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SMART Computational Solutions for the Optimization of Selected Technology Processes as an Innovation and Progress in Improving Energy Efficiency of Smart Cities—A Case Study

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  • Krzysztof Gaska

    (Department of Water and Wastewater Engineering, Silesian University of Technology, Konarskiego 18, 44–100 Gliwice, Poland)

  • Agnieszka Generowicz

    (Department of Environmental Technologies, Cracow University of Technology, Warszawska 24, 31–155 Cracow, Poland)

Abstract

The paper presents advanced computational solutions for selected sectors in the context of the optimization of technology processes as an innovation and progress in improving energy efficiency of smart cities. The main emphasis was placed on the sectors of critical urban infrastructure, including in particular the use of algorithmic models based on artificial intelligence implemented in supervisory control systems (SCADA-type, including Virtual SCADA) of technological processes involving the sewage treatment systems (including in particular wastewater treatment systems) and waste management systems. The novelty of the presented solution involves the use of predictive diagnostic tools, based on multi-threaded polymorphic models supporting decision making processes during the control of a complex technological process and objects of distributed network systems (smart water grid, smart sewage system, smart waste management system) and solving problems of optimal control for smart dynamic objects with logical representation of knowledge about the process, the control object and the control itself, for which the learning process consists of successive validation and updating of knowledge and the use of the results of this updating to make control decisions. The advantage of the proposed solution in relation to the existing ones lies in the use of advanced models of predictive diagnostics, validation and reconstruction of data, implemented in functional tools, allowing the stabilization of the work of technological objects through the use of FTC technology (fault tolerant control) and soft sensors, predictive measurement path diagnostics (sensors, transducers), validation and reconstruction of measurement data from sensors in the measuring paths in real time. The dedicated tools (Intelligent Real Time Diagnostic System − iRTDS) built into the system of a hierarchical, multi-threaded control optimizing system of SCADA system allow to obtain advanced diagnostics of technological processes in real time using HPC technology. In effect of the application of the proprietary iRTDS tool, we obtain a significant rise of energy efficiency of technological processes in key sectors of the economy, which in global terms, e.g., urban agglomeration, increases the economic efficiency.

Suggested Citation

  • Krzysztof Gaska & Agnieszka Generowicz, 2020. "SMART Computational Solutions for the Optimization of Selected Technology Processes as an Innovation and Progress in Improving Energy Efficiency of Smart Cities—A Case Study," Energies, MDPI, vol. 13(13), pages 1-41, June.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:13:p:3338-:d:378311
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    References listed on IDEAS

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    Cited by:

    1. Tatiana Tucunduva Philippi Cortese & Jairo Filho Sousa de Almeida & Giseli Quirino Batista & José Eduardo Storopoli & Aaron Liu & Tan Yigitcanlar, 2022. "Understanding Sustainable Energy in the Context of Smart Cities: A PRISMA Review," Energies, MDPI, vol. 15(7), pages 1-38, March.
    2. Anna Gronba-Chyła & Agnieszka Generowicz & Paweł Kwaśnicki & Dawid Cycoń & Justyna Kwaśny & Katarzyna Grąz & Krzysztof Gaska & Józef Ciuła, 2022. "Determining the Effectiveness of Street Cleaning with the Use of Decision Analysis and Research on the Reduction in Chloride in Waste," Energies, MDPI, vol. 15(10), pages 1-11, May.
    3. Adrian Czajkowski & Agata Wajda & Nikolina Poranek & Shubhangi Bhadoria & Leszek Remiorz, 2022. "Prediction of the Market of End-of-Life Photovoltaic Panels in the Context of Common EU Management System," Energies, MDPI, vol. 16(1), pages 1-15, December.
    4. Olga Pilipczuk, 2020. "Sustainable Smart Cities and Energy Management: The Labor Market Perspective," Energies, MDPI, vol. 13(22), pages 1-24, November.

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