Optimum design method for zeolite heat storage reactors

doi:10.19799/j.cnki.2095-4239.2024.0862

Abstract

Abstract:

Zeolite adsorption heat storage technology offers several advantages, such as high energy storage density, low operating temperatures, and minimal heat loss during long-term storage, making it a promising solution for thermal energy applications in buildings. The thermal output performance of the reactor, a critical component of adsorption heat storage systems, is significantly influenced by its structural dimensions and operating conditions. However, the influence of the reactor design variables (structural parameters and operating conditions) on thermal output performance remains unclear, limiting effective optimization. In this study, a numerical model of an adsorption heat storage reactor was developed, and the thermal output optimization objectives were proposed. Sensitivity analysis was performed to evaluate the effects of the key design variables on the optimization objectives. The findings revealed that inlet air temperature and humidity significantly influenced outlet temperature, with absolute humidity being the main factor affecting heat release per unit volume. The airflow rate primarily affects the response time of the thermal output. Based on these findings, this study further examines the relationships between the design variables and optimization objectives, establishing the priority of the reactor's design variables. Therefore, a comprehensive design approach and process for heat storage reactors was proposed.

Key words: adsorption heat storage, reactor optimization objectives, numerical simulation, design method

CLC Number:

TK 02

Liming WANG, Mengqi WANG, Yimo LUO, Gesang YANG, Yuanyuan WANG, Lexiao WANG. Optimum design method for zeolite heat storage reactors[J]. Energy Storage Science and Technology, 2024, 13(12): 4272-4281.

Figures/Tables 17

Fig. 1

Table 1

Properties of Zoelite-13X"

物理量	名称	设定值	物理量	名称	设定值
孔隙率	$ε$	0.39	吸附热	$Δ$ H	1800 kJ/kg
沸石密度	$ρ p$	690 kg/m³	吸附平衡常数	b	1.5
沸石比热容	$c p, p$	1080 J/(kg·K)	饱和吸附量	q_s	15 mol/kg
沸石导热系数	$k p$	3.3 W/(m·K)	扩散系数	D_s0	2.55 $×$ 10^-6 m²/s
流体比热容	$c p, f$	1005 J/(kg·K)	平均颗粒直径	d_p	4 mm
流体密度	$ρ f$	1.29 kg/m³	反应活化能	E	28035 J/mol

Table 1

Table 2

Fig. 2

Fig. 3

Table 3

Fig. 4

Fig. 5

Table 4

Fig. 6

Fig. 7

Fig. 8

Fig. 9

Fig. 10

Fig. 11

Table 5

Correlation between design variables and optimization objectives"

性能目标	设计变量
性能目标	$T i n$	AH_in	$v i n$	L
$t s t a b l e$	0	-1	-1	1
T_max	1	1	0	0
$∆ T a v e$	0	1	0	0
$E d$	0	1	0	1

Table 5

Fig. 12

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组别	a₁	a₂	MAE1 (参考下组)	MAE2 (参考mesh5)
mesh1	58	9	3.92 K	8.07 K
mesh2	116	18	2.54 K	4.20 K
mesh3	290	45	1.12 K	1.69 K
mesh4	580	90	0.56 K	0.56 K
mesh5	1160	180	—	—

设计变量	起始值	步长	终止值
模拟工况/组	720	—	—
反应器长度L/m	0.20	0.05	0.3
入口空气流速v_in/(m/s)	0.2	0.1	0.5
入口空气温度T_in/℃	15	5	60
入口相对湿度RH_in/%	40	10	90

入口温度/℃	入口相对湿度	绝对湿度/ (g/kg)	稳定时间/min	出口平均温度/℃	出口平均温升/℃
45	0.9	57.90	55	197.91	152.91
50	0.7	57.95	56	200.48	150.48

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