Optimization of Water Reservoir Operation to Minimize the Economic Losses Caused by Pollution

Ciolofan, Sorin N.; Militaru, Gheorghe; Drăghia, Aurelian Florentin; Drobot, Radu; Drăgoicea, Monica

doi:10.1109/access.2018.2879571

Cited by 7 publications

(4 citation statements)

References 41 publications

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“…But, the study from [39] was focused on the distribution network, and it did not deal with the water treatment process. In the same context, authors in [40] presented a strategy to optimize reservoir functioning to minimize economic losses caused by pollution, and authors in [41] detailed an energy consumption reduction conceptual solution and its impact on swimming pool water distribution. Another important issue was presented in [42] regarding the influence of raw water over the treatment process.…”

Section: Towards a Proactive Historian Application In The Water Industrymentioning

confidence: 99%

Identifying Data Dependencies as First Step to Obtain a Proactive Historian: Test Scenario in the Water Industry 4.0

Nicolae

Korodi

Silea

2019

Water

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Current efforts towards achieving better connectivity and increasing intelligence in functioning of industrial processes are guided by the Industrial Internet of Things paradigm and implicitly stimulate occurrence of data accumulation. In recent years, several researchers and industrial products have presented Historian application solutions for data accumulation. The large amounts of data that are gathered by these Historians remains mostly unused or used only for reporting purposes. So far, Historians have been focused on connectivity, data manipulation possibilities, and sometimes on low-cost solutions in order to gain higher applicability or to integrate multiple SCADA servers (e.g. Siemens–WinCC, Schneider Electric – Vijeo Citect, IGSS, Wonderware, InduSoft Web Studio, Inductive Automation – Ignition, etc.), etc. Both literature and industry are currently unable to identify a Historian solution that functions in fog and efficiently applies and is built upon Industry 4.0 ideas. The future is to conceive a proactive Historian that is able to, besides gathering data, identify dependencies and patterns for particular processes and elaborate strategies to increase performance in order to provide feedback through corrective action on the functional system. Using available solutions, determining patterns by the Historian operator in the context of big data is a tremendous effort. The motivation of this research is provided by the currently unoptimized and partly inefficient systems in the water industry that can benefit from cost reduction and quality indicator improvements through IIoT concepts related to data processing and process adjustments. As the first part of more complex research to obtain a proactive Historian, the current paper wishes to propose a reference architecture and to address the issue of data dependency analyses as part of pattern identification structures. The conceptual approach targets a highly customizable solution considering the variety of industrial processes, but it also underlines basic software modules as generally applicable for the same reason. To prove the efficiency of the obtained solution in the context of real industrial processes, and their corresponding monitoring and control solutions, the paper presents a test scenario in the water industry.

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Section: Towards a Proactive Historian Application In The Water Industrymentioning

confidence: 99%

Identifying Data Dependencies as First Step to Obtain a Proactive Historian: Test Scenario in the Water Industry 4.0

Nicolae

Korodi

Silea

2019

Water

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“…Various approaches to advance with data the development of information intensive services (IIS) in public safety for the specific case of water resources management may be integrated today, such as water pollution control [24], [43], with information-based intelligence [44], stressing the role of digital technologies for public safety concerns [45], [29] in managing urban water sustainably [46]. To create, evaluate, and understand the general situation of data integration through IIS for water resource management and to apply Exploratory Data Analysis [40] for the assessment of critical situations in public safety, in this section we explain two general use cases on data collection in Cyber-Physical Systems (CPS).…”

Section: Review On Data Quality Evaluation In Cyber Physical Systemsmentioning

confidence: 99%

“…Therefore, it becomes mandatory to consider the digital potentialities for advancing public safety services with user-generated data, possibly developing complex services to emphasize hazardous environmental phenomena based on different digital tools [17], [43], [44], [16]. This type of digitization of information favors the creation of shared resource systems to conceptualize data, information, and knowledge as commons [87], [21].…”

Section: Review On Data Quality Evaluation In Cyber Physical Systemsmentioning

confidence: 99%

Managing Data, Information, and Technology in Cyber Physical Systems: Public Safety as a Service and its Systems

et al. 2019

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This paper introduces a unified representation for collaborative development of complex services in public safety to explain the infusion of digital technologies into the design of the community resilience processes with respect to the potential hazardous events. It aims at helping to understand how ICT-based knowledge may help stakeholders situated in various positions inside society to participate collaboratively to service development actions. It presents a roadmap to conceive, design, and operationalize the creation of digital artefacts to compound its supporting systems, including the digital one. This representation includes a way of describing the domain of interest to conceive complex services employing human-oriented development, a way of reasoning on the resilience processes complexity, using semantic reasoning along with the time series quality assurance (TSQA) solution ontology, and a way of developing data processing components as internal (technical) services in enterprise information systems to support the design of novel environmental monitoring digital services. A unified semantic reasoning-based approach to evaluate data quality in cyber-physical systems is described to exemplify the creation of a complex public service ecosystem that promotes collaborative knowledge sharing to formalize the domain expertise through the information intensive services. The TSQA ontology integrates knowledge from other domainspecific ontologies to define and share concepts designating observations acquired from sensors, quality issues, methods for detecting quality issues and correcting data, and tags applied to data objects to assure the data traceability. A semantic component that manages the TSQA ontology and the SWRL-encoded rules are introduced in the data acquisition module of a cyber-physical system application for environmental monitoring to solve a specific problem of data cleaning associated with the water resources management. This method is applicable to any time series of measured data.

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“…In general, water allocation from a reservoir can be considered a complex and nonlinear problem due to a large number of conditions and variables. However, from the past ten years, improvements have been made to reservoir rule curves to address complex problems using the optimization technique, which is widely studied [5,6], because it provides quantitative results consistent with the hydrological change situation, including its application in water allocation to reduce economic losses caused by pollution [7,8]. It can also be used as a tool for decision support systems (DSS) in finding the optimal land use in relation to groundwater vulnerability [9].…”

Section: Introductionmentioning

confidence: 99%

Optimal Reservoir of Small Reservoirs by Optimization Techniques on Reservoir Simulation Model

Sriworamas

Kangrang

Thongwan

et al. 2021

Advances in Civil Engineering

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Reservoir rule curves are essential rules for store activity. This investigation connected the Genetic Algorithm, Firefly Algorithm, Bat Algorithm, Flower Pollination Algorithm, and Tabu Search Algorithm associated with the store reproduction model to look through the ideal supply standard bends, utilizing the Huay Ling Jone and Huay Sabag supplies situated in Yasothorn Province, Thailand, as the contextual investigation. Memorable inflow information of the two repositories were utilized in this investigation, and 1,000 examples of engineered inflows of stores were utilized to recreate the repository activity framework for assessing the acquired principle bends as displayed as far as water circumstances. Circumstances of water lack and abundance water appeared as far as the recurrence extent and length. The outcomes demonstrated that GA, FA, BA, FPA, and TS associated with the reservoir simulation model could give the ideal principle bends which better moderate the drought and flood circumstances contrasted and current guideline bends.

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Optimization of Water Reservoir Operation to Minimize the Economic Losses Caused by Pollution

Cited by 7 publications

References 41 publications

Identifying Data Dependencies as First Step to Obtain a Proactive Historian: Test Scenario in the Water Industry 4.0

Identifying Data Dependencies as First Step to Obtain a Proactive Historian: Test Scenario in the Water Industry 4.0

Managing Data, Information, and Technology in Cyber Physical Systems: Public Safety as a Service and its Systems

Optimal Reservoir of Small Reservoirs by Optimization Techniques on Reservoir Simulation Model

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