GoRoSoBo: an overall control diagram to improve the efficiency of water transport systems in real time

Abstract

Abstract:The agriculture holds an important part of the food chain and the water resources for agriculture are essential. The problem is the water transport systems present low efficiencies in practice. The yield agriculture has to be optimized, because the goal of an operational water manager is to deliver the water to the irrigation sites accurately and efficiently. In order to fulfill this objective, we propose a centralized overall control diagram to optimize the management of the canal. Our control diagram in real-time is mainly composed by two algorithms, CSE and GoRoSoBo. The first one is a powerful tool in canal management, so that it is able to estimate the real extracted flow in the canal and the hydrodynamic canal state from measured level data at selected points. The second one is an essential tool in the management of a canal, a feedback control algorithm operating in real-time. The GoRoSoBo algorithm (Gómez, Rodellar, Soler, Bonet) is able to calculate the optimum gates trajectories for a predictive horizon taking into account the current canal state and the real extracted flow both obtained by CSE. Powered by Editorial Manager® and ProduXion Manager® from Aries Systems CorporationTitle: GOROSOBO: An overall control diagram to improve the efficiency of water transport systems in real time Manuscript Click here to download Manuscript PaperGRSB_17_10_2016. doc 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 ABSTRACTThe agriculture holds an important part of the food chain and the water resources for agriculture are essential. The problem is the water transport systems present low efficiencies in practice. The yield agriculture has to be optimized, because the goal of an operational water manager is to deliver the water to the irrigation sites accurately and efficiently. In order to fulfill this objective, we propose a centralized overall control diagram to optimize the management of the canal. Our control diagram in real-time is mainly composed by two algorithms, CSE and GoRoSoBo. The first one is a powerful tool in canal management, so that it is able to estimate the real extracted flow in the canal and the hydrodynamic canal state from measured level data at selected points. The second one is an essential tool in the management of a canal, a feedback control algorithm operating in real-time. The GoRoSoBo algorithm (Gómez, Rodellar, Soler, Bonet) is able to calculate the optimum gates trajectories for a predictive horizon taking into account the current canal state and the real extracted flow both obtained by CSE.

Modeling and control in open-channel irrigation systems: A review

“…Therefore, in order to obtain a stable control-oriented model, the obtained model has a high order. this modeling strategy is used in several reported works (e.g., Reddy 1990b;Garcia et al 1992;Mohan Reddy et al 1992;Mohan Reddy 1995;Reddy 1996;Mohan Reddy and Jacquot 1999;Durdu 2004Durdu , 2006Lemos et al 2009;Durdu 2010;Feng and Wang 2011;Shang et al 2011;Xu et al 2012;Breckpot et al 2013;Soler et al 2013a;Cen et al 2017;Bonet et al 2017;Lacasta et al 2018). On the other hand, Malaterre (1998) uses an implicit Preissmann finite-difference scheme, with the advantage that the stability of the model does not depend on the discretization step size, and Liu et al (1998) propose the use of this scheme in the development of a control strategy based on an inverse solution of the nonlinear SVE.…”

“…] ⊤ ∈ ℝ is considered as a desired level vector, and ̄ is the mean of because excessive gates and flows changes produce mechanical wear and water levels oscillations, to reduce excessive gates and flows changes is desired. The key performance indicators can be used as a measure of performance for controlled systems (e.g., Xu et al 2012;Munir et al 2012;Soler et al 2013a;Bonet et al 2017;Ke et al 2018;Zheng et al 2019), and as a design criteria in optimal controllers (e.g., Feliu-Batlle et al 2011;Ke et al 2018). A relation of the principal key performance indicators is presented in Table 3, where: i) the maximum absolute error (MAE) is the maximum normalized error between the desired and measured level; ii) the integral of the absolute error (IAE) accounts for the cumulative level error along a time period ( ); iii) the steady-state error (StE) is the maximum absolute level error during a time period when the steady state has been reached; iv) the integral square error (ISE) also accounts for the cumulative level error and weights large deviations; v) the absolute gate movement (IAW) relates to positions changes of the regulation structures; and vi) the integrated absolute discharge change (IAQ) accounts for flow variations.…”

“…Finite Differences Lemos et al 2009, Feng and Wang 2011, Shang et al 2011, Soler et al 2013a, Breckpot et al 2013, Soler et al 2013b, Bonet et al 2017, Cen et al 2017ID Ke et al 2018black-box Model Litrico et al 2007, Begovich et al 2007, Feliu-Batlle et al 2009a, Feliu-Batlle et al 2009b, Lozano et al 2010, Feliu-Batlle et al 2011, Munir et al 2012gray-Box Model Cantoni et al 2007, Domingues et al 2011, Herrera et al 2013, Bolea et al 2014b, Sadowska et al 2015a, (Horváth et al, 2015a)…”

Key parameters for assessing the deterioration of reinforced concrete pipes in water networks

“…In this scenario, the appropriate conservation of water infrastructures is essential for the management of water resources for both the present and future generations. In addition to these considerations, water resources are expected to decrease as a result of climate change (Bonet et al, 2017). Urban water systems constitute a vital segment of the global public infrastructure for water utilities, and the municipalities are tasked with the responsibility of overseeing and improving them for present and future generations.…”

Optimal Pumping Flow Algorithm to Improve Pumping Station Operations in Irrigation Systems

“…As shown in Figure 2, the primary energy sources in Spain were oil and natural gas, with 39.6% and 21% shares of the market in 2017, respectively. These were usually used to generate electricity according to International Energy Agency [6]. On the other hand, by 2021, wind energy had become the increasingly leading source of renewable energy.…”