflow prediction and the refinement of spatial precipitation estimates. This model consists of high dimensional vine copulas, conditional bivariate copula simulations, and a quantile‐copula function. The vine copula is employed because of its flexibility in modeling the high dimensional joint distribution of multivariate data by building a hierarchy of conditional bivariate copulas. We investigate two cases to evaluate the performance and applicability of the proposed approach. In the first case, we generate one month ahead streamflow forecasts that incorporate multiple predictors including antecedent precipitation and streamflow records in a basin located in South China. The prediction accuracy of the vine‐based model is compared with that of traditional data‐driven models such as the support vector regression (SVR) and the adaptive neuro‐fuzzy inference system (ANFIS). The results indicate that the proposed model produces more skillful forecasts than SVR and ANFIS. Moreover, this probabilistic model yields additional information concerning the predictive uncertainty. The second case involves refining spatial precipitation estimates derived from the tropical rainfall measuring mission precipitationproduct for the Yangtze River basin by incorporating remotely sensed soil moisture data and the observed precipitation from meteorological gauges over the basin. The validation results indicate that the proposed model successfully refines the spatial precipitation estimates. Although this model is tested for specific cases, it can be extended to other hydrometeorological variables for predictions and spatial estimations.

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“…The purpose of the model was for minimizing flood damages in the downstream areas. Fallah-Mehdipour et al (2012) suggested the use of genetic programming (GP) to develop a reservoir operation policy simultaneously with inflow prediction. The method was to extract an operational policy simultaneously with inflow prediction helps the operator to make decision to determine how much water to release from the reservoir without employing a prediction model.…”

Section: Previous Optimization/simulation Modelsmentioning

confidence: 99%

Development of an Optimization/Simulation Model for Real-Time Flood-Control Operation of River-Reservoirs Systems

Che

Mays

2015

Water Resour Manage

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Real-time optimal operation models for river-reservoir systems, unfortunately, are not widely available. Such models are still in their infancy perhaps due to the complexity of the application. This paper presents the development and testing of a methodology for determining reservoir release schedules before, during, and after an extreme flood event in real time. The problem is formulated as a real-time optimal control problem in which reservoir releases represent the decision variables. The model consists of five major components: (1) the U.S. Army Corps of Engineers (USACE) Hydrologic Engineering Center -Hydrologic Modeling System (HEC-HMS), which simulates rainfall-runoff processes of watershed systems; (2) the U.S. Army Corps of Engineers Hydrologic Engineering Center -River Analysis System (HEC-RAS) for one-dimensional unsteady flow routing; (3) a reservoir release operation model; (4) a short-term rainfall forecasting model to project rainfall over the next few hours during a rainfall event; and (5) a genetic algorithm (GA) optimizer interfaced with the other components that determine the real time operation of a river-reservoir systems. An example application is used to test the development of the modeling framework, also illustrating the use of such a model. Each model component and its interface in the modeling framework was tested for quality assurance.

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Real-Time Operation of Reservoir System by Genetic Programming

Cited by 121 publications

References 26 publications

Development of Future Rule Curves for Multipurpose Reservoir Operation Using Conditional Genetic and Tabu Search Algorithms

Development of Future Rule Curves for Multipurpose Reservoir Operation Using Conditional Genetic and Tabu Search Algorithms

A multivariate conditional model for streamflow prediction and spatial precipitation refinement

Development of an Optimization/Simulation Model for Real-Time Flood-Control Operation of River-Reservoirs Systems

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