A Two Stage Optimization Approach for Calibrating Water Distribution Systems

Asadzadeh, Masoud; Tolson, Bryan A.; McKillop, Robert

doi:10.1061/41203(425)148

Cited by 8 publications

(3 citation statements)

References 4 publications

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“…After selecting input variables, we use the Gaussian RBFs method, which is capable of representing functions for a large class of problems [ Buşoniu et al ., ; Giuliani et al ., ] to incorporate the selected input variables into cascade reservoir operating rules. In the end, using the PA‐DDS multiobjective optimization algorithm, which is robust in solving water resources problems [ Asadzadeh and Tolson , ; Asadzadeh et al ., ; G. Yang et al ., ], we optimize these cascade reservoir operation rules, designed via the RBFs, and evaluated in terms of hypervolume indicator [ Fleischer , ; Fonseca et al ., ], water supply, and power generation. It is worth mentioning that the hypervolume indicator is a guidance criterion that evaluates solutions in multiobjective optimization [ Knowles et al ., ].…”

Section: Methodsmentioning

confidence: 99%

Multiobjective reservoir operating rules based on cascade reservoir input variable selection method

Yang

Guo

Liu

et al. 2017

Water Resources Research

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The input variable selection in multiobjective cascade reservoir operation is an important and difficult task. To address this problem, this study proposes the cascade reservoir input variable selection (CIS) method that searches for the most valuable input variables for decision making in multiple‐objectivity cascade reservoir operations. From a case study of Hanjiang cascade reservoirs in China, we derive reservoir operating rules based on the combination of CIS and Gaussian radial basis functions (RBFs) methods and optimize the rules through Pareto‐archived dynamically dimensioned search (PA‐DDS) with two objectives: to maximize both power generation and water supply. We select the most effective input variables and evaluate their impacts on cascade reservoir operations. From the simulated trajectories of reservoir water level, power generation, and water supply, we analyze the multiobjective operating rules with several input variables. The results demonstrate that the CIS method performs well in the selection of input variables for the cascade reservoir operation, and the RBFs method can fully express the nonlinear operating rules for cascade reservoirs. We conclude that the CIS method is an effective and stable approach to identifying the most valuable information from a large number of candidate input variables. While the reservoir storage state is the most valuable information for the Hanjiang cascade reservoir multiobjective operation, the reservoir inflow is the most effective input variable for the single‐objective operation of Danjiangkou.

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Section: Methodsmentioning

confidence: 99%

Multiobjective reservoir operating rules based on cascade reservoir input variable selection method

Yang

Guo

Liu

et al. 2017

Water Resources Research

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“…This is important for avoiding potential model overfitting (Kapelan 2010). • Asadzadeh et al (2010) used optimization algorithms based on dynamically dimensioned search (DDS) in which the fire-flow test measurements were first fitted using the multiobjective Pareto archived DDS (PA-DDS) algorithm (Asadzadeh and Tolson 2009) after which the demand pattern multipliers were calibrated using the single objective DDS algorithm (Tolson and Shoemaker 2007).…”

Section: • Shen and Mcbean (2010) Linked A Genetic Algorithm With Montementioning

confidence: 99%

Battle of the Water Calibration Networks

Ostfeld

Salomons²,

Ormsbee

et al. 2012

J. Water Resour. Plann. Manage.

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147

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Calibration is a process of comparing model results with field data and making the appropriate adjustments so that both results agree. Calibration methods can involve formal optimization methods or manual methods in which the modeler informally examines alternative model parameters. The development of a calibration framework typically involves the following: (1) definition of the model variables, coefficients, and equations; (2) selection of an objective function to measure the quality of the calibration; (3) selection of the set of data to be used for the calibration process; and (4) selection of an optimization/manual scheme for altering the coefficient values in the direction of reducing the objective function. Hydraulic calibration usually involves the modification of system demands, fine-tuning the roughness values of pipes, altering pump operation characteristics, and adjusting other model attributes that affect simulation results, in particular those that have significant uncertainty associated with their values. From the previous steps, it is clear that model calibration is neither unique nor a straightforward technical task. The success of a calibration process depends on the modeler's experience and intuition, as well as on the mathematical model and procedures adopted for the calibration process. This paper provides a summary of the Battle of the Water Calibration Networks (BWCN), the goal of which was to objectively compare the solutions of different approaches to the calibration of water distribution systems through application to a real water distribution system. Fourteen teams from academia, water utilities, and private consultants participated. The BWCN outcomes were presented and assessed at the 12th Water Distribution Systems Analysis conference in Tucson, Arizona, in September 2010. This manuscript summarizes the BWCN exercise and suggests future research directions for the calibration of water distribution systems.

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“…Few studies have defined demand pattern coefficients as calibration parameter. Asadzadeh et al (2011) performed calibration of pipe roughness and demand pattern coefficients of C-Town WDSs to measure hourly tank levels, pump flows and fire flow test data during 1-week operation.…”

mentioning

confidence: 99%

A New Method for Simultaneous Calibration of Demand Pattern and Hazen-Williams Coefficients in Water Distribution Systems

Dini

Tabesh

2014

Water Resour Manage

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Water distribution systems, where flow in some pipes is not measured or storage tanks are connected together, calculation of demand pattern coefficients of the network is difficult. Since, Hazen-Williams coefficients of the network are also unknown; the problem is becoming unintelligible further. The present study proposes a new method for simultaneous calibration of demand pattern and Hazen-Williams coefficients that uses the Ant Colony Optimization (ACO) algorithms coupled with the hydraulic simulator (EPANET2) in a MATLAB code. In this paper demand pattern and Hazen-Williams coefficients are the calibration parameters and measured data consist of nodal pressure heads and pipe flows. The defined objective function minimizes the difference between the measured and simulated values. The new proposed method was tested on a two-loop test example and a real water distribution network. The results show that the new calibration model is able to calibrate demand pattern and Hazen-Williams coefficients simultaneously with high precision and accuracy.

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A Two Stage Optimization Approach for Calibrating Water Distribution Systems

Cited by 8 publications

References 4 publications

Multiobjective reservoir operating rules based on cascade reservoir input variable selection method

Multiobjective reservoir operating rules based on cascade reservoir input variable selection method

Battle of the Water Calibration Networks

A New Method for Simultaneous Calibration of Demand Pattern and Hazen-Williams Coefficients in Water Distribution Systems

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