화학공학소재연구정보센터
Przemysl Chemiczny, Vol.99, No.11, 1655-1659, 2020
Machine learning methods to optimize plate heat exchanger in a hybrid photovoltaic-thermal collector
The method for optimization of the geometric structure of the plate heat exchanger and the water flow rate by means of the heuristic machine learning algorithm with the use of exergy analysis was presented. The simulation was performed for a polycrystalline photovoltaic panel with a capacity of 250 W. Its electrical efficiency was increased by 29-34%.