Exergy Analysis and Optimization of Series and Parallel Flow Configurations of Vapor Absorption Chiller

Currently, increased clean energy demand due to rapid industrialization and population growth is the main challenge of the world. This can be achieved either by energy efficiency improvement for both the house hold appliances and industrial processes or by utilizing alternative energy resources or fuels. Energy efficiency of an industrial plant may be improved by optimizing its design and operation. Utilization of waste heat may also be an important option for the energy efficiency improvement of the industrial processes. Vapor absorption chillers (VAC) commonly known as absorption refrigeration system (ARS) can utilize the low quality energy or waste heat (which otherwise may have been wasted) as compared to the conventional vapor compression cycles (VCC). VCC require large amount of electricity for compression of the refrigerant. Furthermore, other benefits of VAC over VCC include the use of safe working fluids, low maintenance cost and low noise pollution. Though, low efficiency of VAC is the major issue associated with it. Therefore, the efficiency improvement becomes an importance factor and it can be achieved by analyzing and optimizing the various process configurations of the cycle. In this work, performance of VAC is specified as exergy efficiency instead of conventional coefficient of performance approach. Both the series and parallel flow configurations have been considered. Various operating parameters such as temperatures of all the units of both configurations have been optimized. The thermodynamic model was developed in MATLAB using the best available correlations. A global optimization algorithm i.e., Genetic Algorithm has been used to optimize the operating conditions. Performance of VAC is improved substantially and is shown in terms of exergy efficiency. The effect of variations of effectiveness of heat exchangers and the used of various types of heating sources will also be considered in near future.