Numerical modelling of distribution the discharged heat water from thermal power plant on the aquatic environment
Alibek Issakhov
Citation: AIP Conference Proceedings 1738, 480025 (2016); doi: 10.1063/1.4952261 View online: http://dx.doi.org/10.1063/1.4952261
View Table of Contents: http://scitation.aip.org/content/aip/proceeding/aipcp/1738?ver=pdfcov Published by the AIP Publishing
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Numerical Modelling of Distribution the Discharged Heat Water from Thermal Power Plant on the Aquatic
Environment
Alibek Issakhov
al-Farabi Kazakh National University, Almaty, 050040 Kazakhstan e-mail:alibek.issakhov@gmail.com
Abstract. The paper presents a mathematical model of distribution the discharged heat water from thermal power plant under various operational capacities on the aquatic environment. It was solved by the Navier-Stokes and temperature equations for an incompressible fluid in a stratified medium were based on the splitting method by physical parameters which approximated by the finite volume method. The numerical solution of the equation system was divided into four stages. At the first step it was assumed that the momentum transfer carried out only by convection and diffusion. While the intermediate velocity field was solved by 5-step Runge-Kutta method. At the second stage, the pressure field was solved by found the intermediate velocity field. Whereas Poisson equation for the pressure field was solved by Jacobi method. The third step assumes that the transfer was carried out only by pressure gradient. Finally the fourth step of the temperature equation was also solved as motion equations, with 5-step Runge-Kutta method. The algorithm was parallelized on high-performance computer. The obtained numerical results of three-dimensional stratified turbulent flow were compared with experimental data. What revealed qualitatively and quantitatively approximately the basic laws of hydrothermal processes occurring in the reservoir-cooler.
Keywords: stratified medium, Navier-Stokes equation, operational capacities of thermal power plant, finite volume method, Runge-Kutta method, thermal discharge.
PACS: 47.10.ad; 47.11.Df; 44.10.+i
INTRODUCTION
Environment - the basis of human life, and the energy generated - is the basis of the modern world. However, the production of electricity adversely impact on our environment. Energy is the basis of different types of power plants.
Electricity production in thermal power plants (TPP), hydropower plants (HPP) and nuclear power plants (NPP) is associated with adverse effects on the environment. Interaction energy and the environment has acquired new features, extending the influence of heat on the rivers and lakes. Previously, the impact of TPP or NPP on the environment was not considered, as the main purpose was to obtain the electricity. Electricity production technology in the power plant is connected with a lot of heat emission to the environment. The negative impact of energy on the environment is becoming an important issue, since the pollution each year increases. Today it is important to find the best sources of electricity. One of such kind of source is the thermal power plants. TPP is divided into condensing power plant (CPP), intended only to generate electricity, and thermal power central (TPC), which produces electricity energy and heat in the form of hot water or steam. District large CPPs are called state district power plants (SDPP). All power has a negative impact on the environment.
MATHEMATICAL MODELLING
Technical supply of Ekibastuz SDPP-I was carried out on the back of the circuit with cooling circulating water. The surface of the reservoir is located at the 158.5 m of the sea level, the area is 19.6km2, the maximum size is 4 x 6 km, an average depth - 4.6 m, a maximum depth - 8.5 m from the water intake, the volume of the reservoir is 80 millionm3. In the reservoir used combined type of selective intake and discharge. Intake water enters the pre-channel mixer, and from there through the filter dam uniformly enters the reservoir-cooler. Water intake is made at a distance of 40 m from the dam at a depth of 5 m. Project water consumption is 120m3/sec, and the actual consumption varies depending on the operational capacities of Ekibastuz SDPP-1 within 80-120m3/sec. In reservoir - coolers spatial temperature change is small (it usually does not exceed 200C). Corresponding change in the density is much smaller
than the magnitude of the water density. Therefore, stratified flow in the reservoir - cooler can be described by the equations in the Boussinesq approximation, i.e. in the motion equations a variable of water density can be replaced by some constant everywhere except the members representing the Archimedean force. In view of the above, the starting point for describing the flow in the laminar regime is the Navier - Stokes and temperature equations [1], [2], [3], [16], [17], [7], [8], [9], [10], [11]. In this paper stratification development is taken into account, which is added to the right hand side of motion equation and have the following form:
∂ui
∂t +∂ujui
∂xj
=−∂p
∂xi
+ν ∂
∂xj
(∂ui
∂xj
)
+δi3βg(T−T0) (1)
∂uj
∂xj
=0 (2)
∂T
∂t +∂ujT
∂xj
= ∂
∂xj
( χ∂T
∂xj
)
(3) In the general case, the system of equations (1) - (3) in such way can not be solved because a turbulent model needs to be applied. Large eddy simulation method [13] is used as the turbulent model. Averaged by Favre [12] the system of equations (1) - (3).
NUMERICAL ALGORITHM
Splitting scheme by the physical parameters is used to solve (1) - (3) with Favre average, which was proposed by Chorin [6] and used in [5]. The finite volume method [12] is used for discretization. At the first step it is assumed that the momentum transfer carried out only by convection and diffusion. Intermediate velocity field is solved by is 5-step Runge - Kutta method [14], [15]. At the second stage, the found intermediate velocity field, forms pressure field. Poisson equation for the pressure field is solved by Jacobi method [12]. The third step assumes that the transfer is carried out only by pressure gradient [5], [6]. The temperature field is solved like the velocity field by 5-step Runge - Kutta method. The numerical algorithm is parallelized on high-performance system and a block partitioning computational domain is used for parallelization algorithm.
Initial and boundary conditions were given to solve the problems. The initial conditions are given in the following form for the velocity and temperature: uj =0,(j=1,2,3), T =T0. The boundary conditions for the velocity at the bottom and border side are set by no-slip condition, and for the temperature - adiabatic conditions. On the surface boundary conditions for the velocity is given by the following form:ν∂∂ux3j =τjua, (j=1,2,3), where τj
– components of wind stress,ua– component of the wind speed.
Moreover additional boundary conditions are also used for the velocity and temperature on the border side of the discharge, depending on the operational capacities of Ekibastuz SDPP-1. At the inlet and discharged area the velocity distribution profile is taken from empirical data for a certain operational capacities of Ekibastuz SDPP-1. Temperature is taken from Ekibastuz SDPP-1 by observed data in the intake and discharged area.
THE RESULTS OF NUMERICAL MODELLING
The quadrangular mesh used for this numerical study, which is shown in Figure 1(a). For this simulation used totally 73 710 elements and 15 386 nodes. The mesh size was varied from approximately 6 m in the intake and discharged area and coast, to approximately 12 m in the middle of reservoir-cooler. To simulate temperature stratification accurately in the intake and discharged area 16 uniform nodes were specified in vertical coordinate system. The aim of selection of the mathematical model and development of the numerical model was to study the vertical inhomogeneities in stratified reservoirs. It is necessary to do numerical simulations and to compare the results with experimental data in order to check the correctness of the numerical algorithm and the possibility of their further application. Note that we have data only by the vertical distribution of temperature of Ekibastuz SDPP-1 Zhyngyldy lake. However, these measurements were carried out in 2010 and for the operational capacity of 200 MW. So the verification of the models was carried out on these experimental data. It is noted that, despite the different weather conditions in different years, the vertical thermal structure of the water does not undergo changes cardinally. Therefore, at the first phase, the mathematical
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model was validated by experimental data measured in 2010. The results of numerical simulations of the temperature distribution along the depth of the reservoir and the experimental data for the operational capacity of 200 MW for point A on the reservoir-cooler, which are presented in figure 1(b) is shown. The calculated spatial contour and the isolines of the temperature distribution at different times after the start of Ekibastuz SDPP-1 on the surface of water for the operational capacities 200 MW, 800 MW are shown on the figure 2 (a, b).
FIGURE 1. Computational grid for Ekibastuz SDPP-1 and Comparison of experimental data with simulation data for the operational capacity 200 MW at the point A.
FIGURE 2. The spatial contour and isolines of the temperature distribution at 1, 12 h. after the start of Ekibastuz SDPP-1 on the surface of water for the operational capacities 200 MW and 800 MW.
These results show that the temperature distribution is spread over a large area of the reservoir-cooler. And also from the same figure it can be seen that an increase of thermal power plant’s operational capacity, the area of thermal effect becomes directed in the same way, and leads to water warming of only one part of the reservoir, which has a negative effect on the performance of TPP. This increase of the operational capacities of Ekibastuz SDPP-1 of the reservoir-cooler is not effective, what causes the heating the western part of the reservoir, and the rest is not involved in the cooling of the heated water from the thermal power plant that is resulted in the rapid warming of reservoir-cooler. Thus, the advanced three-dimensional model of a stratified turbulent flow reveals qualitatively and
quantitatively approximately the basic laws of hydrothermal processes in the aquatic environment. Figure 1 (b) of the drawings show that the numerical results agree with the experimental data. A difference in the upper layers can be explained by variations in weather conditions at various times of the day. Models allow us to determine the qualitative vertical structure, the position of the transition zone for the temperature values at the lower and upper layers. Note that mixing occurs under the influence of turbulence and mixing have a significant effect on the flow. The picture of the wind currents depends on the strength of the wind, stratification and reservoir geometry.
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