Optimization of a solid oxide fuel cell and micro gas turbine hybrid system

For a solid oxide fuel cell (SOFC) and micro gas turbine (MGT) hybrid system, optimal control of load changes requires optimal dynamic scheduling of set points for the system's controllers. Thus, this paper proposes an improved iterative particle swarm optimization (PSO) algorithm to optimize the operating parameters under various loads. This method combines the iteration method and the PSO algorithm together, which can execute the discrete PSO iteratively until the control profile would converge to an optimal one. In MATLAB environment, the simulation results show that the SOFC/MGT hybrid model with the optimized parameters can effectively track the output power with high efficiency. Hence, the improved iterative PSO algorithm can be helpful for system analysis, optimization design, and real‐time control of the SOFC/MGT hybrid system. Copyright © 2011 John Wiley & Sons, Ltd.     

Dynamic modeling of a SOFC/MGT hybrid power system based on modified OIF Elman neural network

Solid oxide fuel cell (SOFC) integrated into micro gas turbine (MGT) cycle is a promising power‐generation technology. This article proposes a modified output–input feedback (OIF) Elman neural network model to describe the nonlinear temperature and power dynamic properties of the SOFC/MGT hybrid system. A physics‐based mathematical model of a 220 kW SOFC/MGT hybrid power system is used to generate the data required for the training and prediction of the modified OIF Elman neural network identification model. Compared with the conventional Elman neural network, the simulation results show that the modified OIF Elman identification model can follow the temperature and power response of the SOFC/MGT hybrid system with higher prediction accuracy and faster convergent speed. Copyright © 2010 John Wiley & Sons, Ltd.     

Power decoupling control of a solid oxide fuel cell and micro gas turbine hybrid power system

Solid Oxide Fuel Cell (SOFC) integrated into Micro Gas Turbine (MGT) is a multivariable nonlinear and strong coupling system. To enable the SOFC and MGT hybrid power system to follow the load profile accurately, this paper proposes a self-tuning PID decoupling controller based on a modified output-input feedback (OIF) Elman neural network model to track the MGT output power and SOFC output power. During the modeling, in order to avoid getting into a local minimum, an improved particle swarm optimization (PSO) algorithm is employed to optimize the weights of the OIF Elman neural network. Using the modified OIF Elman neural network identifier, the SOFC/MGT hybrid system is identified on-line, and the parameters of the PID controller are tuned automatically. Furthermore, the corresponding decoupling control law is achieved by the conventional PID control algorithm. The validity and accuracy of the decoupling controller are tested by simulations in MATLAB environment. The simulation results verify that the proposed control strategy can achieve favorable control performance with regard to various load disturbances.     

Performance analysis for the part-load operation of a solid oxide fuel cell–micro gas turbine hybrid system

In this paper, the performance evaluation of a solid oxide fuel cell (SOFC)–micro gas turbine (MGT) hybrid power generation system under the part-load operation was studied numerically. The present analysis code includes distributed parameters model of the cell stack module. The conversions of chemical species for electrochemical process and fuel reformation process are considered. Besides the temperature distributions of the working fluids and each solid part of cell module by accounting heat generation and heat transfers, are taken into calculation. Including all of them, comprehensive energy balance in the cell stack module is calculated. The variable MGT rotational speed operation scheme is adopted for the part-load operation. It will be made evident that the power generation efficiency of the hybrid system decreases together with the power output. The major reason for the performance degradation is the operating temperature reduction in the SOFC module, which is caused by decreasing the fuel supply and the heat generation in the cells. This reduction is also connected to the air flow rate supplement. The variable MGT rotational speed control requires flexible air flow regulations to maintain the SOFC operating temperature. It will lead to high efficient operation of the hybrid system.     

Parameter optimization study on SOFC‐MGT hybrid power system

This paper mainly studied the solid oxide fuel cell (SOFC)–micro gas turbine (MGT) hybrid power system. The key parameters that greatly influence the overall system performance have been studied and optimized. The thermodynamic potential of improving the hybrid system performance by integrating SOFC with the advanced thermal cycle system is analyzed. The optimization rules of main parameters of SOFC‐MGT hybrid power system with the turbine inlet temperature (TIT) of MGT as a constraint condition are revealed. The research results show that TIT is a key parameter that limits the electrical efficiency of hybrid power system. With the increase of the cell number, both the power generation efficiency of the hybrid cycle power system and TIT increase. Regarding the hybrid system with the fixed cell number, in order to get a higher electrical efficiency, the operating temperature of SOFC should be enhanced as far as possible. However, the higher operating temperature will result in the higher TIT. Increasing of fuel utilization factor is an effective measure to improve the performance of hybrid system. At the same time, TIT increases slightly. Both the electrical efficiency of hybrid power system and TIT reduce with the increase of the ratio of steam to carbon. The achievements obtained from this paper will provide valuable information for further study on SOFC‐MGT hybrid power system with high efficiency. Copyright © 2010 John Wiley & Sons, Ltd.     

Multi-loop control strategy of a solid oxide fuel cell and micro gas turbine hybrid system

Solid oxide fuel cell and micro gas turbine (SOFC/MGT) hybrid system is a promising distributed power technology. In order to ensure the system safe operation as well as long lifetime of the fuel cell, an effective control manner is expected to regulate the temperature and fuel utilization at the desired level, and track the desired power output. Thus, a multi-loop control strategy for the hybrid system is investigated in this paper. A mathematical model for the SOFC/MGT hybrid system is built firstly. Based on the mathematical model, control cycles are introduced and their design is discussed. Part load operation condition is employed to investigate the control strategies for the system. The dynamic modeling and control implementation are realized in the MATLAB/SIMULINK environment, and the simulation results show that it is feasible to build the multi-loop control methods for the SOFC/MGT hybrid system with regard to load disturbances.     

Dynamic temperature modeling of an SOFC using least squares support vector machines

Cell temperature control plays a crucial role in SOFC operation. In order to design effective temperature control strategies by model-based control methods, a dynamic temperature model of an SOFC is presented in this paper using least squares support vector machines (LS-SVMs). The nonlinear temperature dynamics of the SOFC is represented by a nonlinear autoregressive with exogenous inputs (NARXs) model that is implemented using an LS-SVM regression model. Issues concerning the development of the LS-SVM temperature model are discussed in detail, including variable selection, training set construction and tuning of the LS-SVM parameters (usually referred to as hyperparameters). Comprehensive validation tests demonstrate that the developed LS-SVM model is sufficiently accurate to be used independently from the SOFC process, emulating its temperature response from the only process input information over a relatively wide operating range. The powerful ability of the LS-SVM temperature model benefits from the approaches of constructing the training set and tuning hyperparameters automatically by the genetic algorithm (GA), besides the modeling method itself. The proposed LS-SVM temperature model can be conveniently employed to design temperature control strategies of the SOFC.     

A hybrid multi-variable experimental model for a PEMFC

A hybrid model composed of a least square support vector machine (LS-SVM) model and a pressure-incremental model is developed to dispose operation conditions of current, temperature, cathode and anode gas pressures, which have major impacts on a proton exchange membrane fuel cell's (PEMFC) performance. The LS-SVM model is built to incorporate current and temperature and a particle swarm optimization (PSO) algorithm is used to improve its performance. The optimized LS-SVM model fits the experimental data well, with a mean squared error of 0.0002 and a squared correlation coefficient of 99.98%. While a pressure-incremental model with only one empirical coefficient is constructed to for anode and cathode pressures with satisfactory results. Combining these two models together makes a powerful hybrid multi-variable model that can predict a PEMFC's voltage under any current, temperature, cathode and anode gas pressure. This black-box hybrid PEMFC model could be a competitive solution for system level designs such as simulation, real-time control, online optimization and so on.     

天然气重整SOFC/MGT混合分布式供能系统性能分析

针对固体氧化物燃料电池(SOFC)与微型燃气轮机(MGT)构成的混合分布式供能系统,首先建立了一种管式SOFC准二维数值模型,优化了辐射计算,提高了热传递模型的准确性;考虑了CO及H2同时作为燃料参加电化学反应,并完善了损失计算模型;最后采用所发展的系统性能预测模型,分别在内部重整和外部重整情况下,预测比较了两种SOFC/MGT混合系统的性能,结果表明外部重整系统在系统输出功率、CO2排放以及热应力分布方面都比内部重整系统具有优势,然而这种轻微的优势是需要额外增加外部重整器的设备投资换取的。     

SOFC-MGT混合发电系统的半实物仿真方案研究

提出了一种固体氧化物燃料电池(SOFC)-微型燃气轮机(MGT)混合发电系统的半实物仿真和预集成方案.该方案以基于模型的燃烧器和涡轮增压器分别作为SOFC模拟器和MGT模拟器,克服了现有的试验系统均只适用于单一工作方式和传统的慢速迭代控制算法的缺点,可以兼容增压型和常压型两种工作模式,适用于正常运行、启动、部分负荷和瞬态等多种工况的模拟.通过对比传统的慢速迭代控制算法开发模式,探讨了基于Matlab/xPC Target和PowerPC5xx的快速控制原型的V型控制器开发模式.     

Parameter identification for solid oxide fuel cells using cooperative barebone particle swarm optimization with hybrid learning

Solid oxide fuel cell (SOFC) has been widely recognized as one of the most promising fuel cells. The SOFC performance is highly influenced by several parameters associated with the internal multi-physicochemical processes. In this work, the optimal modeling strategy is designed to determine the parameters of SOFC using a simple and efficient barebone particle swarm optimization (BPSO) algorithm. The cooperative coevolution strategy is applied to divide the output voltage function into four subfunctions based on the interdependence among variables. To the nonlinear characteristic of SOFC model, a hybrid learning strategy is proposed for BPSO to ensure a good balance between exploration and exploitation. The experimental results illustrate the effectiveness of the proposed algorithm. The comparisons also indicate that cooperative coevolution strategy and hybrid learning improve the performance of original PSO algorithm, offering better approximation effect and stronger robustness.     

On the start-up transient simulation of a turbo fuel cell system

The start-up transient behavior is an important issue in a turbo fuel cell system design. This paper developed a general dynamic model of the hybrid fuel cell/micro-gas turbine (MGT) system to investigate the transient behavior during cold start. The unsteady flow process through components of the turbo fuel cell system, which includes a solid oxide fuel cell (SOFC) stack, an afterburner, a turbo generator and heat exchangers, was modeled using a filling-and-emptying approach. Each major component was treated as a function block in the coded model. Computer simulations were performed on a Matlab/Simulink platform based on the block-diagram concept. The main focus of this study is on the start-up transient behavior of a basic turbo fuel cell system. The simulation results show that the start-up time for the example turbo fuel cell system (200 kW SOFC plus 50 kW MGT) can be up to about a few hours. Preliminary parametric investigations with different operating conditions show that the start-up duration can be reduced to less than 1 h.     

Control-oriented thermal management of solid oxide fuel cells based on a modified Takagi–Sugeno fuzzy model

Thermal management for a solid oxide fuel cell (SOFC) is actually temperature control, due to the importance of cell temperature for the performance of an SOFC. An SOFC stack is a nonlinear and multi-variable system which is difficult to model by traditional methods. A modified Takagi–Sugeno (T–S) fuzzy model that is suitable for nonlinear systems is built to model the SOFC stack. The model parameters are initialized by the fuzzy c-means clustering method, and learned using an off-line back-propagation algorithm. In order to obtain the training data to identify the modified T–S model, a SOFC physical model via MATLAB is established. The temperature model is the center of the physical model and is developed by enthalpy-balance equations. It is shown that the modified T–S fuzzy model is sufficiently accurate to follow the temperature response of the stack, and can be conveniently utilized to design temperature control strategies.     

Part-load,startup, and shutdown strategies of a solid oxide fuel cell-gas turbine hybrid system

Current work on the performance of a solid oxide fuel cell (SOFC) and gas turbine hybrid system is presented. Each component model developed and applied is mathematically defined. The electrochemical performance of single SOFC with different fuels is tested. Experimental results are used to validate the SOFC mathematical model. Based on the simulation model, a safe operation regime of the hybrid system is accurately plotted first. Three different part-load strategies are introduced and used to analyze the part-load performance of the hybrid system using the safe regime. Another major objective of this paper is to introduce a suitable startup and shutdown strategy for the hybrid system. The sequences for the startup and shutdown are proposed in detail, and the system responses are acquired with the simulation model. Hydrogen is used instead of methane during the startup and shutdown process. Thus, the supply of externally generated steam is not needed for the reforming reaction. The gas turbine is driven by complementary fuel and supplies compressed air to heat up or cool down the SOFC stack operating temperature. The dynamic simulation results show that smooth cooling and heating of the cell stack can be accomplished without external electrical power.     

Effects of operating and design parameters on the performance of a solid oxide fuel cell–gas turbine system

We present a steady‐state thermodynamic model of a hybrid solid oxide fuel cell (SOFC)–gas turbine (GT) cycle developed using a commercial process simulation software, AspenPlus?. The hybrid cycle model incorporates a zero‐dimensional macro‐level SOFC model. A parametric study was carried out using the developed model to study the effects of system pressure, SOFC operating temperature, turbine inlet temperature, steam‐to‐carbon ratio, SOFC fuel utilization factor, and GT isentropic efficiency on the specific work output and efficiency of a generic hybrid cycle with and without anode recirculation. The results show that system pressure and SOFC operating temperature increase the cycle efficiency regardless of the presence of anode recirculation. On the other hand, the specific work decreases with operating temperature. Overall, the model can successfully capture the complex performance trends observed in hybrid cycles. Copyright © 2010 John Wiley & Sons, Ltd.     

Externally reformed solid oxide fuel cell–micro-gas turbine (SOFC–MGT) hybrid systems fueled by methanol and di-methyl-ether (DME)

Solid oxide fuel cell–micro-gas turbine (SOFC–MGT) hybrid power plants integrate a solid oxide fuel cell and a micro-gas turbine and can achieve efficiencies of over 60% even for small power outputs (200–500 kW). The SOFC–MGT systems currently developed are fueled with natural gas, which is reformed inside the same stack, but the use of alternative fuels can be an interesting option. In particular, as the reforming temperature of methanol and di-methyl-ether (DME) (200–350 °C) is significantly lower than that of natural gas (700–900 °C), the reformer can be sited outside the stack. External reforming in SOFC–MGT plants fueled by methanol and DME enhances efficiency due to improved exhaust heat recovery and higher voltage produced by the greater hydrogen partial pressure at the anode inlet. The study carried out in this paper shows that the main operating parameters of the fuel reforming section (temperature and steam-to-carbon ratio (SCR)) must be carefully chosen to optimise the hybrid plant performance. For the stoichiometric SCR values, the optimum reforming temperature for the methanol fueled hybrid plant is approximately 240 °C, giving efficiencies of about 67–68% with a SOFC temperature of 900 °C (the efficiency is about 72–73% at 1000 °C). Similarly, for DME the optimum reforming temperature is approximately 280 °C with efficiencies of 65% at 900 °C (69% at 1000 °C). Higher SCRs impair stack performance. As too small SCRs can lead to carbon formation, practical SCR values are around one for methanol and 1.5–2 for DME.     

Novel and optimal integration of SOFC-ICGT hybrid cycle: Energy analysis and entropy generation minimization

Integrating fuel cells with conventional gas turbine based power plant yields higher efficiency, especially solid oxide fuel cell (SOFC) with gas turbine (GT). SOFCs are energy efficient devices, performance of which are not limited to Carnot efficiency and considered as most promising candidate for thermal integration with Brayton cycle. In this paper, a novel and optimal thermal integration of SOFC with intercooled-recuperated gas turbine has been presented. A thermodynamic model of a proposed hybrid cycle has been detailed along with a novelty of adoption of blade cooled gas turbine model. On the basis of 1st and 2nd law of thermodynamics, parametric analysis has been carried out, in which impact of turbine inlet temperature and compression ratio has been observed on various output parameters such as hybrid efficiency, hybrid plant specific work, mass of blade coolant requirement and entropy generation rate. For optimizing the system performance, entropy minimization has been carried out, for which a constraint based algorithm has been developed. The result shows that entropy generation of a proposed hybrid cycle first increases and then decreases, as the turbine inlet temperature of the cycle increases. Furthermore, a unique performance map has also been plotted for proposed hybrid cycle, which can be utilized by power plant designer. An optimal efficiency of 74.13% can be achieved at TIT of 1800 K and r_p,c 20.     

Estimation of exergy-based sustainability index and performance evaluation of a novel intercooled hybrid gas turbine system

This paper contributes a novel sustainability index and modified exergy indicators for conventional gas turbines and solid oxide fuel cell integrated gas turbine (SOFC-GT) hybrid power cycles. In this work, an intercooled gas turbine (Ic-GT) cycle is considered as a base cycle, which gives an additive advantage in lowering the power required for the compressor. Moreover, on SOFC integration with Ic-GT, the qualitative and quantitative performance are examined. Numerical modeling is done using MATLAB and an exclusive comparison has been made based on energy-exergy and sustainability analysis for the system and its components. On comparing the first law efficiency at turbine inlet temperature, TIT 1250K and rp = 18 for Ic-GT, intercooled recuperated gas turbine (Ic-RGT), and Ic–SOFC–RGT, it is 25.82%, 36.04%, and 64.78%, respectively. Similarly, second law efficiency is 11.43%, 22.33%, and 61.11% and the overall sustainability index is 1.12, 1.28, and 2.57 for Ic-GT, Ic-RGT, and Ic–SOFC–RGT, respectively. Nine other modified exergy-based parameters are used to identify the role of fuel and product exergy and then compare the most affected component in three configurations.     

Analysis of the design of a pressurized SOFC hybrid system using a fixed gas turbine design

Design characteristics and performance of a pressurized solid oxide fuel cell (SOFC) hybrid system using a fixed gas turbine (GT) design are analyzed. The gas turbine is assumed to exist prior to the hybrid system design and all the other components such as the SOFC module and auxiliary parts are assumed to be newly designed for the hybrid system. The off-design operation of the GT is modeled by the performance characteristics of the compressor and the turbine. In the SOFC module, internal reforming with anode gas recirculation is adopted. Variations of both the hybrid system performance and operating condition of the gas turbine with the design temperature of the SOFC were investigated. Special focus is directed on the shift of the gas turbine operating points from the original points. It is found that pressure loss at the fuel cell module and other components, located between the compressor and the turbine, shifts the operating point. This results in a decrease of the turbine inlet temperature at each compressor operating condition relative to the original temperature for the GT only system. Thus, it is difficult to obtain the original GT power. Two cell voltage cases and various degrees of temperature difference at the cell are considered and their influences on the system design characteristics and performance are comparatively analyzed.     

燃料电池_燃气轮机混合动力系统中催化燃烧室特性分析

对熔融碳酸盐燃料电池/微型燃气轮机(MCFC/MGT)混合动力系统中的催化燃烧室进行了实验和理论分析,确定了燃烧室入口温度、燃料浓度对燃料转化率的影响,在非设计工况下运行时催化燃烧室入口条件会发生变化,应用数学模型分析了各主要因素对催化燃烧室运行特性的影响。结果表明,计算结果与实验结果的最大误差在4%以内。在混合动力系统的运行范围内催化燃烧室入口温度高于770K时燃料转化率达99%以上,而入口流速和燃料浓度的变化对转化率的影响不明显。