Solar Absorption Chiller Optimization by Using Genetic Algorithms

The main propose of this research is providing a tool for suitable modeling, increase efficiency and decrease construction cost of solar absorption chiller. At first, the solar absorption chiller is modeled by the thermodynamic laws. Then, this model is converted to the new standard mathematical programming model with considering all technical and economic constrains. This mathematical model is optimized by Genetic algorithm (GA). After applying GA, optimized parameters of chiller heat exchanger designing and its electricity consumption are calculated. These parameters consist of heat exchanger effectiveness, heat transfer cross section area, heat transfer coefficient, efficiency of pump and motor. The effect of costs economic optimization is shown with comparing the optimum point and a system base case. It will be shown that for optimum point the total investment cost increases 2.0568% while the sum of destruction and loss exergy decreases 0.21% and annual cost decrease about 8.91% rather than base case. Coaling load of evaporator is related to an apartment with 50 m² Area in Tehran (case study).