基于T-S模型的预测控制在SOFC中的应用

固体氧化物燃料电池(SOFC)被认为是21世纪最有潜力的发电技术之一.文章针对固体氧化物燃料电池(SOFC)具有较强的输出非线性且难以建模的特点,提出一种基于Takagi-Sugeno模型的模糊预测控制方法.文章先根据SOFC的结构建立了机理模型,然后采用模糊聚类的方法,建立了Takagi-Sugeno的预测模型来逼近模型中的非线性部分,并结合广义预测控制算法(GPC)来实现对SOFC的控制,此方法能很好的解决SOFC输出电压不稳定和难以跟踪设定功率的问题.对SOFC系统的仿真结果表明了该方法的有效性.     

基于广义回归神经网络的SOFC电压模型研究靠

首先介绍并分析了固体氧化物燃料电池(SOFC)的工作原理和理论电压模型.然后,针对SOFC系统过于复杂,理论电压模型存在明显不足的特点,试图绕开SOFC的内部复杂性,利用广义回归神经网络(GRNN)对SOFC系统进行辨识建模.模型以电池工作温度为神经网络辨识模型的输入量,电池电压/电流密度为输出量,利用750组实验数据作为训练样本,建立了SOFC在不同工作温度下的电池电压/电流密度动态响应模型.仿真结果表明了该方法的有效性,所建模型精度也较高.     

基于LS-SVM的SOFC系统自适应逆控制

关于固体氧化物燃料电池(Solid Oxide Fuel Cell,SOFC)性能的优化问题,其中工作温度和电压是关键参数。针对固体氧化物燃料具有较强的非线性且常规成熟线性理论不适用的特点,提出了一种最小二乘支持向量机(LS-SVM)的自适应逆控制策略。首先建立了SOFC的机理模型,然后采用LS-SVM方法建立了SOFC系统的逆动力学模型。在获得逆动力学模型的基础上,设计了一种逆动力学递推最小二乘支持向量机的控制方法。在自适应逆控制下,逆模型通过RLS算法更新,控制器依据ε-滤波进行在线调整。SOFC系统辨识和仿真结果表明,改进方法的可信性,辨识出的逆动力模型具有较高的精度,所设计的控制器能获得较好的控制性能。仿真结果可以为SOFC的实用化和产业化提供一定的理论依据。     

基于启发式动态规划的固体氧化物燃料电池优化控制研究

固体氧化物燃料电池(SOFC)系统是一个非线性系统,现存的建模方法和优化控制算法很难对其进行精确的建模及优化控制;针对此问题,采用基于数据的建模方法,对固体氧化物燃料电池系统进行BP神经网络建模,然后在此基础上,首次采用启发式动态规划(HDP)算法对固体氧化物燃料电池系统中的各种气体分压、输出电压以及温度进行优化控制;Matlab仿真结果表明,基于BP神经网络的HDP优化算法具有收敛速度快、鲁棒性强、控制精度高等优点,并使固体氧化物燃料电池系统在负载变化时很快稳定输出电压,实现了优化控制,减少能耗。     

基于人工神经网络的固体氧化物燃料电池性能 预测模型开发

固体氧化物燃料电池(Solid-Oxide Fuel Cell,SOFC)因其能量转换效率高而备受关注,但其相 关技术非常复杂,技术成熟度比质子交换膜燃料电池、直接甲醇燃料电池等其他类型的燃料电池低。 SOFC 的微观结构是影响其性能的因素之一,为加速 SOFC 的商业化应用,需要对其复杂微观结构进 行有效优化。同时,SOFC 性能测试实验耗时长、费用高,而高可靠性的 SOFC 计算机模型可用来缩 短 SOFC 微观结构优化时间和降低研发成本。该研究根据阳极支撑 SOFC 结构变化对应的性能实验 数据,开发了一种基于人工神经网络的、根据结构特性来预测其性能的 SOFC 计算机模型。实验过程 利用部分数据对该人工神经网络进行训练,并利用另一部分数据对其进行验证。结果显示,所开发的 SOFC 模型能够准确地根据微观结构的变化呈现其性能变化,适合用于 SOFC 微观结构的优化。     

两种固体氧化物燃料电池系统的故障建模与仿真对比研究

固体氧化物燃料电池(SOFC)系统的建模方式较多,而基于机理模型的故障诊断是能够通过系统的动态趋势辨别故障的有效手段之一,但该方法对机理模型的准确性有要求.此外,不同的燃料供给系统采用的系统结构也是有差异的,进而导致在相同故障下SOFC系统的动态响应也是不同的.因此,本文基于两种燃料供应方式,提出了分别以纯氢气和天然气作为燃料的SOFC系统结构,并基于原有机理知识进行MATLAB/Simulink系统建模.经与真实SOFC系统实验对比,搭建的系统模型能够有效模拟系统在无故障状态下的动态变化;另外,在无故障模型的基础上,分别加入两类常见故障,其一为风机故障,其二为燃料供应管路泄露.最后通过仿真分析,明确了所搭建模型的合理性,且发现了两种燃料供应对SOFC系统热响应特性是不同的,对SOFC系统故障的检测和设备选型具有重要意义.     

两种固体氧化物燃料电池系统的故障建模与仿真对比研究（英文）

固体氧化物燃料电池(SOFC)系统的建模方式较多,而基于机理模型的故障诊断是能够通过系统的动态趋势辨别故障的有效手段之一,但该方法对机理模型的准确性有要求.此外,不同的燃料供给系统采用的系统结构也是有差异的,进而导致在相同故障下SOFC系统的动态响应也是不同的.因此,本文基于两种燃料供应方式,提出了分别以纯氢气和天然气作为燃料的SOFC系统结构,并基于原有机理知识进行MATLAB/Simulink系统建模.经与真实SOFC系统实验对比,搭建的系统模型能够有效模拟系统在无故障状态下的动态变化;另外,在无故障模型的基础上,分别加入两类常见故障,其一为风机故障,其二为燃料供应管路泄露.最后通过仿真分析,明确了所搭建模型的合理性,且发现了两种燃料供应对SOFC系统热响应特性是不同的,对SOFC系统故障的检测和设备选型具有重要意义.     

安全操控下5 kW固体氧化物燃料电池电堆预测控制器设计

基于5 kW固体氧化物燃料电池(SOFC)电堆,考虑建模仿真—2温度层模型在模型精度与复杂度上做了更好的折中,可以更有效地应用于控制器设计.本文首先对2温度层模型在常用稳态工作点附近采用泰勒级数展开,获得其状态空间方程.然后考虑其安全操作特性,设计了两种带约束的预测控制器:即面向SOFC电堆的快速负载跟踪与燃料亏空控制...     

顶层MCFC-MGT联合循环系统稳态性能仿真研究

被誉为绿色能源的熔融碳酸盐燃料电池具有高效无污染的突出优点,是21世纪最有吸引力的发电方法之一,高品位的废热使得它可以和燃气轮机组成联合循环系统,从而大幅度地提高装置整体效率,在分布式发电领域具有十分重要的意义.该文在IPSEPRO仿真环境下建立了顶层熔融碳酸盐燃料电池/微型燃气轮机联合循环系统仿真模型.利用该模型对联合系统在额定工况和变工况下的稳态性能进行了仿真研究,并对平均电流密度、燃料利用系数等参数对系统性能的影响作了探讨.仿真结果表明,顶层熔融碳酸盐燃料电池/微型燃气轮机联合循环系统具有较高的发电效率,并具有良好的变负荷特性.     

平板式固体氧化物燃料电池的建模与仿真研究

基于气流模型以及热模型利用流体力学计算软件Fluent,建立平板式固体氧化物燃料电池（SOFC）的计算流体力学（CFD）模型。模型中采用电化学反应控制方程、质量、动量和能量守恒方程描述电池内的传热传质等物理过程,并对电池内部的运行电压、温度以及各种极化分布情况,进行了数值模拟。研究给出了顺流平板型SOFC与逆流平板型SOFC情况下,运行电压、温度和极化的分布。结果显示逆流平板型SOFC可获得更好的性能,具有更大的电功率密度和燃料利用率。     

Monitoring Power Data: A first step towards a unified energy efficiency evaluation toolset for HPC data centers

The energy consumption of High Performance Computing (HPC) systems, which are the key technology for many modern computation-intensive applications, is rapidly increasing in parallel with their performance improvements. This increase leads HPC data centers to focus on three major challenges: the reduction of overall environmental impacts, which is driven by policy makers; the reduction of operating costs, which are increasing due to rising system density and electrical energy costs; and the 20 MW power consumption boundary for Exascale computing systems, which represent the next thousandfold increase in computing capability beyond the currently existing petascale systems. Energy efficiency improvements will play a major part in addressing these challenges.This paper presents a toolset, called Power Data Aggregation Monitor (PowerDAM), which collects and evaluates data from all aspects of the HPC data center (e.g. environmental information, site infrastructure, information technology systems, resource management systems, and applications). The aim of PowerDAM is not to improve the HPC data center's energy efficiency, but is to collect energy relevant data for analysis without which energy efficiency improvements would be non-trivial and incomplete. Thus, PowerDAM represents a first step towards a truly unified energy efficiency evaluation toolset needed for improving the overall energy efficiency of HPC data centers.     

Optimization and control of a stand-alone hybrid solid oxide fuel cells/gas turbine system coupled with dry reforming of methane

This paper presents the hybrid solid oxide fuel cells (SOFC)/gas turbine (GT) system coupled with dry reforming of methane (DRM). The DRM is a syngas producer by consuming greenhouse gas. The stand-alone (off-the-grid) power system is developed by using a combination of a post-burner, recuperators and pressurized recycles in place of external energy supplies. To address the stand-alone operation and meet the complete combustion condition for the burner, the optimal operating conditions are initially determined by solving a constrained optimization algorithm for maximizing the hybrid power efficiency, and the dynamic control loops are implemented in a plantwide environment. In the proposed plantwide control strategy, the inventory control framework is added to regulate the plant component inventory, an air/fuel cross-limiting combustion control is added to ensure complete combustion and reduce heat loss, and the power and CO₂ emission control configuration is added to achieve the quality control performance. Finally, the simulation shows that the IMC-based multi-loop control scheme can efficiently regulate the total system power and control CO₂ emissions per kWh of electricity as well.     

Disturbance rejection control of a fuel cell power plant in a grid-connected system

Interface of a fuel cell plant to power grid is challenging because of the high nonlinearities of the fuel cell plant and the power conditioning system (PCS). This paper focuses on the control of grid-connected solid-oxide fuel cell (SOFC) power plant that is subject to varying load and uncertain network parameters. To this end, Active Disturbance Rejection Control (ADRC) is utilized to improve the performance of the PCS consisting of a dc-dc converter and a dc-ac inverter. ADRC is used in the dc-dc converter to stabilize the dc link voltage and yield a robust performance against the nonlinearity. Used in the dc-ac inverter, ADRC eliminates the steady-state error and is insensitive to the high-frequency noise. Simulation results show that, for grid current control, ADRC achieves a more robust performance than the conventional proportional-integral (PI) controller. Moreover, the total harmonic distortions (THDs) of the output current controlled by ADRC are always below 5% in spite of the variation in the load demand and network parameters.     

Nano-structured solid oxide fuel cell design with superior power output at high and intermediate operation temperatures

A solid oxide fuel cell (SOFC) with a thin-film yttria-stabilized zirconia (YSZ) electrolyte was developed and tested. This novel SOFC shows a similar multilayer set-up as other current anode-supported SOFCs and is composed of a Ni/8YSZ anode, a gas-tight 8YSZ electrolyte layer, a dense Sr-diffusion barrier layer and a LSCF cathode. To increase the power density and lower the SOFC operating temperature, the thickness of the electrolyte layer was reduced from around 10 μm in current cells to 1 μm, using a nanoparticle deposition method. By using the novel 1 μm electrolyte layer, the current density of our SOFC progressed to 2.7, 2.1 and 1.6 A/cm² at operation temperatures of 800, 700 and 650°C, respectively, and out-performs all similar cells reported to date in the literature. An important consideration is also that cost-effective dip-coating and spin-coating methods are applied for the fabrication of the thin-film electrolyte. Processing of 1 μm layers on the very porous anode substrate material was initially experienced as very difficult and therefore 8YSZ nanoparticle coatings were developed and optimized on porous 8YSZ model substrates and transferred afterwards to regular anode substrates. In this paper, the preparation of the novel SOFC is shown and its morphology is illustrated with high resolution SEM pictures. Further, the performance in a standard SOFC test is demonstrated.     

Rapid Load Following of an SOFC Power System via Stable Fuzzy Predictive Tracking Controller

The solid oxide fuel cell (SOFC) is widely accepted for clean and distributed power generation use, but critical operation problems often occur when the stand-alone fuel cell is directly connected to the electricity grid or the dc electric user. In order to address these problems, in this paper, a data-driven fuzzy modeling method is employed to identify the dynamic model of an integrated SOFC/capacitor system. A novel offset-free input-to-state stable fuzzy predictive controller is developed based on the obtained fuzzy model. Both the rapid power load following and safe SOFC operation requirements are taken into account in the design of the closed-loop control system. Simulations are also given to demonstrate the load following control performance of the proposed fuzzy predictive control strategy for the SOFC/capacitor power system.     

质子交换膜燃料电池建模与动态仿真

对质子交换膜燃料电池（PEMFC）电堆进行电输出特性研究,有助于改善燃料电池的设计,提高其性能。运用MATLAB的Simulink仿真工具对PEMFC建立仿真模型,通过所建立的电堆参数模型,就能够研究主要运行参变量对电堆动态输出性能和电堆非线性内阻产生的影响。当电堆输出电流出现阶跃变化时,对电堆电压,输出功率,消耗功率,电堆效率,非线性内阻的动态响应,进行了仿真和结果分析。仿真结果符合文献[7]实验数据,表明此参数模型是可操作和有效的,并可方便地用于PEMFC控制方法研究。