熔融碳酸盐燃料电池/燃气轮机混合发电系统的建模与控制研究
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摘要
高温燃料电池/燃气轮机混合发电技术具有很高的发电效率和极低的污染物排放水平,在国内外引起广泛的关注。目前,该技术在国外还处于示范电站阶段,国内的相应研究才刚刚起步。
     本课题是在863工程项目“50kW天然气熔融碳酸盐燃料电池发电系统研究”和“燃料电池/燃气轮机混合动力系统研制”资助下完成的。在参考国内外混合发电系统研究经验的基础上,对熔融碳酸盐燃料电池/燃气轮机混合发电系统(MCFC/GT)进行结构设计、系统建模、动态仿真、性能分析、动态优化和分层控制,最终使设计出的系统在稳定、可靠而且高效运行的同时良好地满足负载的电能需求,为熔融碳酸盐燃料电池/燃气轮机混合发电系统提供必要的技术准备和理论指导。研究的具体内容和成果包括:
     1.建立了MCFC/GT混合发电系统动态数学模型。本文通过分析比较确定了MCFC和GT混合发电的底层循环式拓扑结构,并采用灵活的模块化建模方法建立该系统的动态模型。首先建立了面向MCFC/GT混合发电系统的简化集中参数型直接内重整熔融碳酸盐燃料电池(DIR-MCFC)模型。然后分别基于最小二乘和非线性最小二乘方法建立了燃气轮机的压气机模块和透平模块,根据质量守恒、热力学公式建立了转子模块、燃烧室模块、换热器模块以及旁通阀等。经仿真验证,该系统动态模型能够正确反映各种操作参数的动态变化和系统电能输出特性,可以作为系统仿真设计、性能分析和控制研究的有效工具。为实现动态优化和控制设计打下坚实的基础。
     2.研究了MCFC/GT混合发电的动态优化问题,并针对MCFC/GT混合发电系统动态优化问题提出了迭代遗传优化方法。本文针对复杂的动态优化问题,将迭代思想、平滑算子和改进了的遗传寻优操作相结合,设计改进的迭代遗传算法(Novel iterative genetic algorithm, NIGA),并首次利用NIGA智能寻优方法对混合系统进行动态优化的研究。对于NIGA算法,首先将变量离散化,用改进遗传优化算法搜索离散控制变量的最优解,然后在随后的迭代过程中将基准移到刚解得的最优值处,同时收缩控制变量的搜索域,使优化性能指标和控制轨线在迭代过程中不断趋于最优解。采用NIGA根据设计的目标函数离线计算出不同负荷下最优运行轨迹,避免了求解大规模的微分方程组问题,优化结果为以后混合发电系统实际应用中现场的工作人员提供操作指导或直接作为下层控制回路的设定值和系统的前馈输出值,进行闭环优化控制。
     3.提出并验证了MCFC/GT混合发电系统的分层控制设计。以建立的MCFC/GT混合发电系统的动态模型为对象,结合系统开环仿真分析结果及发电系统NIGA离线动态优化结果,完成系统稳定运行的控制设计。本文针对系统结构庞大、性能复杂且控制参数多的特点,提出具有基础层和监督层的分层控制策略。采用多输出支持向量机回归(Multi-output Support Vector Machine Regression ,MSVR)方法实现监督层、先进复合控制方法实现基础层。首先利用NIGA离线动态优化得到的数据建立基于多输出支持向量机的监督层,该监督层为MCFC/GT混合发电系统提供实时性的优化指导。实验表明基于MSVR的预测精度高于现有的基于神经网络和单输出支持向量机的函数估计方法。在基础控制层,采用分块简化再整合的设计方法,针对各输出参数响应特点,利用AZNPI对系统输出功率进行反馈调节、利用MCFC输出电压对燃料流量进行反馈调节、利用QDRNN-PID对燃烧室温度和MCFC温度进行解耦控制等。最后,将各部分内容按照分层控制设计方案连接起来,仿真验证了分层控制是合理的和有效的。在所设计的分层控制方案下混合发电系统能够跟随负载的电能需求,且具有较高的发电效率,透平入口温度和燃烧室温度及燃料使用率都能维持在系统要求的范围。
Fuel cell and gas turbine (FC/GT) hybrid power-generation system with high efficiency and low emissions has been focused and developed all over the world. In the world, the demonstration hybrid power plant has been developed. In China, fuel cell gas turbine hybrid system is still in the early research stages.
     The work is supported by the national 863 scientific project item“Analysis and control strategy for 50 kW-scale molten carbonate fuel cells power generation system”and“Molten carbonate fuel cells–gas turbine hybrid system”. According to some experiences on hybrid system in China and foreign countries, this dissertation realizes a molten carbonate fuel cell and gas turbine (MCFC/GT) hybrid power-generation system with good performances by simulation design, and makes it operate steadily by the integrated control, providing valuable instructions for developments and applications of hybrid power-generation technologies. The main achievements and contributions are summarized as follows:
     1. A dynamic model of MCFC/GT hybrid generation system is established. The topological structure of hybrid system based on bottoming mode is used by comparing with variable configurations. Firstly, the reduced lumped parameter DIR-MCFC mode is established. Then, based least square method and nonlinear least square method, the compressor module and turbine module are established respectively. The heat exchanger, catalytic oxidizer and bypass valve are modeled in several simulation modules according to the conservation law of mass and energy, and ideal gas law. At last, these separate modules are connected to build up the total MCFC/GT hybrid system dynamic model according to the designed topological structure. Simulation results show that, the model is able to and also enough to reflect all operating parameters and power output can be used in the simulation design, performance analysis and control research of the system. That lay a solid foundation for dynamic optimization and control research.
     2. The dynamic optimization problem is introduced in detail, and novel iterative genetic algorithm (NIGA) is proposed to solve the optimal operating trajectories for MCFC/GT hybrid generation system. The proposed algorithm is combined the iteration method and the novel genetic algorithm together. The algorithm is especially practical when the system’s gradient information is unavailable. For the algorithm, the control variables are discretized firstly and the novel genetic algorithm is used to search for the best solution of the discretized control variables. Next, the benchmark is moved to the acquired optimal values in the subsequent iterations and the searching space contracted at the same time, hence the optimization performance index and control profile could achieve the best value gradually through iterations.The algorithm is simple,feasible and efficient. It avoided the problem solving large-scale differential equation group. That will help workers on the spot manipulate the hybrid system in practical application or act as the set points and the feed forward control inputs in order to closed loop optimized control.
     3. The hierarchical control design is proposed and tested for molten carbonate fuel cell gas turbine hybrid generation system to operate steadily. In this dissertation, for the heavy structure, many performance parameters and complex characteristics, the hierarchical control scheme of MCFC/GT hybrid system based on Multi-output Support Vector Machine Regression (MSVR) supervisor is proposed. Advanced compound control method is the basical control. The setpoints and the values of feedforward control are obtained from MSVR. That is hierarchical control proposed in this dissertation. Optimal control results were successfully modeled and predicted by means of MSVR supervisor. This facilitates optimal feed forward control moves and set points under varying process conditions. The experiment is implemented to illustrate the superiority of the MSVR compared to neural network and SVR. The system operation is separated to some basic processes including system power, fuel utilization, combustion temperature and MCFC temperature to design and test local control strategies (AZNPI feed back power controller, fuel flow controller based on the voltage feed back and QDRNN-PID decoupling temperature controller )firstly. Then, these controlled processes are integrated to realize the ideal steady operation of MCFC/GT hybrid system under the step power loads. The simulation results illustrate the effectiveness of controllers. The hybrid system can track the desired power with high system efficiency and main system parameters are all satisfied with the real online control of the system.
引文
[1]衣宝廉.燃料电池.北京:化学工业出版社. 2003:1-4
    [2] Braun,R.J., Klein,S.A., Reindl,D.T. Review of state-of-the-art fuel cell technologies for distributed generation-a technical and marketing analysis[R]. Solar Energy Laboratory, University of Wisconsin-Madison, 2000.
    [3]毛宗强.氢能时代-燃料电池的新能源革命.电源技术. 2006, 30(2):251-254.
    [4] Fuel cell handbook(sixth edition), West Virginia: U.S. Department of energy office of fossil energy & National energy technology laboratory, 2002.
    [5]姚思童,刘虹.燃料电池的工作原理及其发展现状.沈阳工业大学学报. 1998, 20(1): 41-45.
    [6] He, W. Power generation characteristics of molten carbonate fuel cell stack by using computational fluid dynamics technique. Part1:moldelling equations and program implementation, International Journal of Energy Research,vol. 1999(23): 1345-1357.
    [7] He, W. Numerical analysis of molten carbonate fuel cell systems. In Journal of Energy Research. 1997(21): 69-76.
    [8]沈承.熔融碳酸盐燃料电池发电系统建模与智能控制策略研究[博士论文].上海:上海交通大学, 2002.
    [9] Bischoff, M., Huppmann G. Operating experience with a 250 kW molten carbonate fuel cell (MCFC) power plant. Journal of Power Sources. 2002, 105(22): 216-221.
    [10] Shinoki T., Matsumura M., Sasaki A. Development of an internal reforming molten carbonate fuel cell stack. IEEE Transactions on Energy Conversion. 1995 (10): 722-729.
    [11] Freni S., Aquino M., Passalacque E., Molten carbonate fuel cell with indirect internal reforming. Journal of Power Sources. 1994, 52(11): 41-47.
    [12] Wolf T. L., Wilemski G. Molten carbonate fuel cell performance model. Journal of Electrochemical Society. 1983 (130): 48-55.
    [13] Watanabe T., Mugikura Y., etc., Modeling analysis on molten carbonate fuel cells and stacks. Transaction of the Japan society of mechanical engineers.1986 (52): 3335-3336.
    [14] Watanabe T., Koda E., etc., Development of molten carbonate fuel cell stack performance analysis model [R]. Japan: Yokosuka research laboratory rep. 1991: 30-30.
    [15] Bosio, B., Costamagna, P. etc., Modeling and experimentation of molten carbonate fuel cell reactors in a scale-up process. Chemical Engineering Science. 1999(54): 2907-2916.
    [16] Mitsushima, S., Lifetime modeling for molten carbonate fuel cells. Denki Kagaku. 1994(62): 152-155.
    [17] Morita, H., Mugikura, Y., Izaki, Y., etc., Model of Cathode Reaction Resistance in Molten Carbonate fuel Cells. Journal of Electrochemical Society, 1998(145): 1511-1517.
    [18] Standaert, F., Hemmes,K., Woudstra, N. Analytical fuel cell modeling. Journal of Power Sources. 1996(63): 221-134.
    [19] Standaert, F., Hemmes,K., Woudstra, N. Analytical fuel cell-non-isothermal fuel cells. Journal of Power Sources. 1998(70): 181-199.
    [20] Tsuru, A. etc., Electrode's Deformation and cell performance on MCFC stack. The 2nd IFCC International fuel cell conference. Japan, 1996: 3-13.
    [21] Heidebrechta, P., Sundmacher, K., Molten carbonate fuel cell (MCFC) with internal reforming: model-based analysis of cell dynamics. Chemical Engineering Science. 2003(58): 1029-1036.
    [22] Au S. F., Woudstra, N., Hemmes, K. Verification of a simple numerical fuel cell model in a flowsheeting program by performance testing of a 110 cm2 molten carbonate fuel cell. Energy Conversion and Management. 2003(44): 2297–2307.
    [23] Lee, Y. R., Kim, I. G., Chung, G.Y. etc. Studies on the initial behaviors of the molten carbonate fuel cell. Journal of Power Sources. 2004(137): 9-16.
    [24] Beale, S. B., Lin, Y., Zhubrin, S.V., etc., Computer methods for performance prediction in fuel cells. Journal of Power Sources. 2003(118): 79-85.
    [25] Yu, L.J., Yuan, J. Q., Cao, G. Y., Numerical simulation of dynamic performance of themolten carbonate fuel cell. Chinese Journal of Chemical Engineering. 2004 (12): 272-276.
    [26] Ding, J., Patel, P. S., etc., A computer model for direct carbonate fuel cells. In proc. 4th Int.Symp.on carbonate fuel cell technology. 1997(4): 127-138.
    [27] Arato, E., Bosio, B., Massa, R., Parodi, F. Optimization of the cell shape for industrial MCFC stacks. Journal of Power Sources. 2000(86): 302–308.
    [28] Fujimura, H., Kobayashi, N., Ohtsuka, K., Heat and mass transfer in a molten carbonate fuel cell: Performance and temperature distribution in a cell stack, JSME International Journal. 1992,35(1):81-88.
    [29] Mugikura,Y., Yoshiba, F., Izaki, Y., Watanabe, T.. Performance and life of 10-kW molten-carbonate fuel cell stack using Li/K and Li/Na carbonates as the electrolyte. Journal of Power Sources. 1998(75):108–115.
    [30] Koh, J. H., Kang, B. S., Lim, H. C.. Effect of various stack parameters on temperature rise in molten carbonate fuel cell stack operation. Journal of Power Sources. 2000(91): 161-171.
    [31] Lee, J. H., Lalk, T. R. Modeling fuel cell stack systems. Journal of Power Sources. 1998(73):229–241.
    [32] Kim, M. H., Park, H. K., Chung, G. Y., Effects of water-gas shift reaction on simulated performance of a molten carbonate fuel cell. Journal of Power Sources. 2002(103): 245-252.
    [33] He, W., Dynamic model for molten carbonate fuel cell power-generation systems. Energy conversation. 1998(39): 775-783.
    [34] Lukas, M. D., Lee, K. Y., Ayagh, H. G., Modeling and cycling control of carbonate fuel cell power plants. Control Engineering Practice. 2002(10): 197–206.
    [35] Koh, J. H., Kang, B. S., Lim, H. C., Effect of various stack parameters on temperature rise in molten carbonate fuel cell stack operation. Journal of Power Sources. 2000(91):161-171.
    [36] Kang, B. S., Koh, J. H., Lim, H. C., Experimental study on the dynamic characteristics of kW-scale molten carbonate fuel cell systems. Journal of Power Sources. 2001(94): 51-62.
    [37] Miao Z., Choudhry, M.A., Klein, R.L. etc., Study of a fuel cell power plant in power distribution system. Part I. Dynamic model. IEEE Power Engineering Society General Meeting, 2004:2220– 2225.
    [38] Miao Z. Choudhry, M.A., Klein, R.L. etc., Study of a fuel cell power plant in power distribution system. Part II. Stability control, IEEE Power Engineering Society General Meeting. 2004: 2226 -2231.
    [39] Ferguson, A., Ugursal,V. I., Fuel cell modelling for building cogeneration applications. Journal of Power Sources. 2004 (137): 30-42.
    [40] Miyake, Y., Nakanishi, N., Nakajima, T. etc., A study of heat and material balances in an internal reforming molten carbonate fuel cell. Journal of Power Sources. 1995(56) : 1l-17.
    [41] Au, S.F., Woudstra, N., Hemmes, K., Study of multi-stage oxidation by flowsheet calculations on a combined heat and power molten carbonate fuel cell plant. Journal of Power Sources. 2003(122): 28-36.
    [42] Sasaki, A., Matsumoto, S., Tanaka, T. etc., Dynamic characteristics of a molten carbonate fuel cell stack, In Proc. of the 27th IEEE Conference on Decision and Control, 1988(2): 1044–1049.
    [43] Colella, W.G., Design considerations for effective control of an afterburner sub-system in a combined heat and power (CHP) fuel cell system (FCS). Journal of Power Sources. 2003,118 :118-128.
    [44] Jahn, H. J., Schroer,W., Dynamic simulation model of a steam reformer for a residential fuel cell power plant. Journal of Power Sources.2005(150): 101-109.
    [45] He W., Chen Q.. Three-dimensional simulation of a molten carbonate fuel cell stack using computational fluid dynamics technique. Journal of Power Sources. 1995(55): 25-32.
    [46] He W., Hemes K., Operating characteristics of a reformer for molten carbonate fuel cell power generation systems. Fuel processing technology. 2000(67): 61-78.
    [47] He W., The dynamic performance of a molten carbonate fuel cell in power-generation systems. Journal of Power Sources. 1994(52):179-184.
    [48] He W., Operating Characteristics of a Molten Carbonate Fuel-cell Power GenerationSystem. International Journal of Energy Research. 1999(23): 1331-1344.
    [49] Yamaguchi, M. etc., Analysis of control characteristics using fuel cell plant simulator. IEEE Transaction on Industry Electronic. 1990(37): 378-386
    [50] Okada, T. etc., Study of temperature control in indirect internal reforming MCFC stack, In Proc. of the Intersociety Energy Conversion Engineering Conference, 1990(3): 207-212.
    [51] Sasaki, A., Matsumoto,S.,Fujitsuka, M., Shinoki, T. etc., CO2 recovery in molten carbonate fuel cell system by pressure swing absorption. Journal of Energy Conversion. 1993(81):26–32.
    [52] Fukuzawa, etc., Control of MCFC by feedback linearization technique. Transactions of the Japan Society of Mechanical Engineers. 1995(61): 4270-4275.
    [53] Kim, Y. H., Kim, S. S. An electrical modeling and fuzzy logic control of a fuel cell generation system. IEEE Transactions on Energy Conversion. 1999(14): 239–244.
    [54] Nishitani, H. etc., Dynamic simulation of large systems. International chemical Engineering. 1993(33):298-306.
    [55] Lukas, M. D., Lee, K.Y. etc., Development of a stack simulation model for control study on direct reforming molten carbonate fuel cell power plant. IEEE Transactions on Energy Conversion. 1999(14): 1651–1657.
    [56] Mangold, M., Sheng, M., Heidebrechtc, P. etc., Development of physical models for the process control of a molten carbonate fuel cell system. Chemical Engineering Science. 2004(59): 4847– 4852.
    [57] Vahidi, A., Stefanopoulou, A. Peng,H., Model predictive control for starvation prevention in a hybrid fuel cell system. In Proc. American Control Conference. 2004: 834-839.
    [58] Au, S. F. , McPhail, S. J., Woudstra,N., The influence of operating temperature on the efficiency of a combined heat and power fuel cell plant. Journal of Power Sources.2003(122): 37-46.
    [59] Yoshiba, F. Abe, T., Watanabe, T., Numerical analysis of molten carbonate fuel cell stack performance: diagnosis of internal conditions using cell voltage profiles. Journal of Power Sources. 2000(87): 21–27.
    [60] Kang,B. S., Koh,J. H., Lim, H. C., Effects of system configuration and operating condition on MCFC system efficiency. Journal of Power Sources, 2002(108): 232-238.
    [61] Colella, W. G. Modelling results for the thermal management sub-system of a combined heat and power (CHP) fuel cell system (FCS). Journal of Power Sources. 2003(118): 129-149.
    [62] Bosio, B., Costamagna, P., Parodi, F. etc., Industrial experience on the development of the molten carbonate fuel cell technology. Journal of Power Sources. 1998(74): 175-187.
    [63] Grillo O., Magistri L, Massardo A. F., Hybrid systems for distributed power generation based on pressurization and heat recovering of an existing 100 kW molten carbonate fuel cell. Journal of Power Sources. 2003, 115(2): 252-267.
    [64] Palsson Jens. Combined solid oxide fuel cell and gas turbine systems for efficient power and heat generation.Journal of Power Source. 2000(86):442-448.
    [65] Kuchonthara P.. Energy recuperation in solid oxide fuel cell (SOFC) and gas turbine (GT) combined system. Journal of Power Sources. 2003(117): 7-13.
    [66] Inui,Y. High performance SOFC/GT combined power generation system with CO2 recovery by oxygen combustion method. Energy Conversion and Management. 2005(46):1837-1847.
    [67] Inui Y., Yanagisawa S., Ishida T. Proposal of high performance SOFC combined power generation system with carbon dioxide recovery [J].Energy Conversion and Management 44 (2003) 597-609.
    [68] Selimovic,Azra. Networked solid oxide fuel cell stacks combined with a gas turbine cycle. Journal of Power Sources. 2002(106):76-82.
    [69] Ghezel-Ayagh, H., Walzak J., et al. State of direct fuel cell/turbine systems development. Journal of Power Sources. 2005, 152(1): 219-225.
    [70] Kang, B. S., Koh,J. H. et al. Effects of system configuration and operating condition on MCFC system efficiency. Jounal of Power Sources. 2002, 108(1-2): 232-238.
    [71] G. De Simon, F. Parodi, M. Fermeglia, R. Taccani, Simulation of process for energy production based on molten carbonate fuel cells. J. Power Sources 115 (2003) 210–218
    [72] Amorelli, A., M. B. Wilkinson, et al. An experimental investigation into the use of molten carbonate fuel cells to capture CO2 from gas turbine exhaust gases. Energy 2004,29(9-10): 1279-1284.
    [73] Bedont, P., O. Grillo, et al. Off-design performance analysis of a hybrid system based on an existing molten fuel cell stack.. Journal of Engineering for Gas Turbines and Power- Transactions of the Asme. 2003, 125(4): 986-993.
    [74] Lusardi, A., B. Bosio, et al. An example of innovative application in fuel cell system development: CO2 segregation using Molten Carbonate Fuel Cells. Journal of Power Sources. 2004,131(1-2): 351-360.
    [75] Kimijima, S., Kasagi N., Cycle analysis of micro gas turbine-molten carbonate fuel cell hybrid system. Jsme International Journal Series B-Fluids and Thermal Engineering. 2005, 48(1): 65-74.
    [76] Magistri, L., Traverso, A., Cerutti, F., etc., Modeling of Pressurized Hybrid Systems Based on Integrated Planar Solid Oxide Fuel Cell Technology. Fuel Cells. 2004(5): 80-96.
    [77] Sreedhar Reddy Guda, Modeling and Power Management of a Hybrid System Wind-Microturine Power Generation System [Dissertation]. Montana State University, 2005.
    [78] Wang Cai-sheng, Modeling and Control of Hybrid Wind/Photovoltaic/Fuel Cel Distributed Generation Systems [Dissertation], Montana State University, 2006.
    [79] Rambabu Kandepu, Lars Imsland, Christoph Stiller, Control-relevant Modeling and Simulation of a SOFC-GT Hybrid System. Modeling, Identification and Control. 2006(27): 1-14.
    [80]卢立宁.固体氧化物燃料电池与燃气轮机联合发电系统模拟研究.热能动力工程. 2004,19(4): 358-362.
    [81]张兄文,李国君,李军.高温燃料电池/燃气轮机混合循环发电系统.燃气轮机技术.2005,18(1) :24-29
    [82]陈跃华,曹广益,翁一武. MCFC-燃气轮机联合循环系统模拟与优化.热能动力工程. 2006, 21(2):119-123.
    [83]陈启梅,翁一武,朱新坚等.熔融碳酸盐燃料电池-燃气轮机混合动力系统特性分析.中国电机工程学报. 2007, 27(8):130-135.
    [84]张会生,翁史烈,苏明.燃料电池-燃气轮机混合发电装置研究现状.电源技术. 2006,30(2):165-169.
    [85] Jurado, F., Saenz, J.R., Adaptive control of a fuel cell-microturbine hybrid power plant. IEEE Transactions on Energy Conversion. 2003, 18(2):342-347.
    [86] Stiller, C., Thorud, B., Bolland, O., Kandepu, R., Imsland, L., Control strategy for a solid oxide fuel cell and gas turbine hybrid system. Journal of Power Sources. 2006 (158):303-315.
    [87] Kandepu, R., Imsland, L., Foss, B.A., Stiller, C., Thorud, B., Bolland, O., Modeling and control of a SOFC-GT-based autonomous power system. Energy, 2007(32): 406-417.
    [88] Yamaguchi, M., Saito,T., Izumitani, M., Sugita, S., Tsutsumi,Y.. Analysis of control characteristics using fuel cell plant simulator. IEEE Transactions on Industrial Electronics. 1990,37(5): 378-386.
    [89] W. He, Dynamic simulations of molten carbonate fuel cell systems, PhD. Dissertation, Delft university press, 2000
    [90] Xu,J., Froment, G.F., Methane steam reforming, methanation and water–gas shift. I. Intrinsic kinetics. AIChE J. 1989 (35):88-96.
    [91] Cengel,Y.A., Boles, Michael A., Thermodynamics : A Engineering Approach. McGraw-Hill.2005.
    [92] Yuh C.Y., Selman J.R., The polarization of molten carbonate fuel cell electrodes:Ⅰ. Analysis of steady state polarization data. Journal of Electrochemical. 1991(138):3642-3648.
    [93] Analytic Investigation of the Internal Conditions of a Molten Carbonate Fuel Cell Stack, CRIEPI Annual Research Report. 1996:30-31.
    [94] Michael D. Lukas, Kwang Y. Lee, Hossein Ghezel-Ayagh. An Explicit Dynamic Model for Direct Reforming Carbonate Fuel Cell Stack. IEEE TRANSACTIONS ON ENERGYCONVERSION, 2001(16) :289-295.
    [95] Roberts,R. A.,Brouwer, J.,Gemmen,R., and Liese, E., Interlaboratory dynamic modeling of a carbonate fuel cell for hybrid application. Pro.ASME Turbo Expo,Atlanta,Georgia. , 2003 paper no.GT-2003-38774.
    [96] Tanaka, T., Research on On-Site Internal Reforming Molten Carbonate Fuel Cell, International Gas Research Conference, 1989:252-258.
    [97] Farooque, M., Development of Internal Reforming Carbonate Fuel Cell Stack technology, Final Report, DOE/MC /23 274-2941, 1991
    [98] Research and Development on Fuel Cell Power Generation Technology FY1990 Annual Report, NEDO, 1991
    [99] Lee, H.I., Lee C.H., Oh T.Y., Choi S.G., Park I.W., Baek K.K.. Development of 1kW class polymer electrolyte membrane fuel cell power generation system. Journal of Power Sources. 2002(107):110-119.
    [100]张颖颖,60kW PEMFC家用热电联供系统的动态建模与协调控制方法研究[博士论文].上海交通大学博士学位论文,上海交通大学,2006.
    [101]胡蓉,多输出函数回归的SVM算法研究[硕士论文].华南理工大学硕士论文,华南理工,2005.
    [102] Suykens J.A.K., Vandewalle J., Least squares support vector machine classifiers[J]. Neural Processing Letters, 1999, 9(3):293-300.
    [103] Christoph Stiller. Design, operation and control modeling of SOFC/GT hybrid systems[D]. Norwegian University,2006. [104] Deng N.Y.,Zhang C.H., Liu G. L.,et al. Support vector classification with uncertainty. 5th International conference on computer sciences,Metz,France, July 1-3,2004.
    [105] Chang C.C., Lin C.J.. Training v-support vector classifiers: theory and algorithms. Neural Computation,2001(13):2119-2147.
    [106] Yang F., Zhu X.-J., Cao G.-Y., Nonlinear fuzzy modelling of a MCFC stack by an identification method. Journal of Power Sources. 2007,166 (2):354-361.
    [107] Lin C.F., Wang S.D., Fuzzy support vector machines.IEEE Trans.on Neural Networks,2001,13(2):464-471.
    [108] Deng N.Y,Liu G. J., Zhang C. H.. A new version of support vector classification and its application to early warning of food security.OR Transactions,2003,7(1):1-8.
    [109] Zhu Q., Zhu J., Gao F., Design and tuning of a kind of nonlinear PID controller. Chinese Automation in Refined and Chemical Industry. 1997,18 (3) :46-49.
    [110] Jurado F., Saenz J.R., Adaptive control of a fuel cell microturbine hybrid power plant. IEEE Power Engineering Society Summer Meeting. 2002(1):76 -81.
    [111] Layne A., Samuelsen S., Williams M., Hybrid heat engines: the power generation systems of the future, ASME Turbo Expo 2000, 2000-GT-0549.
    [112] Massardo A.F., Mcdonald C. F., Korakianitis T., Microturbine /fuel cell coupling for high-efficiency electrical-power generation, ASME Turbo Expo 2000-GT-175.
    [113]张方伟.中冷回热燃气轮机动态仿真研究[硕士论文].上海:上海交通大学,2004.
    [114]伊亭.燃料电池-燃气轮机联合循环动态仿真研究[硕士论文].上海:上海交通大学.2002.
    [115]郭正榘.燃气轮机自动控制系统设计.北京:机械工业出版社.1986:188-192.
    [116]陈跃华.基于智能方法的熔融碳酸盐燃料电池/微型燃气轮机联合发电系统的建模与控制研究[博士论文].上海:上海交通大学.2007.
    [117]张燕燕.燃料电池与微型燃气轮机混合装置热力性能分析[硕士论文].上海:上海交通大学,2002.
    [118] Kurzke.J., Compressor and turbine maps for gas turbine performance computer programs-Component Map Collection 1,Dachau,Germany,2004
    [119] Pullen K.R., Baines N.C., Hill S.H., The design and evaluation of a high pressure ratio turbine. ASME 1992,paper 92-GT-93.
    [120]陈启梅. MCFC-GT混合动力系统非线性特征的协调控制研究[博士论文].上海:上海交通大学,2007.
    [121]于立军,曹广益,朱新坚,田子平.熔融碳酸盐燃料电池单体实验研究.动力工程. 2003:23(2): 2354-2356.
    [122]于立军,姜秀民,袁俊琪,曹广益.熔融碳酸盐燃料电池动态性能数值模拟.热能动力工程. 2004,19(3): 288-291.
    [123]李乃朝,衣宝廉,张恩俊.不同工作条件下的熔盐燃料电池性能.电源技术, 1997, 21(3):100-113.
    [124] Doyon J., Farooque M., Maru H., The direct fuelcell stack engineering, Journal of Power Sources. 2003(118): 8–13.
    [125] Liese Eric,Gemmen Randall S., Dynamic modelling results of a 1 MW MCFC/GT power system, in: Proceedings of the ASME Turbo Expo 2002, Amsterdam, 3–6 June 2002,
    [126] Roberts Rory A.,Brouwer J.,Liese Eric,Gemmen Randall S.,Dynamic Simulation of Carbonate Fuel Cell-Gas Turbine Hybrid Systems[J]. Journal of Engineering for Gas Turbines and Power,.2006, (128):294-301
    [127] Song, J.G., Zhang, C.N.,Sun,F.C. Structure and control strategies of fuel cell vehicle. Journal of Beijing Institute of Technology, 2004,13(1):63-66.
    [128]李鸿儒,王建辉,顾树生.准对角递归神经网络及其算法的研究[J].系统仿真学报,2004,07:1542—1544.
    [129] Almeida,P.E.M.,Simoes,M.G.Neural optimal control of PEM fuel cells with parametric CMAC networks.IEEE Transactions on Industry Applications,2005,41(1):237-245.
    [130] Panda SK, Lim JMS, Dash PK, Lock KS. Gain scheduled PI speed controller for PMSM Drive. In: Proc. IEEE industrial electronics society international conference IECON’97, vol. 2. 1997: 925–30.
    [131] Mohan N, Undeland TM, Robbins WP. Power Electronics. Converters, Applications, and Design, 2nd Ed. New York: John Wiley & Sons; 1995.
    [132] Mueller F., Brouwer J., Jabbari F., Samuelsen S., Dynamic simulation of an intergrated solid oxide fuel cell system including current-based fuel flow control. Journal of fuel cell science and technology. 2006 (3):144-154
    [133] Gigliucci,G.,Petruzzi,L.,Cerelli,E..Demonstration of a residential CHP system based on PEM fuel cells. Journal of Power Sources,2004,131(1-2):62-68
    [134] Roberts R. A.. A dynamic fuel cell-gas turbine hybrid simulation methodology to establish control strategies and an improved alance of plant[DIssertation]. University of California.2005.
    [135] Grillo O. Design and part load performance of a hybrid system based on a molten carbonate fuel cell-MCFC and a micro gas turbine [D].University of Genoa in Italian,June 2001.
    [136] Tursini M, Parasiliti F, Zhang D. Real time gain tuning of PI controllersfor high performance PMSM drives. IEEE Trans Industry Appl 2002, 38(4):1018–26.
    [137]孙兴进.熔融碳酸盐燃料电池电堆的建模、仿真及控制[博士论文.].上海:上海交通大学. 2002.
    [138] Goldberg F.E. Genetic algorithm in search, optimization and machine learning. Reanding: Addison-Wesley,1989.
    [139] Schaudolph N. N., Belew R. K., Dynamic parameter encoding for genetic algorithms. Machine Learning, 1992,9(6):9-21.
    [140] Schaffer J. D.. Multiple objective optimization with vector evaluated genetic algorithms. In:proc of International Conference on Genetic Algorithm and Their Application, 1985:93-100.
    [141] Hajela P, Lin C Y. Genetic search strategies in multi-criterion optimal design. Structural Optimization, 1992,5(4):99-107.
    [142] Janikow C. Z. A knowledge-intensive genetic algorithms for supervised learing. Machine Learning,1993,13(2-3):189-228.
    [143] Karr C. L. Design of an adaptive fuzzy logic controller using a genetic algorithm. In:Proc of the 4th ICGA,1991:450.
    [144] Karaboga D. Genetic algorithms with variable mutation rates:application to fuzzy logic controller design. Journal of systems and control Engineering, Proc. Instu Mech. Engts,1997,211:157-167.
    [145] Vignaux G A, Michalewicz Z. A genetic algorithm for the linear transporation problem. IEEE trans on systems, Man and Cybernetic,1991,21(2):445-452.
    [146] R.Roberts, J.Brouwer, F.Jabbari,T.Junker, H.Ghzel-Ayagh.Control design of anatmospheric solid oxide fuel cell/gas turbine hybrid system:variable versus fixed speed gas turbine operation, Journal of power sources, 2006,161(1):484-491
    [147] Roubos J A,van Straten G,van Boxtel S J B. An evolutionary strategy for fed-batch bioreactor optimization: concepts and performance. Journal of Biotechnology, 1999,67:173-187.
    [148] T.-I.Choi, K.Y. Lee, S.T.Junker, H.Ghzel-Ayagh. Neural network supervisor for hybrid fuel cell/gas turbine power plants,IEEE power engineering society (PES) general meeting,Tampa,FL, June 24-28,2007.
    [149] Basilio JC, Matos SR. Design of PI and PID controllers with transient performance specification. IEEE Trans Education 2002, 45(4):364–70.
    [150] Mudi RK, Pal NR. A self-tuning fuzzy PI controller. Fuzzy Sets Syst. 2000,115(2):327–38.
    [151] Lee J. On methods for improving performance of PI-type fuzzy logic controllers. IEEE Trans Fuzzy Syst 1993, 1(4):298–301.
    [152] Kulic F, Kukolj D, Levi M. Artificial neural network as a gain scheduled for PI speed controller in DC motor drives. In: Proc. fifth seminar on neural network applications in electrical engineering—NEUREL-2000. 2000.: 199–203.
    [153] Inoue K. An advanced DC brushless servo drive system with a fuzzy logic based self-tuning control scheme and its practical evaluations. Internat J.Electron 1996,80 (2):223–33.
    [154] Rajani K. Mudia, Chanchal Dey, Tsu-Tian Lee. An improved auto-tuning scheme for PI controllers。ISA Transactions. 2008, 47:45–52.
    [155] Fan Yang, Xin-Jian Zhu, Guang-Yi Cao. Development of fuzzy control of a fuel cell generation system using FPGA. BATTERY. 2006, 36(5):405-40

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