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Proceedings ArticleDOI

Optimization methods for water supply SCADA system

TL;DR: One possible methodology for control, reduction and optimization of water loss in the communal water supply system is recommended, with efficient usage of modern SCADA systems implemented to existing water supply systems, becoming integral part in the new optimized operational management and control system of communal water Supply companies.
Abstract: Drinking water reserves are not infinite natural resource. Rapid social development generates huge pollution of all of the environment, including surface and underground drinking water reserves. One of the biggest challenges in management and control of modern city water supply system is to retain uninterrupted supply with chemically and biologically safe drinking water. Real-time monitoring systems of the water quality and quantity parameters gives us on-time alert and more time for reaction. The possible solution for this challenge is presented. Real-time measuring station using industrial SCADA system and optimization of the system is recommended. SCADA system provides continuous monitoring of the many physical, chemical and biological parameters enabling fast and reliable detection of the deviations in system. Saved data give chance for additional analysis of the measured parameters and dependencies between. One possible methodology for control, reduction and optimization of water loss in the communal water supply system is recommended, with efficient usage of modern SCADA systems implemented to existing water supply systems, becoming integral part in the new optimized operational management and control system of communal water supply companies.
Citations
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Journal ArticleDOI
TL;DR: This paper designs a water quality monitoring system combined with the computer image processing technology and use computer vision to analyze the fish behavior in real-time for monitoring the existence or not of water pollution, and can achieve more accurate multi-level classification than the shallow neural network, such as RNN.
Abstract: Water pollution has seriously threatened our life, so an effective water quality monitoring mechanism is the most important part of water quality management. Most studies use biological monitoring methods to monitor water pollutants, such as pesticides, heavy metals, and organic pollutants. However, there are still many difficulties at present. Few methods consider the influence of illumination and complex background in the monitoring environment, and the characteristics parameters extracted in the systems are single. In addition, the results of using shallow neural networks for water quality classification are often not ideal. In order to solve the above problems, we design a water quality monitoring system combined with the computer image processing technology and use computer vision to analyze the fish behavior in real-time for monitoring the existence or not of water pollution. For the illumination problem, we use the no-reference quality assessment algorithm based on natural scene statistics for contrast distortion images to evaluate the video and configure the lighting conditions of the monitoring environment. White balance preprocessing is also performed to provide a great basis for moving target detection. Besides, we use background modeling to eliminate the influence of complex background on the moving target detection and the foreground is extracted using the saliency detection algorithm. In order to comprehensively analyze the influence of water quality on the fish behavior from the extracted foreground targets, multi-dimensional feature parameters are used to quantify the indicators, including movement velocity, rotation angle, spatial standard deviation, and body color which characterize the behavior changes of the fish. Finally, the classification model based on the long short-term memory neural network is used to classify the feature parameters data of the fish behavior in different water quality environments. In this paper, red zebra fish is used as the indicator organism and copper sulfate solution is used as the toxic pollutant to simulate the water pollution. Experiment results show that the classification accuracy rate of water quality using the proposed system can reach 100% at level 2 classification (93.33% at level 3 and 91% at level 4). Our system can achieve more accurate multi-level classification than the shallow neural network, such as RNN, and it is faster for real-time monitoring with a high reference for the water environment emergencies.

34 citations


Cites background from "Optimization methods for water supp..."

  • ...[2] constructed the SCADA system for modern city water supply with continuous monitoring of the physical, chemical and biological parameters....

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Journal ArticleDOI
02 Mar 2020
TL;DR: This paper aims to provide the next step in obtaining a proactive historian application and proposes a non-invasive decision and control solution in the context of the Industrial Internet of Things, meant to reduce energy consumption in a water treatment and distribution process.
Abstract: The industry is generally preoccupied with the evolution towards Industry 4.0 principles and the associated advantages as cost reduction, respectively safety, availability, and productivity increase. So far, it is not completely clear how to reach these advantages and what their exact representation or impact is. It is necessary for industrial systems, even legacy ones, to assure interoperability in the context of chronologically dispersed and currently functional solutions, respectively; the Open Platform Communications Unified Architecture (OPC UA) protocol is an essential requirement. Then, following data accumulation, the resulting process-aware strategies have to present learning capabilities, pattern identification, and conclusions to increase efficiency or safety. Finally, model-based analysis and decision and control procedures applied in a non-invasive manner over functioning systems close the optimizing loop. Drinking water facilities, as generally the entire water sector, are confronted with several issues in their functioning, with a high variety of implemented technologies. The solution to these problems is expected to create a more extensive connection between the physical and the digital worlds. Following previous research focused on data accumulation and data dependency analysis, the current paper aims to provide the next step in obtaining a proactive historian application and proposes a non-invasive decision and control solution in the context of the Industrial Internet of Things, meant to reduce energy consumption in a water treatment and distribution process. The solution is conceived for the fog computing concept to be close to local automation, and it is automatically adaptable to changes in the process’s main characteristics caused by various factors. The developments were applied to a water facility model realized for this purpose and on a real system. The results prove the efficiency of the concept.

10 citations


Cites methods from "Optimization methods for water supp..."

  • ...Towards this system functioning improvements, the study from [35] proposes a methodology for both control and optimization of water loss in the water supply system by using real-time monitoring and industrial Supervisory Control and Data Acquisition (SCADA) systems....

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Proceedings ArticleDOI
01 Sep 2020
TL;DR: This article proposes a new approach to software and hardware implementation of an automatic system for diagnosing the condition of an intelligent electric drive based on the normal behavior method that can significantly reduce its cost and expand the functionality of existing automatic control systems.
Abstract: This article proposes a new approach to software and hardware implementation of an automatic system for diagnosing the condition of an intelligent electric drive based on the normal behavior method. Diagnostic technology is based on taking into account deviations between a given and calculated mechanical torque in the structure of an intelligent electrical drive. Software analysis of these deviations in the control system allows you to diagnose undesirable phenomena in an electrical machine and drive equipment. The main technological parameters for calculating the mechanical torque are currents, voltages and speed. In addition, the design parameters of an intelligent electric drive are taken into account. According to the results of the study, a prototype of a system for diagnosing an intelligent electrical drive in real time was developed. The software implementation of the prototype diagnostic system is based on a universal dispatch and data collection system. This approach to the software implementation of the diagnostic system can significantly reduce its cost and expand the functionality of existing automatic control systems. The results of tuning and testing the diagnostic system are presented. The response of the control system to the deviation of the mechanical torque from the given torque of normal behavior is simulated.

5 citations

Journal ArticleDOI
12 Dec 2020
TL;DR: In this article, the SCADA system of electricity metering using the internet network aims to monitor electrical energy remotely by utilizing internet services, and the system consists of a meter that measures electric quantities acquired by a server located close to the meter.
Abstract: SCADA (Supervisory Control and Data Acquisition) system of electricity metering using the internet network aims to monitor electrical energy remotely by utilizing internet services. The system consists of a meter that measures electric quantities acquired by a server located close to the meter. The client reads data acquired by the server through the internet network. The use of internet networks for data transmission generally results in latency time, which affects the validity of the data read by the client, resulting in reduced cumulative power calculation accuracy. In this article, energy calculations using current, voltage and power factor data on the client are compared with the energy value calculated by the power meter. Errors that occur are used to calculate the accuracy of the system. The experiment resulted in latency times ranging from 110 ms - 11219 ms with an average of 572.3025 ms with valid data ranging from 93% of population data and accuracy values ranging from 99.2974% to 99.8648%. The resulting accuracy is within the ANSI C12.20 standard.

4 citations

References
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01 Dec 2006

278 citations


"Optimization methods for water supp..." refers background in this paper

  • ...It is current state-of-the-art area for research [2][3]....

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Proceedings ArticleDOI
12 Jun 2016
TL;DR: This SCADA system provides continues (24/7) monitoring of the diverse physical, chemical, biological parameters enabling fast and reliable detection of the pollutants.
Abstract: Protection of the natural water resources becomes more and more important issue. Usual way to deal with this problem is to build on-site monitoring station capable for independent measurement of water quality parameters where all the measurement equipment is installed and where all measurements are done. But, in this case a dedicated person is needed which on regular basis will collect the data from the station, in order to compare them with laboratory measurements. In this way, delay between emerging and noted data is introduced. It is here presented possible solution of this problem developing completely independent real-time measuring station using industrial SCADA system. Real-time monitoring of the water quality and quantity parameters gives on-time alert and time for reaction. This SCADA system provides continues (24/7) monitoring of the diverse physical, chemical, biological parameters enabling fast and reliable detection of the pollutants. Saved data give chance for additional (off-site) analysis of the measured parameters and their connections. System is consisted of Central Monitoring Station (located at the Faculty of Mechanical Engineering in Skopje), Local Monitoring Station (located near town Demir Kapija), and several mobile monitoring stations. Specially designed Local Monitoring Station has been automated with the use of industrial PLC in order to integrate the work of all diverse instruments, real-time measuring devices, analytical measuring devices and station functionality equipment. Data gathered at the Remote real-time stations is continuously sent to CMS for further analysis.

13 citations


"Optimization methods for water supp..." refers background in this paper

  • ...SCADA systems are centralized computer-controlled systems which are used in industry to monitor and control whole industry processes and plants [1, 5, 7]....

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Journal Article
TL;DR: The paper describes different method used to solve the unit commitment problems and suggests a comprehensive algorithm that combines the strength of all the methods and overcome each other’s weakness would be a suitable approach.
Abstract: Unit Commitment helps in making decision that which unit should be running in which period so as to satisfy the varying demand of electricity. In case of electricity the load is higher during the daytime especially in evening when industrial loads are high, lights are on and lower during the night and early morning when most of the population is asleep. Unit commitment helps in deciding which generating unit should be on i.e. to bring the unit up to speed, synchronize it to the system, and connect it so it can deliver power to the network. The paper describes different method used to solve the unit commitment problems. All these methods have some weakness, a comprehensive algorithm that combines the strength of all the methods and overcome each other’s weakness would be a suitable approach for solving unit commitment problems.

2 citations


"Optimization methods for water supp..." refers methods in this paper

  • ...Simple, but most effective optimization is priority list method of optimal pump unit commitment in water supply system [4]....

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