Optimization of Solar Absorption Chillers by Differential Evolution Algorithm Method

Absorption chillers as cooling machines use thermal energy instead of electrical energy to produce cold. Therefore, solar chillers can be used as appropriate alternatives for gas and evaporative coolers which have higher electricity consumption. Solar energy in such devices decreases the expenses of fuel greatly. The present paper utilizes genetic algorithm (GA) for the problem of optimal chiller load (OCL). The problem of Lagrange method is that it lacks convergence in low demands, while (GA) does not. In fact, using part load ratio (PLR) and the operators of genetic algorithm, cause to obtain results with higher speed and accuracy. The present paper by modeling and optimization using differential evolution algorithm method by MATLAB software, presents the layout and arrangement of the absorption chillers in a building, assuming that the energy needed for balancing the temperature inside is specified, as a result the most optimal condition is obtained that indicates the best energy consumption by the chillers.