Thermal Science 2019 Volume 23, Issue Suppl. 4, Pages: 1053-1063
https://doi.org/10.2298/TSCI19S4053K
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An adaptive neuro-fuzzy model of a re-heat two-stage adsorption chiller
Krzywanski Jaroslaw (Faculty of Mathematics and Natural Sciences, Jan Dlugosz University in Czestochowa, Czestochowa, Poland)
Grabowska Karolina (Faculty of Mathematics and Natural Sciences, Jan Dlugosz University in Czestochowa, Czestochowa, Poland)
Sosnowski Marcin (Faculty of Mathematics and Natural Sciences, Jan Dlugosz University in Czestochowa, Czestochowa, Poland)
Zylka Anna (Faculty of Mathematics and Natural Sciences, Jan Dlugosz University in Czestochowa, Czestochowa, Poland)
Sztekler Karol (Faculty of Energy and Fuels, AGH University of Science and Technology, Cracow, Poland)
Kalawa Wojciech (Faculty of Energy and Fuels, AGH University of Science and Technology, Cracow, Poland)
Wojcik Tadeusz (Faculty of Energy and Fuels, AGH University of Science and Technology, Cracow, Poland)
Nowak Wojciech (Faculty of Energy and Fuels, AGH University of Science and Technology, Cracow, Poland)
Since the adsorption chillers do not use primary energy as driving source the
possibility to employ low temperature waste heat sources in cooling energy
production receives nowadays much attention of the industry and science
community. However, the performance of the thermally driven adsorption
systems is lower than that of other heat driven heating/cooling systems. Low
coefficients of performance are one of the main disadvantages of adsorption
coolers. It is the result of a poor heat transfer coefficient between the
bed and the immersed heating surfaces of a built-in heat exchanger system.
The purpose of this work is to study the effect of thermal conductance
values of sorption elements and evaporator as well as other design
parameters on the performance of a re-heat two-stage adsorption chiller.
One of the main energy efficiency factors in cooling production, i. e.
cooling capacity for wide-range of both design and operating parameters is
analyzed in the paper. Moreover, the work introduces artificial
intelligence approach for the optimization study of the adsorption cooler.
The ANFIS was employed in the work. The increase in both the bed and
evaporator conductance provides better performance of the considered
innovative adsorption chiller. The highest obtained value of cooling
capacity is 21.7 kW and it can be achieved for the following design and
operational parameters of the considered re-heat two-stage adsorption
chiller: Msorb = 40 kg, t = 1300 s, T = 80ºC, Csorb/Cmet = 50, hAsorb =
4000 W/K, hAevap = 4000 W/K.
Keywords: overall thermal conductance, combined cooling, heating and power, artificial intelligence, low temperature heat sources, ANFIS, adsorption chiller, reheat two-stage, bio-inspired modeling