固体氧化物电解池时空分布式参数建模

doi:10.3969/j.issn.2097-0706.2024.07.007

摘要/Abstract

摘要：

固体氧化物电解池（SOEC）在高温环境下运行，内部存在复杂的热电相互耦合，温度、电压的控制对电堆平稳、安全运行至关重要。针对电堆复杂非线性、时空分布的特点，基于时空最小二乘支持向量机（ LS-SVM）构建了SOEC温度、电压时空分布模型，采用一个核函数来描述电堆流道方向不同位置的空间相关性，采用动态回归方程描述电堆温度、电压分布的时间特性。通过Simulink构建SOEC机理仿真模型，生成样本数据来对时空分布模型进行训练并测试。仿真结果表明该模型能够准确预测SOEC温度、压力在时间及空间维度的分布，具有较优的泛化能力，可为电解系统优化与控制提供参考。

关键词: 固体氧化物电解池, 温度控制, 时空LS-SVM, 分布式动态预测模型, 电解系统, 电解制氢

Abstract:

There are complex thermoelectric couplings in solid oxide electrolysis cells （SOEC）operating under high temperature environment. Thus， temperature control and voltage control are crucial to the stable and safe operation of SOEC stacks. In view that SOEC stacks are complex， nonlinear and spatiotemporal distributed systems， a spatiotemporal distributed model for the temperature and voltage of an SOEC is constructed based on the spatiotemporal least square support vector machine（LS-SVM）. A kernel function is adopted to represent the spatial correlations at different locations along the flow channel， and dynamic regression equation is used to represent the temporal features of the temperature and voltage of the SOEC stack. A mechanism model of the SOEC stack is established in Simulink to obtain the sample data，which are used for the training and testing of the spatiotemporal distributed model. The simulation results show that the developed model can effectively predict the spatiotemporal distributions of the temperature and voltage in SOEC and has an excellent generalization ability， which can guide the further optimization and control of electrolysis cells.

Key words: solid oxide electrolysis cell, temperature control, spatiotemporal LS-SVM, distributed dynamic prediction model, electrolysis system, water electrolysis for hydrogen production

中图分类号:

TK91:TM911.4

窦真兰, 李佳文, 张春雁, 蔡祯祺, 袁本峰, 郏琨琪, 肖国萍, 王建强. 固体氧化物电解池时空分布式参数建模[J]. 综合智慧能源, 2024, 46(7): 53-62.

DOU Zhenlan, LI Jiawen, ZHANG Chunyan, CAI Zhenqi, YUAN Benfeng, JIA Kunqi, XIAO Guoping, WANG Jianqiang. Spatiotemporal distributed parameter modeling of solid oxide electrolysis cells[J]. Integrated Intelligent Energy, 2024, 46(7): 53-62.

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参数	数值
电池长度L/cm	10
电池宽度b/cm	10
电池片厚度h_s/um	215
连接体厚度h_l/mm	1
阴极流道高度h_c/mm	1
阳极流道高度h_a/mm	1
电池片辐射系数σ_s/m	0.8
电池片比定压热容c_p_,s/[J·(kg·K)^-1]	500
电池片密度ρ_s/(kg·m^-3)	5 900
连接体辐射系数σ_l	0.1
连接体比定压热容c_p_,l/[J·(kg·K)^-1]	500
连接体密度ρ_l/(kg·m^-3)	8 000
阴极入口温度/℃	750
阴极气体组分	y(H₂)=10%，y(H₂O)=90%
阴极入口压力p_c,in/kPa	100
阳极入口温度/℃	750
阳极气体组分	y(N₂)=79%，y(O₂)=21%
阳极入口压力p_a,in/kPa	100

操作参数	变动范围	阶跃幅度	阶跃周期/s	阶跃间隔/s
电流	20~80 A	10 A	6 720	1 120
电堆入口温度	650~740 ℃	10 ℃	1 120	160
蒸汽转化率	0.40~0.80	0.05	40	5
空气比	1~4	1	160	40