发电机组灰色预测可拓控制方法研究
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摘要
现代电力系统的快速发展在带来巨大经济效益的同时,也使得电力系统的稳定问题日趋复杂和严重。作为提高电力系统稳定运行能力、改善电力系统稳定性的重要措施,发电机组励磁控制和调速控制得到了广泛应用。鉴于已有控制策略的缺点和局限性,开展新型的发电机组励磁和调速控制方法的研究仍具有重要和现实的意义。
本文对电力系统稳定控制的研究现状进行了综述和分析。认为:由于电力系统具有维数高、工况时变、非线性强等特点,采用常规线性控制方法难以取得令人满意的控制效果,而各种基于现代控制理论的非线性控制方法算法复杂、实时性差,模糊控制和神经网络控制方法规则库或知识库设计复杂、工程实用性较差。灰色预测控制是一种事前控制方法,可拓控制方法不要求建立精确的数学模型,且实时性好,二者的有机结合将可能获得更好的控制效果。
作为结合灰色预测和可拓控制方法的基础,简述了灰色预测的基本原理,针对灰色预测原始数据含负数的情况,采用一种原理简单且易于实现的数据变换方法对含负数的原始数据进行变换,算例表明了其有效性;简述了可拓方法的基本概念,在此基础上把自然界普遍存在的对偶性纳入物元的可拓性范畴,提出了基于物元对偶性的可拓方法——相似偶方法,并用实例证明了该方法可以将未知矛盾问题的求解转化为另一已知问题的求解,为复杂问题的解决提供了一条可能途径。
为结合灰色预测方法和可拓控制技术的优点,本文提出了一种基于灰色预测的可拓控制(GPEC)方法,给出了灰色预测可拓控制器的设计过程,并应用论文提出的一种具有较高搜索速度和精度的首尾轮换交叉(HTAC)遗传算法对控制器的参数进行优化。线性系统、时滞系统和非线性系统仿真表明,与采用PID、可拓控制方式相比,GPEC控制方式可以改善系统的动态性能。
本文将GPEC方法应用于发电机组励磁、调速、励磁调速综合控制器的设计。所设计的GPEC励磁控制器以发电机机端电压作为灰色预测环节的输入,连续采集5个数据进行灰色预测,输出作为可拓控制器的特征量。GPEC调速控制器的设计利用调速控制系统与励磁控制系统之间存在的对偶性,在已设计的GPEC励磁控制器的基础上,应用本文提出的相似偶方法直接进行,简化了设计过程。在设计励磁调速综合GPEC控制器时,针对传统可拓控制器无法应用于多变量系统的问题,提出了一种多输入-多输出可拓控制器,并基于此方法设计了综合控制器。
本文采用时域仿真法对所设计的GPEC励磁、调速、励磁调速综合控制器的控制效果进行检验。分别以单机无穷大系统和多机电力系统为对象,使用适当的数学模型,研究所设计控制器在系统不同初始工况下对大、小扰动稳定性的影响。仿真结果表明:与常规控制方式相比,基于可拓控制策略的控制器具有较好的控制效果;加入灰色预测后,控制器的性能得到了进一步提高;无论对运行工况变化,还是对模型精确程度以及扰动大小,GPEC控制方式均具有较强的鲁棒性。
The rapid development of modern power system brings good economic returns, but at the same time, it makes the stability problem of power system more complicated and serious. As the important measures to improve stable operation ability and to enhance power system stability, excitation system controller and governor controller of generator unit have been widely used. In view of shortcomings and limitations of existing control methods, the study on new control strategy for generator unit is still important and realistic.
By the reviewing and analyzing about the study status quo of power system stability control, it is achieved that the conventional linear control methods are disillusionary because of the excessive dimensions, diverse operating modes and intense nonlinearity of modern power system, all kinds of nonlinear control methods based on modern control theory are discouraging because of the complex algorithms and poor real-time operation, and fuzzy control and neural network control are not satisfied because the design of rules or knowledge base is complex and the engineering practicality are poor. Grey prediction control is a pre-control methods, and extension control is a real-time method which does not require accurate mathematical model. The organic integration of two methods will get better control effects.
As a base combining grey prediction and extension control method, the basic principles of grey prediction are introduced in brief. For the original raw data containing negatives, a simple and easy-to-realize transform method is used, and an example shows the effectiveness of the method. The extension methods are introduced in brief. On this basis, the widespread duality in nature is brought into matter-element category and an extension method namely analogical-dual based on the duality of matter-element is produced. An example shows that the method can translate the solving of an unknown incompatible problem into the solution of another known problem, so as to provide a possible way to solve the complex problem.
In order to combine the advantages of grey prediction method and extension control technology, a grey prediction-based extension control (GPEC) method is proposed. The controller design process is given. A modified genetic algorithm (GA) which can enhance the search speed and accuracy is applied to optimize the controller parameters. The simulation study respectively on linear system, time-lag system and nonlinear system indicate that GPEC control method can improve the dynamic performance compared with PID and extension control method.
The GPEC method is applied to design excitation system controller, governing controller and integrated controller of generator set. The terminal voltage of generator is taken as the input of grey predictor of GPEC excitation controller, 5 data are gathered continuously to carry on grey prediction, and the output is taken as the characteristic variable of extension controller. With the duality which exists between governing control system and excitation control system, the GPEC governing controller is designed directly by using the proposed analogical-dual method, which simplified the design process. A multi-input multi-output extension controller is proposed in view of the shortcoming of traditional extension controller which is unable to apply in multi-variable system, and the controller integrating governing and excitation system is designed based on this method
The time-domain simulation method is applied to examine the control effects of excitation, governing and integrated controller designed by GPEC method. A single-machine infinite-bus power system and a multi-machine system are taken as the object and suitable mathematical models are used to study the controller’s effects for large disturbance and small signal under different initial operating modes. The simulation results indicated that the extension controller has good control effect comparing with conventional method, controller's performance is further enhanced after joining the grey prediction and the GPEC control method always has strong robustness in operating condition, model precise degree and the perturbation size.
本文对电力系统稳定控制的研究现状进行了综述和分析。认为:由于电力系统具有维数高、工况时变、非线性强等特点,采用常规线性控制方法难以取得令人满意的控制效果,而各种基于现代控制理论的非线性控制方法算法复杂、实时性差,模糊控制和神经网络控制方法规则库或知识库设计复杂、工程实用性较差。灰色预测控制是一种事前控制方法,可拓控制方法不要求建立精确的数学模型,且实时性好,二者的有机结合将可能获得更好的控制效果。
作为结合灰色预测和可拓控制方法的基础,简述了灰色预测的基本原理,针对灰色预测原始数据含负数的情况,采用一种原理简单且易于实现的数据变换方法对含负数的原始数据进行变换,算例表明了其有效性;简述了可拓方法的基本概念,在此基础上把自然界普遍存在的对偶性纳入物元的可拓性范畴,提出了基于物元对偶性的可拓方法——相似偶方法,并用实例证明了该方法可以将未知矛盾问题的求解转化为另一已知问题的求解,为复杂问题的解决提供了一条可能途径。
为结合灰色预测方法和可拓控制技术的优点,本文提出了一种基于灰色预测的可拓控制(GPEC)方法,给出了灰色预测可拓控制器的设计过程,并应用论文提出的一种具有较高搜索速度和精度的首尾轮换交叉(HTAC)遗传算法对控制器的参数进行优化。线性系统、时滞系统和非线性系统仿真表明,与采用PID、可拓控制方式相比,GPEC控制方式可以改善系统的动态性能。
本文将GPEC方法应用于发电机组励磁、调速、励磁调速综合控制器的设计。所设计的GPEC励磁控制器以发电机机端电压作为灰色预测环节的输入,连续采集5个数据进行灰色预测,输出作为可拓控制器的特征量。GPEC调速控制器的设计利用调速控制系统与励磁控制系统之间存在的对偶性,在已设计的GPEC励磁控制器的基础上,应用本文提出的相似偶方法直接进行,简化了设计过程。在设计励磁调速综合GPEC控制器时,针对传统可拓控制器无法应用于多变量系统的问题,提出了一种多输入-多输出可拓控制器,并基于此方法设计了综合控制器。
本文采用时域仿真法对所设计的GPEC励磁、调速、励磁调速综合控制器的控制效果进行检验。分别以单机无穷大系统和多机电力系统为对象,使用适当的数学模型,研究所设计控制器在系统不同初始工况下对大、小扰动稳定性的影响。仿真结果表明:与常规控制方式相比,基于可拓控制策略的控制器具有较好的控制效果;加入灰色预测后,控制器的性能得到了进一步提高;无论对运行工况变化,还是对模型精确程度以及扰动大小,GPEC控制方式均具有较强的鲁棒性。
The rapid development of modern power system brings good economic returns, but at the same time, it makes the stability problem of power system more complicated and serious. As the important measures to improve stable operation ability and to enhance power system stability, excitation system controller and governor controller of generator unit have been widely used. In view of shortcomings and limitations of existing control methods, the study on new control strategy for generator unit is still important and realistic.
By the reviewing and analyzing about the study status quo of power system stability control, it is achieved that the conventional linear control methods are disillusionary because of the excessive dimensions, diverse operating modes and intense nonlinearity of modern power system, all kinds of nonlinear control methods based on modern control theory are discouraging because of the complex algorithms and poor real-time operation, and fuzzy control and neural network control are not satisfied because the design of rules or knowledge base is complex and the engineering practicality are poor. Grey prediction control is a pre-control methods, and extension control is a real-time method which does not require accurate mathematical model. The organic integration of two methods will get better control effects.
As a base combining grey prediction and extension control method, the basic principles of grey prediction are introduced in brief. For the original raw data containing negatives, a simple and easy-to-realize transform method is used, and an example shows the effectiveness of the method. The extension methods are introduced in brief. On this basis, the widespread duality in nature is brought into matter-element category and an extension method namely analogical-dual based on the duality of matter-element is produced. An example shows that the method can translate the solving of an unknown incompatible problem into the solution of another known problem, so as to provide a possible way to solve the complex problem.
In order to combine the advantages of grey prediction method and extension control technology, a grey prediction-based extension control (GPEC) method is proposed. The controller design process is given. A modified genetic algorithm (GA) which can enhance the search speed and accuracy is applied to optimize the controller parameters. The simulation study respectively on linear system, time-lag system and nonlinear system indicate that GPEC control method can improve the dynamic performance compared with PID and extension control method.
The GPEC method is applied to design excitation system controller, governing controller and integrated controller of generator set. The terminal voltage of generator is taken as the input of grey predictor of GPEC excitation controller, 5 data are gathered continuously to carry on grey prediction, and the output is taken as the characteristic variable of extension controller. With the duality which exists between governing control system and excitation control system, the GPEC governing controller is designed directly by using the proposed analogical-dual method, which simplified the design process. A multi-input multi-output extension controller is proposed in view of the shortcoming of traditional extension controller which is unable to apply in multi-variable system, and the controller integrating governing and excitation system is designed based on this method
The time-domain simulation method is applied to examine the control effects of excitation, governing and integrated controller designed by GPEC method. A single-machine infinite-bus power system and a multi-machine system are taken as the object and suitable mathematical models are used to study the controller’s effects for large disturbance and small signal under different initial operating modes. The simulation results indicated that the extension controller has good control effect comparing with conventional method, controller's performance is further enhanced after joining the grey prediction and the GPEC control method always has strong robustness in operating condition, model precise degree and the perturbation size.
引文
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