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Absorption heat pump parameter identification using a micro genetic algorithm

This paper investigates identification of key parameters in a control oriented dynamic model of an absorption heat pump used in a district heating system. Automatic identification or improvement of manually tuned parameters can speed up model development and improve the accuracy of estimation of, e.g., heat transfers in the system, which is important for optimization of the district heating plant operation. The heat transfers rely strongly on heat transfer coefficients and real time data series from the plant are used to identify these parameters. A micro genetic algorithm for global optimization is investigated as a candidate for automatic parameter identification, due to the sparsity of sensor measurement locations and the high degree of coupling in the complex nonlinear system. Results show that a micro genetic algorithm is well suited for the purpose and guidelines for potential improvement of the model is discussed. Finally, sensitivity of the heat transfers towards changes in the identified heat transfer coefficients is investigated.