固体氧化物燃料电池/微型燃气轮机混合发电系统的建模与控制
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摘要
固体氧化物燃料电池/微型燃气轮机(SOFC/MGT)混合发电是一种高效、环保的新型发电技术，在未来的分布式发电领域具有广阔的应用前景。然而目前，该技术在国外处于示范电站阶段，国内的相应研究才刚刚起步，尚无实际的系统设备。
因此，本文以仿真技术为研究手段，在参考国内外混合发电系统研究经验的基础上，对SOFC/MGT混合发电系统进行动态建模、性能分析、动态优化和综合控制，最终使所设计的系统在稳定、高效运行的同时良好满足负荷用电需求，为SOFC/MGT混合发电系统的实际开发和应用提供必要的技术准备和理论指导。主要研究工作包括以下三个方面：
1.建立了SOFC/MGT混合发电系统的动态模型。首先，根据西门子-西屋动力公司建立的混合发电系统示范装置，结合现有的相关文献和实际操作经验，确定了阳极再循环SOFC/MGT混合发电系统的顶层循环式拓扑结构。然后，针对系统结构庞大、参数繁多和性能复杂等特点，采用了灵活的模块化建模思想，根据理想气体状态方程、质量平衡方程、能量平衡方程、热动力学公式和电功率的转换关系，在MATLAB/SIMULINK仿真环境里，逐级搭建构成混合系统的各个子系统模型，包含阳极再循环SOFC各部件模型、微型燃气轮机各部件模型和电管理系统各部件模型。最后，按照混合发电系统的拓扑结构连接各子系统模型，建立了完整的SOFC/MGT混合发电系统动态模型。经仿真验证，所建立的混合系统动态模型能够正确反映系统的稳态和动态特性，因此该系统模型可作为系统性能分析、动态优化和控制研究的有效工具。同时，该混合发电系统动态模型可方便修改系统的部分结构设计和参数设置，因此不仅适用于本文所设计的拓扑结构系统的仿真研究，而且通过简单修改也适用于其它类似混合发电系统的开发和研究，具有广泛的适用性。
2.研究了SOFC/MGT混合发电系统运行参数的动态优化问题。目前混合发电系统大多处于试验探索阶段，研究者普遍着眼于过程设计优化，即在指定的目标函数下，通过特定的寻优方法确定最优混合结构，寻找最佳能量循环利用方式，而对最佳运行参数的研究却非常少。因此，本文首先针对混合发电系统的动态优化问题，将迭代思想与自适应免疫粒子群优化方法相结合，设计了改进的迭代粒子群优化算法。改进的迭代粒子群优化算法首先将变量离散化，用改进的粒子群优化算法搜索离散控制变量的最优值，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迹在迭代过程中不断趋于最优解。通过大量实例验证了该优化算法的有效性。然后，利用该改进的迭代粒子群优化算法对SOFC/MGT混合系统动态优化模型进行优化，得到了不同负荷下的最优运行参数值。混合系统动态优化模型的建立是以系统输出功率跟随负荷要求及系统效率最大为优化的目标函数，以混合发电系统的动态模型及系统安全运行的具体要求为约束条件。最后，将运行参数的优化结果代入混合系统动态模型中，便得到了不同负荷下SOFC输出功率的最优运行轨迹，该优化轨迹作为系统功率控制的最优设定值，进行闭环优化控制。
3.提出并验证了混合发电系统稳定运行的综合控制方法。目前文献对混合发电系统的控制研究主要针对单一子系统或单一变量，缺乏对整个系统的综合控制研究。由于系统的强非线性动态特性和多参数耦合的特点，只有通过综合控制使其运行时实现所有要求的性能指标才具有实际的应用意义。因此，本文以建立的SOFC/MGT混合发电系统动态模型为对象，结合系统性能分析结果及动态优化结果，完成了混合发电系统稳定运行的综合控制研究。针对混合发电系统的复杂性，采用分块处理再整合的控制方法。首先，对影响系统性能的各操作参数及电管理系统分别进行了独立的控制设计和仿真，其中包括：利用改进的神经网络预测控制方法对混合发电系统输出功率进行了跟踪控制；利用基于动态RBF神经网络的PID解耦控制方法对混合发电温度系统进行了解耦控制；利用改进的单神经元自适应PID控制方法将燃料利用率稳定在了理想水平；利用滑模变结构控制方法将SOFC输出电压转换成了理想幅值的交流电压。在对混合发电系统输出功率控制时，利用改进的迭代粒子群优化算法离线动态优化获取的运行轨迹数据，建立了基于最小二乘支持向量机的函数逼近层，实现了根据系统负荷情况实时给出SOFC输出功率的最优设定值。最后，将各独立控制环节连接起来进行了完整的综合控制研究。在阶跃负荷情况下，仿真结果显示所设计的控制方案使SOFC/MGT混合发电系统在实时稳定运行中满足了负荷的用电要求，并且具有高效的发电效率。
The solid oxide fuel cell/micro gas turbine(SOFC/MGT) hybrid power generation systemis an advanced efficiency and environmentally-friendly novel power generation technology,which has a wide application prospect in the field of future distributed generation. However,at present the demonstration hybrid power plant has been developed abroad. In China thehybrid system is still in the early research stage, and the practical equipment for the systemhas not been built.
Therefore, according to some experience on the hybrid power generation system in theworld, a dynamic model is established firstly, and then the performance simulation analysisand dynamic optimization are carried on, lastly the integral control strategy for theSOFC/MGT hybrid power generation system is researched in the dissertation. By simulationanalysis, the SOFC/MGT hybrid power generation system can operate steadily and meet theload power requirements with high efficiency. The dissertation can provide valuable theoryinstructions for developments and applications of real hybrid power generation system. Themain contributions and achievements of this dissertation are given below:
1. Establish the dynamic model of a SOFC/MGT hybrid power generation system. Firstly,according to the demonstration device built by the Siemens Westinghouse Power, thepertinent literatures and practical operating experience, the topping cycle topologicalstructure is designed for an anode recirculation SOFC/MGT hybrid power generationsystem. And then, for the heavy structure, many performance parameters and complexcharacteristics, the dynamic model is established by modularization modelling method.According to the ideal gas equation, mass conservation law, energy conservation law,thermodynamics formula and electric power conversion, the components models of ananode recirculation SOFC, micro gas turbine and a power conditioning system are builtrespectively in MATLAB/SIMULINK environment. Lastly, according to the designedtopological structure, each submodular is connected to make up of the integrateddynamic model for the whole hybrid power generation system. The simulation results show that the model is able to reflect the steady and dynamic characteristics of the hybridsystem correctly, so it can be used in the performance analysis, dynamic optimizationand control design of the hybrid system. Moreover, owing to the part structures andparameters easily modified, the dynamic model of the hybrid system possesses thegeneral applicability. It can be used not only for the designed topological structure in thesimulation research, but also for the other researches of similar hybrid power generationsystems by simply changing.
2. The dynamic optimization problem of operating parameters for the SOFC/MGT hybridpower is introduced in detail. At present, the researches mainly focus on the processdesign optimization. The optimal hybrid structure and circulation mode are determinedby special optimization method. However, research about the optimal operatingparameter is very little. For the dynamic optimization of the hybrid system, firstly, anovel iteration partial swarm optimization (PSO) algorithm is proposed, which is madeup of iteration dynamic programming and adaptive immune particle swarm optimization.For the algorithm, firstly the control variables are discretized and the improved particleswarm optimization is used to search for the best solution of the discretized controlvariables. And then the benchmark is moved to the acquired optimal values in thesubsequent iterations and the searching space contracts at the same time, hence theoptimization performance index and control profile could achieve the best valvegradually through iterations. The optimization algorithm is proved to be effective by alarge number of examples. According to the designed dynamic optimization model of thehybrid power generation system, the novel iteration PSO algorithm can calculate theoptimal operating parameters. Tracking the demanded load and obtaining the highestgenerating efficiency are the goal function, and the dynamic model and safe operationrequest are the constraints of the dynamic optimization model for the hybrid system.Lastly, substituting the optimal parameters into the established dynamic model of thehybrid system, the optimal SOFC output power trajectory can be obtained, which acts asthe SOFC output power setpoints in order to closed loop optimized control.
3. The integral control design is proposed and tested for the SOFC/MGT hybrid powergeneration system. At present, documents focus on controlling the specific performancesof hybrid system, and the integrated control research is lack. But for the close nonlineardynamic characteristics and some parameters couplings of the system, it is significant forreal applications that the system is controlled to operate steadily with all idealperformances.Therefore, according to the performance analysis and dynamicoptimization results, the integrated control design is proposed and tested for the hybridsystem based on the dynamic model.In this dissertation, for the complex characteristics of the hybrid system, the system control is separated to some processes. An improvedneural network predictive controller is designed for tracking the system output power. APID decoupling controller based on a dynamic RBF neural network is put forward forsystem temperature decoupling control. An improved single-neural unit adaptive PIDcontroller is utilized for steady fuel utilization.The SOFC output voltage is transformed toan ideal amplitude alternate current voltage by sliding mode variable structure controlmethod. During the power control, the optimal operation trajectory results obtained fromthe improved iteration PSO algorithm are successfully modeled and predicted by meansof the least squares support vector machine. This facilitates the optimal SOFC outputpower setpoints under various loads. And then, these above controlled processes areintegrated to realize the integral control research of the SOFC/MGT hybrid powergeneration system. Under the step power loads, the simulation results show that the mainoperation parameters are kept in the ideal steady state, and the hybrid system can track thedesired power with high system efficiency.
因此，本文以仿真技术为研究手段，在参考国内外混合发电系统研究经验的基础上，对SOFC/MGT混合发电系统进行动态建模、性能分析、动态优化和综合控制，最终使所设计的系统在稳定、高效运行的同时良好满足负荷用电需求，为SOFC/MGT混合发电系统的实际开发和应用提供必要的技术准备和理论指导。主要研究工作包括以下三个方面：
1.建立了SOFC/MGT混合发电系统的动态模型。首先，根据西门子-西屋动力公司建立的混合发电系统示范装置，结合现有的相关文献和实际操作经验，确定了阳极再循环SOFC/MGT混合发电系统的顶层循环式拓扑结构。然后，针对系统结构庞大、参数繁多和性能复杂等特点，采用了灵活的模块化建模思想，根据理想气体状态方程、质量平衡方程、能量平衡方程、热动力学公式和电功率的转换关系，在MATLAB/SIMULINK仿真环境里，逐级搭建构成混合系统的各个子系统模型，包含阳极再循环SOFC各部件模型、微型燃气轮机各部件模型和电管理系统各部件模型。最后，按照混合发电系统的拓扑结构连接各子系统模型，建立了完整的SOFC/MGT混合发电系统动态模型。经仿真验证，所建立的混合系统动态模型能够正确反映系统的稳态和动态特性，因此该系统模型可作为系统性能分析、动态优化和控制研究的有效工具。同时，该混合发电系统动态模型可方便修改系统的部分结构设计和参数设置，因此不仅适用于本文所设计的拓扑结构系统的仿真研究，而且通过简单修改也适用于其它类似混合发电系统的开发和研究，具有广泛的适用性。
2.研究了SOFC/MGT混合发电系统运行参数的动态优化问题。目前混合发电系统大多处于试验探索阶段，研究者普遍着眼于过程设计优化，即在指定的目标函数下，通过特定的寻优方法确定最优混合结构，寻找最佳能量循环利用方式，而对最佳运行参数的研究却非常少。因此，本文首先针对混合发电系统的动态优化问题，将迭代思想与自适应免疫粒子群优化方法相结合，设计了改进的迭代粒子群优化算法。改进的迭代粒子群优化算法首先将变量离散化，用改进的粒子群优化算法搜索离散控制变量的最优值，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迹在迭代过程中不断趋于最优解。通过大量实例验证了该优化算法的有效性。然后，利用该改进的迭代粒子群优化算法对SOFC/MGT混合系统动态优化模型进行优化，得到了不同负荷下的最优运行参数值。混合系统动态优化模型的建立是以系统输出功率跟随负荷要求及系统效率最大为优化的目标函数，以混合发电系统的动态模型及系统安全运行的具体要求为约束条件。最后，将运行参数的优化结果代入混合系统动态模型中，便得到了不同负荷下SOFC输出功率的最优运行轨迹，该优化轨迹作为系统功率控制的最优设定值，进行闭环优化控制。
3.提出并验证了混合发电系统稳定运行的综合控制方法。目前文献对混合发电系统的控制研究主要针对单一子系统或单一变量，缺乏对整个系统的综合控制研究。由于系统的强非线性动态特性和多参数耦合的特点，只有通过综合控制使其运行时实现所有要求的性能指标才具有实际的应用意义。因此，本文以建立的SOFC/MGT混合发电系统动态模型为对象，结合系统性能分析结果及动态优化结果，完成了混合发电系统稳定运行的综合控制研究。针对混合发电系统的复杂性，采用分块处理再整合的控制方法。首先，对影响系统性能的各操作参数及电管理系统分别进行了独立的控制设计和仿真，其中包括：利用改进的神经网络预测控制方法对混合发电系统输出功率进行了跟踪控制；利用基于动态RBF神经网络的PID解耦控制方法对混合发电温度系统进行了解耦控制；利用改进的单神经元自适应PID控制方法将燃料利用率稳定在了理想水平；利用滑模变结构控制方法将SOFC输出电压转换成了理想幅值的交流电压。在对混合发电系统输出功率控制时，利用改进的迭代粒子群优化算法离线动态优化获取的运行轨迹数据，建立了基于最小二乘支持向量机的函数逼近层，实现了根据系统负荷情况实时给出SOFC输出功率的最优设定值。最后，将各独立控制环节连接起来进行了完整的综合控制研究。在阶跃负荷情况下，仿真结果显示所设计的控制方案使SOFC/MGT混合发电系统在实时稳定运行中满足了负荷的用电要求，并且具有高效的发电效率。
The solid oxide fuel cell/micro gas turbine(SOFC/MGT) hybrid power generation systemis an advanced efficiency and environmentally-friendly novel power generation technology,which has a wide application prospect in the field of future distributed generation. However,at present the demonstration hybrid power plant has been developed abroad. In China thehybrid system is still in the early research stage, and the practical equipment for the systemhas not been built.
Therefore, according to some experience on the hybrid power generation system in theworld, a dynamic model is established firstly, and then the performance simulation analysisand dynamic optimization are carried on, lastly the integral control strategy for theSOFC/MGT hybrid power generation system is researched in the dissertation. By simulationanalysis, the SOFC/MGT hybrid power generation system can operate steadily and meet theload power requirements with high efficiency. The dissertation can provide valuable theoryinstructions for developments and applications of real hybrid power generation system. Themain contributions and achievements of this dissertation are given below:
1. Establish the dynamic model of a SOFC/MGT hybrid power generation system. Firstly,according to the demonstration device built by the Siemens Westinghouse Power, thepertinent literatures and practical operating experience, the topping cycle topologicalstructure is designed for an anode recirculation SOFC/MGT hybrid power generationsystem. And then, for the heavy structure, many performance parameters and complexcharacteristics, the dynamic model is established by modularization modelling method.According to the ideal gas equation, mass conservation law, energy conservation law,thermodynamics formula and electric power conversion, the components models of ananode recirculation SOFC, micro gas turbine and a power conditioning system are builtrespectively in MATLAB/SIMULINK environment. Lastly, according to the designedtopological structure, each submodular is connected to make up of the integrateddynamic model for the whole hybrid power generation system. The simulation results show that the model is able to reflect the steady and dynamic characteristics of the hybridsystem correctly, so it can be used in the performance analysis, dynamic optimizationand control design of the hybrid system. Moreover, owing to the part structures andparameters easily modified, the dynamic model of the hybrid system possesses thegeneral applicability. It can be used not only for the designed topological structure in thesimulation research, but also for the other researches of similar hybrid power generationsystems by simply changing.
2. The dynamic optimization problem of operating parameters for the SOFC/MGT hybridpower is introduced in detail. At present, the researches mainly focus on the processdesign optimization. The optimal hybrid structure and circulation mode are determinedby special optimization method. However, research about the optimal operatingparameter is very little. For the dynamic optimization of the hybrid system, firstly, anovel iteration partial swarm optimization (PSO) algorithm is proposed, which is madeup of iteration dynamic programming and adaptive immune particle swarm optimization.For the algorithm, firstly the control variables are discretized and the improved particleswarm optimization is used to search for the best solution of the discretized controlvariables. And then the benchmark is moved to the acquired optimal values in thesubsequent iterations and the searching space contracts at the same time, hence theoptimization performance index and control profile could achieve the best valvegradually through iterations. The optimization algorithm is proved to be effective by alarge number of examples. According to the designed dynamic optimization model of thehybrid power generation system, the novel iteration PSO algorithm can calculate theoptimal operating parameters. Tracking the demanded load and obtaining the highestgenerating efficiency are the goal function, and the dynamic model and safe operationrequest are the constraints of the dynamic optimization model for the hybrid system.Lastly, substituting the optimal parameters into the established dynamic model of thehybrid system, the optimal SOFC output power trajectory can be obtained, which acts asthe SOFC output power setpoints in order to closed loop optimized control.
3. The integral control design is proposed and tested for the SOFC/MGT hybrid powergeneration system. At present, documents focus on controlling the specific performancesof hybrid system, and the integrated control research is lack. But for the close nonlineardynamic characteristics and some parameters couplings of the system, it is significant forreal applications that the system is controlled to operate steadily with all idealperformances.Therefore, according to the performance analysis and dynamicoptimization results, the integrated control design is proposed and tested for the hybridsystem based on the dynamic model.In this dissertation, for the complex characteristics of the hybrid system, the system control is separated to some processes. An improvedneural network predictive controller is designed for tracking the system output power. APID decoupling controller based on a dynamic RBF neural network is put forward forsystem temperature decoupling control. An improved single-neural unit adaptive PIDcontroller is utilized for steady fuel utilization.The SOFC output voltage is transformed toan ideal amplitude alternate current voltage by sliding mode variable structure controlmethod. During the power control, the optimal operation trajectory results obtained fromthe improved iteration PSO algorithm are successfully modeled and predicted by meansof the least squares support vector machine. This facilitates the optimal SOFC outputpower setpoints under various loads. And then, these above controlled processes areintegrated to realize the integral control research of the SOFC/MGT hybrid powergeneration system. Under the step power loads, the simulation results show that the mainoperation parameters are kept in the ideal steady state, and the hybrid system can track thedesired power with high system efficiency.
引文
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