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Open AccessArticle

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

1
Department of Water and Wastewater Engineering, Silesian University of Technology, Konarskiego 18, 44–100 Gliwice, Poland
2
Department of Environmental Technologies, Cracow University of Technology, Warszawska 24, 31–155 Cracow, Poland
*
Author to whom correspondence should be addressed.
Energies 2020, 13(13), 3338; https://doi.org/10.3390/en13133338
Received: 9 May 2020 / Revised: 12 June 2020 / Accepted: 29 June 2020 / Published: 30 June 2020
(This article belongs to the Special Issue Energy Economics and Innovation of Smart Cities)
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. View Full-Text
Keywords: smart cities; smart computational solution; artificial intelligence; energy economics; control systems; energy efficiency of technological processes; wastewater treatment system; fuel from wastes smart cities; smart computational solution; artificial intelligence; energy economics; control systems; energy efficiency of technological processes; wastewater treatment system; fuel from wastes
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Gaska, K.; Generowicz, A. 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 2020, 13, 3338.

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