Mathematical model of a supercritical power boiler for simulating rapid changes in boiler thermal loading

Taler, Jan; Zima, Wiesław; Ocłoń, Paweł; Grądziel, Sławomir; Taler, Dawid; Cebula, Artur; Jaremkiewicz, Magdalena; Korzeń, Anna; Cisek, Piotr; Kaczmarski, Karol; Majewski, Karol

doi:10.1016/j.energy.2019.03.085

Cited by 45 publications

(21 citation statements)

References 25 publications

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“…Figure 6 depicts the temperature measured at node (4,4,1) on the rear heated surface, the temperature calculated at node (4,4,2) at distance z = Δz from the insulated surface, and the calculated and experimental temperature values at node (4,4,3) placed on the exposed sprayed surface. The calculated and measured temperature at node (4,4,3) as well as in other points, exhibited a very good coincidence. The results shown in Figure 6 were obtained by dividing the thickness of the plate into three control volumes.…”

Section: Resultssupporting

confidence: 63%

“…The heat flux at node (4,4,3) was estimated using three formulas (Equations (7)-(9)). The time changes of the heat flux and heat transfer coefficient determined on the sprayed surface at node (4,4,3) are illustrated in Figure 7.…”

Section: Resultsmentioning

confidence: 99%

“…The slab was made of St3S steel with the following dimensions: H1 = 0.8 m, H2 = 0.8 m, and s = 0.035 m. The finite volumes, in the middle of which the temperature is measured or determined, lying in different planes z are marked with different colors (Figures 2-4). With the use of the computational algorithm described above, the temperature at points (4,5,3), (3,4,3), (4,4,3), (5,4,3), and (4,3,3) is found.…”

Section: Verification Of the Methods By Experimental Testsmentioning

confidence: 99%

“…Then, from these equations, the time-dependent temperatures in 13 nodes lying in the plane z = ∆z (Figure 3b The finite volumes, in the middle of which the temperature is measured or determined, lying in different planes z are marked with different colors (Figures 2-4). With the use of the computational algorithm described above, the temperature at points (4,5,3), (3,4,3), (4,4,3), (5,4,3), and (4,3,3) is found. To determine the heat transfer coefficient at node (4,4,3) ( Figures 3c,d), located on the cooled plate surface, the normal component of the heat flux at the same point has been calculated as follows:…”

Section: Of 13mentioning

confidence: 99%

“…Thermal power plants must, therefore, be adapted to fast start-ups, shutdowns, and rapid load changes. Cyclical operation of the power unit as well as start-ups and shutdowns cause high thermal stresses in thick-walled pressure elements, which can significantly reduce the service life of these elements [1][2][3]. The thermal stresses are very much influenced by the heat transfer coefficient on the surface where the heat transfer takes place.…”

Section: Introductionmentioning

confidence: 99%

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Online Determining Heat Transfer Coefficient for Monitoring Transient Thermal Stresses

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2020

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This paper proposes an effective method for determining thermal stresses in structural elements with a three-dimensional transient temperature field. This is the situation in the case of pressure elements of complex shapes. When the thermal stresses are determined by the finite element method (FEM), the temperature of the fluid and the heat transfer coefficient on the internal surface must be known. Both values are very difficult to determine under industrial conditions. In this paper, an inverse space marching method was proposed for the determination of the heat transfer coefficient on the active surface of the thick-walled plate. The temperature and heat flux on the exposed surface were obtained by measuring the unsteady temperature in a small region on the insulated external surface of a pressure component that is easily accessible. Three different procedures for the determination of the heat transfer coefficient on the water-spray surface were presented, with the division of the plate into three or four finite volumes in the normal direction to the plate surface. Calculation and experimental tests were carried out in order to validate the method. The results of the measurements and calculations agreed very well. The computer calculation time is short, so the technique can be used for online stress determination. The proposed method can be applied to monitor thermal stresses in the components of the power unit in thermal power plants, both conventional and nuclear.

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Section: Resultssupporting

confidence: 63%

Section: Resultsmentioning

confidence: 99%

Section: Verification Of the Methods By Experimental Testsmentioning

confidence: 99%

Section: Of 13mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Online Determining Heat Transfer Coefficient for Monitoring Transient Thermal Stresses

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2020

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Assessing the eco-environmental aspects of fossil fuels-based units substitution of Point Aconi thermal power plant by green-based energies: a case study of Canada

Amiri,

Shaterabadi,

Ben-Brahim

et al. 2024

Electr Eng

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Canada possesses significant potential in harnessing renewable energy from its vast and diverse geography, which can generate clean electricity. This paper presents a model that replaces fossil fuels used in a proposed thermal power plant in Point Aconi, Nova Scotia, with photovoltaic and wind turbine units based on the region’s climate conditions. The research results are based on evaluating multiple thermal power plants worldwide and examining various wind turbines and PV panels from different companies to ensure accuracy. The chosen units that best suit the location’s geographical and biological conditions, transmission, and operation costs demonstrate that the power plant currently consumes approximately 47 tons of coal and petroleum coke per hour. Replacing these materials with the proposed green units makes it possible to reduce environmental pollution by eliminating almost 165 tons of CO2 and other pollutants per hour while increasing the plant’s efficiency and independence from fossil fuel price variations. The presented structure’s ROI is approximately 20 years, which is reasonable compared to the economic and environmental benefits of utilizing such a structure and converting the thermal power plant to green units.

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Attention mechanism-based deep learning for heat load prediction in blast furnace ironmaking process

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Mathematical model of a supercritical power boiler for simulating rapid changes in boiler thermal loading

Cited by 45 publications

References 25 publications

Online Determining Heat Transfer Coefficient for Monitoring Transient Thermal Stresses

Online Determining Heat Transfer Coefficient for Monitoring Transient Thermal Stresses

Assessing the eco-environmental aspects of fossil fuels-based units substitution of Point Aconi thermal power plant by green-based energies: a case study of Canada

Attention mechanism-based deep learning for heat load prediction in blast furnace ironmaking process

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