Artificial Intelligence and Computational Methods in the Modeling of Complex Systems

Sosnowski, Marcin; Ščurek, Radomír

doi:10.3390/e23050586

Cited by 10 publications

(2 citation statements)

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“…All these activities are concise with the global scientific modeling trend, allowing better description and recognition of complex systems [16][17][18][19].…”

Section: Conflicts Of Interestmentioning

confidence: 99%

Novel Combustion Techniques for Clean Energy

2022

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“…All these activities are concise with the global scientific modeling trend, allowing better description and recognition of complex systems [16][17][18][19].…”

Section: Conflicts Of Interestmentioning

confidence: 99%

Novel Combustion Techniques for Clean Energy

2022

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“…In the last two decades, AI-based data modeling tools have presented a remarkable performance in developing engineering solutions and optimization strategies for large-scale industrial systems overcoming the limitations of mathematical modeling tools. − Our research group has also reported performance enhancement solutions developed on the component level, system level, and strategic level of a 660 MW coal power plant using advanced AI modeling tools and statistical techniques. ,, AI-based modeling and simulation algorithms can provide accurate results mined out of the high-dimensional and nonlinear interacting features of engineering systems, which can be reliably implemented in the running operation of energy systems . However, asymmetric and high-dimensional space of the data, development of efficient AI models and their validation, domain knowledge-backed experimental designs, and operating strategies are the challenges to be addressed carefully to exploit the true potential of data and AI algorithms.…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence Modeling-Based Optimization of an Industrial-Scale Steam Turbine for Moving toward Net-Zero in the Energy Sector

et al. 2023

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Augmentation of energy efficiency in the power generation systems can aid in decarbonizing the energy sector, which is also recognized by the International Energy Agency (IEA) as a solution to attain net-zero from the energy sector. With this reference, this article presents a framework incorporating artificial intelligence (AI) for improving the isentropic efficiency of a high-pressure (HP) steam turbine installed at a supercritical power plant. The data of the operating parameters taken from a supercritical 660 MW coal-fired power plant is well-distributed in the input and output spaces of the operating parameters. Based on hyperparameter tuning, two advanced AI modeling algorithms, i.e., artificial neural network (ANN) and support vector machine (SVM), are trained and, subsequently, validated. ANN, as turned out to be a better-performing model, is utilized to conduct the Monte Carlo technique-based sensitivity analysis toward the high-pressure (HP) turbine efficiency. Subsequently, the ANN model is deployed for evaluating the impact of individual or combination of operating parameters on the HP turbine efficiency under three real-power generation capacities of the power plant. The parametric study and nonlinear programming-based optimization techniques are applied to optimize the HP turbine efficiency. It is estimated that the HP turbine efficiency can be improved by 1.43, 5.09, and 3.40% as compared to that of the average values of input parameters for half-load, mid-load, and full-load power generation modes, respectively. The annual reduction in CO2 measuring 58.3, 123.5, and 70.8 kilo ton/year (kt/y) corresponds to half-load, mid-load, and full load, respectively, and noticeable mitigation of SO2, CH4, N2O, and Hg emissions is estimated for the three power generation modes of the power plant. The AI-based modeling and optimization analysis is conducted to enhance the operation excellence of the industrial-scale steam turbine that promotes higher-energy efficiency and contributes to the net-zero target from the energy sector.

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Heat and mass transfer prediction in fluidized beds of cooling and desalination systems by AI approach

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et al. 2023

Applied Thermal Engineering

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Artificial Intelligence and Computational Methods in the Modeling of Complex Systems

Abstract: Based on the increased attention, the Special Issue aims to investigate the modeling of complex systems using artificial intelligence and computational methods [...]

Cited by 10 publications

References 20 publications

Novel Combustion Techniques for Clean Energy

Novel Combustion Techniques for Clean Energy

Artificial Intelligence Modeling-Based Optimization of an Industrial-Scale Steam Turbine for Moving toward Net-Zero in the Energy Sector

Heat and mass transfer prediction in fluidized beds of cooling and desalination systems by AI approach

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