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.
Highlights
The transformation of global economies towards the effective use of energy sources and the reduction of pollution emissions, including greenhouse gases, is becoming one of key challenges facedEnergies 2020, 13, 3338; doi:10.3390/en13133338 www.mdpi.com/journal/energiesEnergies 2020, 13, 3338 by our civilization
We focused on the sectors processes as an innovation and progress in improving energy efficiency of smart cities
We focused of critical urbanofinfrastructure, in particular the in useparticular of algorithmic models based on artificial on the sectors critical urbanincluding infrastructure, including the use of algorithmic models intelligence implemented in control systems
Summary
The transformation of global economies towards the effective use of energy sources and the reduction of pollution emissions, including greenhouse gases, is becoming one of key challenges facedEnergies 2020, 13, 3338; doi:10.3390/en13133338 www.mdpi.com/journal/energiesEnergies 2020, 13, 3338 by our civilization. With respect to power generation sector, an important aspect of the performance of any energy system is to ensure balance between the demand and the production of energy carriers when we are confronted with conditions or factors destabilizing its proper functioning. Such factors involve, for example, power supply fluctuations of renewable energy sources, failures of networks or generators, changes in energy demand, etc. By the application of numerical modeling, we can develop systems based on the knowledge of complex solutions, processes and installations in a relatively short time It is important in the context of process optimization that requires complex calculations for one specific case (building real models for each solution variant is impossible for technical reasons). Models of this type are used in each of the fields of power generation and environmental engineering, ranging from simulation of individual devices, through designs of power systems, such as power plants, to technical and social models of entire systems for a region
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