A modelling methodology for natural dam-river network systems

Zhuan, Xiangtao; Zheng, Guoxin; Xia, Xiaohua

doi:10.1016/j.conengprac.2008.10.009

Cited by 3 publications

(1 citation statement)

References 38 publications

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“…Furthermore, the relationship assessment of variables from reservoirs and rivers natural system [54]; A Bayesian network to manage gates to avoid floods, helpful on decision making about which maneuvers has to be performed [55]; The analysis of water temperature variation due to dams structure revealed that gates operation does not have a great influence on water temperature, and that this variable is mainly influenced by climate conditions and hydrologic variables [56]; A Fuzzy Logic for the reservoirs operation system on hydropower plants, taking into account energy cost uncertainties on gate water flow [21].…”

Section: Systematic Literature Review On Economic and Environmental Amentioning

confidence: 99%

Economic, Environmental and Social Gains of the Implementation of Artificial Intelligence at Dam Operations toward Industry 4.0 Principles

et al. 2020

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Due to the increasing demand for water supply of urban areas, treatment and supply plants are becoming important to ensure availability and quality of this essential resource for human health. Enabling technologies of Industry 4.0 have the potential to improve performances of treatment plants. In this paper, after reviewing contributions in scientific literature on I4.0 technologies in dam operations, a study carried out on a Brazilian dam is presented and discussed. The main purpose of the study is to evaluate the economic, environmental, and social advantages achieved through the adoption of Artificial Intelligence (AI) in dam operations. Unlike automation that just respond to commands, AI uses a large amount of data training to make computers able to take the best decision. The current study involved a company that managed six reservoirs for treatment systems supplying water to almost ten million people at the metropolitan area of São Paulo City. Results of the study show that AI adoption could lead to economic gain in figures around US$ 51,000.00 per year, as well as less trips between sites and less overtime extra costs on the main operations. Increasing gates maneuvers agility result in significant environmental gains with savings of about 4.32 billion L of water per year, enough to supply 73,000 people. Also, decreasing operational vehicle utilization results in less emissions. Finally, the AI implementation improved the safety of dam operations, resulting in social benefits such as the flood risk mitigation in cities and the health and safety of operators.

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Section: Systematic Literature Review On Economic and Environmental Amentioning

confidence: 99%

Economic, Environmental and Social Gains of the Implementation of Artificial Intelligence at Dam Operations toward Industry 4.0 Principles

et al. 2020

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A Wetland Network Design for Water Allocation Based on Environmental Flow Requirements

Yang

Cui

2012

CLEAN Soil Air Water

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Excessive water use with economic development has led to the shortage of environmental flow requirements (EFRs) for different wetlands in the past years, a number of wetlands become degraded or disappeared. A suitable water allocation used for wetland restoration has become focus in the field. This article presents a wetland network design approach to achieve the objective of water allocation. First, a wetland network was designed by linking linear wetlands (as edges) and patch wetlands (as nodes), the EFRs were then calculated for restoration of wetlands under three scenarios (normal years, dry years, and extremely dry years) defined by annual precipitation; second, the water trade-off between human use and wetland network was determined, and after that water allocation was arranged within the designed wetland network based on certain priorities. Finally, the satisfaction proportion of EFRs, flood-control capacity, and connectivity for the designed wetland network were assessed by two functional indicators and one structural indicator. The results showed that the designed network with three new patch wetlands and water trade-off scenarios made additional water available to wetlands. This additional water amount ranges from 56.1 to 79.4 million m 3 in different scenarios. The three assessment indicators reflect the improved performance of the designed wetland network. This article can promote the understanding of wetland network and serve as water management tool that goes beyond conservation of individual wetland.Abbreviations: EFRs, environmental flow requirements; PDZ, prohibited development zone; RDZ, restricted development zone; SDZ, suitable development zone

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Robust and nonlinear control literature survey (No. 13)

2009

Intl J Robust & Nonlinear

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In order to keep readers up-to-date, the journal will contain a list of recently published journal articles relevant to the fields of robust and nonlinear control six times a year. This list is compiled from a wide range of journals. Please note that even though the list has been broadly categorized these classifications are by no means strict, and are there to assist the reader. Please also note that inclusion in the list is not an endorsement of a papers quality. If you have any suggestions or comments, please email Leonardo Giovanini at lgiovanini@fich.unl.edu.ar. THEORETICAL DEVELOPMENTS IN ROBUST CONTROLFleming A, Wills A. Optimal periodic trajectories for band-limited systems. IEEE Transaction on Control Systems Technology 2009; 17(3):552-562. Ghosh S, Das S, Ray G. Decentralized stabilization of uncertain systems with interconnection and feedback delays: an LMI approach. IEEE Transaction on Automatic Control 2009; 54(4):905-912. Guo L, Yin L. Robust PDF control with guaranteed stability for non-linear stochastic systems under modelling errors. IET Control Theory and Applications 2009; 3(5):575-582. Huang G, Wang S. Use of predicted information to improve the control performance of systems with uncertainties. Journal of Process Control 2009; 19(3):457-463. Jetto L, Orsini V. Some remarks on the robust Schur stability analysis of interval polynomials. International Journal of Control 2009; 82(3):493-496. Karafyllis I, Kravaris C. Robust global stabilisability by means of sampled-data control with positive sampling rate. International Journal of Control 2009; 82(4):755-772. Khadra A, Liu X, Shen X. Analyzing the robustness of impulsive synchronization coupled by linear delayed impulses. IEEE Transaction on Automatic Control 2009; 54(4):923-928. Nobakhti A, Brown M, Wang H. On the sensitivity of the control structure selection problem in largescale multivariable systems. IET Control Theory and Applications 2009; 3(5):533-550. Ou L-L, Zhang W-D, Yu L. Low-order stabilization of LTI systems with time delay. IEEE Transaction on Automatic Control 2009; 54(4):774-787. Sun J, Djouadi S. Robust stabilization over communication channels in the presence of unstructured uncertainty. IEEE Transaction on Automatic Control 2009; 54(4):830-834. Wallin R, Hansson A, Johansson J. A structure exploiting preprocessor for semidefinite programs derived from the Kalman-Yakubovich-Popov Lemma. IEEE Transaction on Automatic Control 2009; 54(4):697-704. Zhang X-N, Yang G-H. Control synthesis via state feedback with finite frequency specifications for time-delay systems. International Journal of Control 2009; 82(3):508-516. 2. THEORETICAL DEVELOPMENTS IN NONLINEAR CONTROL Alamir M, Welsh J, Goodwin G. Redundancy versus multiple starting points in nonlinear system related inverse problems. Automatica 2009; 45(4): 1052-1057. Ambrosino R, Calabrese F, Cosentino C, De Tommasi G. Sufficient conditions for finite-time stability of impulsive dynamical systems. IEEE Transaction on Automatic Control 2009; 54(4): 861-865. Costa E, do Val J. Uni...

show abstract

A modelling methodology for natural dam-river network systems

Cited by 3 publications

References 38 publications

Economic, Environmental and Social Gains of the Implementation of Artificial Intelligence at Dam Operations toward Industry 4.0 Principles

Economic, Environmental and Social Gains of the Implementation of Artificial Intelligence at Dam Operations toward Industry 4.0 Principles

A Wetland Network Design for Water Allocation Based on Environmental Flow Requirements

Robust and nonlinear control literature survey (No. 13)

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