Equitable Water Distribution in Main Irrigation Canals with Constrained Water Supply

Shahdany, Seied Mehdy Hashemy; Maestre, J. M.; Overloop, P. J. van

doi:10.1007/s11269-015-1000-4

Cited by 32 publications

(5 citation statements)

References 25 publications

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“…For instance, MPC is used to keep the water level of reservoirs within bounds by controlling releases based on inflow forecasts (Anghileri et al., 2016; Raso et al., 2019), or to optimize hydropower production (Doan et al., 2013). MPC has also been applied for controlling water quality (Aydin et al., 2016; Galelli et al., 2015) by flushing, for controlling the water level of inland waterways (Segovia et al., 2019), and in drinking water networks (Ocampo‐Martínez et al., 2009), sewer networks (Joseph‐Duran et al., 2015), irrigation systems (Fele et al., 2014; Hashemy Shahdany et al., 2012) and drainage systems (Dekens, 2013; Horváth et al., 2019).…”

Section: Introductionmentioning

confidence: 99%

How to Choose Suitable Physics‐Based Models Without Tuning and System Identification for Model‐Predictive Control of Open Water Channels?

Horváth,

van Esch,

Pothof

2024

Water Resources Research

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Model predictive control (MPC) is used to manage water systems, and its performance depends on the (internal or control‐oriented) model it is based on. Several models for the hydraulics of open water systems are presented in literature and used in applications, but their performance has not yet been investigated systematically, and no guideline exists on which model to select for a certain channel. The aim of this research is to present a guideline for model choice based on the geometry of the channel and the flow conditions. The guideline is developed by first categorizing the channels into four types, followed by performing time‐domain, frequency domain, and closed‐loop tests for all models and channel types. The evaluation of the tests shows that for short and wave‐dominated channels, the Muskingum, Integrator Delay, and Integrator Delay Zero models perform the best, while for longer channels the linear inertial model is the most suitable. Finally, a decision‐tree is presented how to choose the model. Lastly, a decision‐tree is introduced to aid in the selection of the most appropriate model.

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Section: Introductionmentioning

confidence: 99%

How to Choose Suitable Physics‐Based Models Without Tuning and System Identification for Model‐Predictive Control of Open Water Channels?

Horváth,

van Esch,

Pothof

2024

Water Resources Research

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“…The principle of the ID model is to divide the channel into uniform and backwater zones according to the hydraulic response relationship and use the hydraulic response relationship to predict the evolution of the water level change and flow rate in the channel. This control method has been widely used in water transfer and irrigation projects [19][20][21][22]. However, all of the above articles focus on the accurate control of the water level, ignoring the role of its storage capacity in the regulation process.…”

Section: Introductionmentioning

confidence: 99%

Study on the Hydraulic Response of an Open-Channel Water Transmission Project after Flow Switching

Zhang,

Ren,

Lin

2023

Water

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For the complex and changing water transfer conditions along the nullah water transfer project, it is of great significance to analyze the hydraulic response characteristics of the channel pool to ensure the safe and efficient operation of the project. In this paper, using the adjustable reservoir capacity of the channel pool, combined with the earliest and latest regulation time, a method is proposed to determine the optimal regulation time of water conservancy engineering structures through the hydraulic response characteristics. In order to validate the method, the hydraulic response characteristics of the channel pool during the whole regulation period were investigated using an actual river diversion project as an example. By using the Sobol global sensitivity analysis method, the sensitivity analysis of three variables (water transfer flow, upstream initial flow, and downstream water level) was conducted, and the results showed that the change of water transfer flow was the most-critical factor affecting the optimal regulation time. In order to quantitatively study the correlation between the water transfer flow and the optimal regulation time, the water transfer flow factor was coupled to the existing prediction model, and the results showed that the coupled model can efficiently predict the optimal regulation time, and the NSE coefficient can reach 0.98. In addition, the coupled model can be efficiently used to serve on-site dispatchers for accurately predicting the optimal regulation time and making the corresponding safety decisions.

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“…Its performance is compared with the centralized one, emphasizing the obtained advantages of the decentralized MPC controller. Many other examples can be found in the literature [13][14][15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Design of PI Controllers for Irrigation Canals Based on Linear Matrix Inequalities

Arauz

Maestre

Tian

et al. 2020

Water

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A new Proportional-Integral (PI) tuning method based on Linear Matrix Inequalities (LMIs) is presented. In particular, an LMI-based optimal control problem is solved to obtain a sparse feedback that provides the PI tuning. The ASCE Test Canal 1 is used as a case study. Using a linearised model of the canal, different tunings for the design of the PI controller are developed and tested using the software Sobek. Furthermore, the proposed method is also compared with other tunings proposed for the same canal available in the literature. Our results show that the proposed method reduces by half the maximum errors with respect to other assessed alternatives and minimizes undesired mutual interactions between canal pools. Also, our method improves the optimality degree of the PI tuning by 30%. Therefore, it is concluded that the LMI based PI controllers lead to satisfactory performance in regulating water levels and canal flows/structure outflows, outperforming other tested alternatives, thus becoming a useful tool for irrigation canal control.

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Equitable Water Distribution in Main Irrigation Canals with Constrained Water Supply

Cited by 32 publications

References 25 publications

How to Choose Suitable Physics‐Based Models Without Tuning and System Identification for Model‐Predictive Control of Open Water Channels?

How to Choose Suitable Physics‐Based Models Without Tuning and System Identification for Model‐Predictive Control of Open Water Channels?

Study on the Hydraulic Response of an Open-Channel Water Transmission Project after Flow Switching

Design of PI Controllers for Irrigation Canals Based on Linear Matrix Inequalities

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