THERMAL STRATIFICATION IN WATER STORAGE TANKS
J.E.B. Nelson and S. Srinivasamurthy
Refrigration and air-conditioning laboratory,
Department of Mechanical Engineering, Indian Institute of Technology Madras
Chennai - 600 036, India
Department of Chemical Engineering, Indian Institute of Technology Madras
Chennai - 600 036, India
The concept of energy storage is recognized for achieving energy conservation and management. The need to use an energy storage system arises whenever there is a time or rate mismatch between times of available energy and its demand. Thermal energy storage devices are essentially needed in devices working on solar energy due to intermittent and variable insolation of solar energy. There are several studies on various storage techniques reported in the literature both for storing heat and cold. The energy can be stored in the form of sensible heat or latent heat. The present paper describes a study of sensible storage in stratified storage tanks with water as storage medium. Thermal stratification is achieved due to density difference between hot or warm water and cold water. The interface separating the hot and cold water is a narrow zone (thermocline zone) in which there is a large temperature gradient. The thickness of this zone is a measure of thermal degradation. The expansion of this thermocline zone leads to increased thermal degradation. The water heated in the solar collector flows over the cold water in the storage tank. Water is withdrawn for use from the top of the storage tank. In both cases the thermal degradation of the hot water should be a minimum. The recycled water is admitted into the storage tank from the bottom of the storage tank. It should be supplied to the solar collector with the least rise in temperature to achieve high collector efficiency.
Similarly the concept of energy storage is useful in the air conditioning of large commercial buildings to shift the electric demand from peak to off peak night periods. The cooling capacity produced during the off-peak hours and nights is stored and used for meeting the cooling load demands during the peak periods of electric utility or to meet cooling load demands of the additional spaces. In both cases either the heating or cooling capacity degrades due to (i) heat conduction in the tank across the thermocline (ii) heat exchange between the stored medium and the ambient (iii) energy transfer between the hot and cold water through the conducting wall (axial wall conduction) and (iv) mixing introduced during the admission of fluid at the top and bottom of the storage tank.
Several investigators have described one-dimensional models in the literature. One of the earliest models is the TRANSYS model developed by Klein et al. in 1978 and updated periodic-ally. This model is extensively used in solar thermal simulation. In 1993 Al-Najem et al. used a 2-D heat conduction model. Both these neglect axial wall conduction and heat exchange of the stored fluid with the ambient. Wildin and Truman in 1989 formulated at 1-D heat conduction model in the fluid and 2-D heat conduction model in the wall. Many of the models in the literature neglect the effect of mixing at inlet and axial wall conduction.
In this paper a numerical model suitable for studying the performance of either the hot or chilled water storages is presented. The model accounts for various parameters such as aspect ratio, tank length to tank wall thickness ratio, axial wall conduction, thermo-physical properties of the tank material and insulation, mixing effects due to inflow and outflow of the fluid in the tank. The model is validated with the published numerical and experimental results of both heat and cool storages at limiting conditions. The special feature of this model is that the mixing is quantified in terms of dimensionless parameters which account for various factors contributing to mixing. This eliminates the empirical constants being used at present to match the numerical and experimental results. The mixing coefficient is expressed in terms of Richardson and Reynolds numbers.
Figure 1: Comparison of model with experimental data.
Keywords: Thermal storage cool storage thermocline 1-D model degradation