Please use this identifier to cite or link to this item: http://dspace.iitrpr.ac.in:8080/xmlui/handle/123456789/1616
Title: Eigenfunctions and genetic algorithm based improved strategies for performance analysis and geometric optimization of a two-zone solar pond
Authors: Kumar, A.
Verma, S.
Das, R.
Issue Date: 11-Dec-2020
Abstract: In this paper, concept of a modified two-zone solar pond consisting lateral extraction from an extended length of convection free zone combined with thermoelectric generators for electrical power generation is proposed. In this work, a new transient-state analytical model to predict the performance of such a system is developed. Fully closed-form transient solution for performance analysis during extended length lateral heat extraction from solar ponds is not yet available in the literature. The presence of two source terms, one of which is solution dependent and mixed boundary conditions makes the present study complex to be solved analytically. The methodology based on the expansion of Eigenfunctions is proposed to predict temperature profiles within the solar pond having dual layer heat extraction. Using the temperature field, net energy output from the system for a specified period is obtained. The variation in power output and net energy for various cases of design and operating parameters during the maturation phase of the solar pond and after achieving the steady-state is analysed. The sensitivity of different operating and design parameters on the output of the system is also evaluated. Further, an inverse optimization analysis is also carried out to search for possible combinations of various design and operating parameters in the system towards meeting a specified net energy output from the thermoelectric generators. It was observed that using the inversely obtained set of parameters can significantly reduce the volume, base area, and total height of the solar pond concerning the existing convention.
URI: http://localhost:8080/xmlui/handle/123456789/1616
Appears in Collections:Year-2020

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