Abstract:
The world is going through a fuel crisis, and a lot of resources are spent on it to produce electricity and hence refrigeration. Therefore, it has become necessary to adopt energy-efficient technologies, such as absorption refrigeration system (ARS), that uses a low-grade form of energy and hence not only saves fuel but also stops the wastage of heat that could go to the atmosphere and pollute it. During optimization of ARS, researchers have previously used constant values of heat transfer coefficient, but as decision variables change during optimization, values of heat transfer coefficient don’t remain constant as they depend on fluid properties like density, temperature & pressure, etc., flow properties like Reynold number and geometric properties. So, a constant value will give inaccurate results during optimization when the optimizer constantly changes decision variables to go towards a global minima. The objective of this work was to optimize operating conditions and areas, by using empirical correlations found in the literature to minimize Total Annual Cost (TAC). For this purpose, a 50-kW evaporator is considered for both series and parallel configurations of a double effect ARS system. A thermo-economic model is developed in MATLAB and optimization is done using a Genetic Algorithm (GA). Results show that TAC is reduced in both cases after the integration of correlations, which implies that although constant values give a good initial guess, correlations affect the process variables a lot.
Page(s):
0-0
DOI:
DOI not available
Published:
Journal: Sixth International Conference on Sustainability in Process Industries (SPI) 19-20 Octover 2022 (Book of Abstracts), Volume: 0, Issue: 0, Year: 2022