电力系统神经网络逆系统的协调控制

【作者】 胡欣；

【导师】 杨冠鲁；

【作者基本信息】 华侨大学 ， 电工理论与新技术， 2003， 硕士

【摘要】 电力系统运行的稳定性问题是电力系统运行的重要问题。改善与提高电力系统稳定性的主要手段是控制。 本文根据逆系统方法、神经网络方法、最优控制理论及分散协调控制理论的特点，综合运用于电力系统单机、多机系统的稳定控制。 本文首先介绍了逆系统和α阶积分逆系统理论，接着研究了逆系统方法和神经网络监督学习控制理论在单机—无穷大系统励磁控制的综合应用；然后在介绍了神经网络α阶逆系统控制理论后，研究了神经网络逆系统方法在单机—无穷大系统励磁控制中的应用；最后作为本文研究重点，首次将神经网络逆系统方法应用于多机电力系统稳定控制，研究了神经网络逆系统方法在多机系统励磁控制中的应用情况，并结合多机系统最优分散协调控制理论，设计出基于神经网络逆系统方法的多机电力系统分散协调励磁控制器，进行了控制系统仿真和效果分析。 单机和多机系统的仿真结果表明，神经网络α阶逆系统控制方法应用于电力系统控制，对系统运行点和网络结构的变化有良好的适应性，可显著改善系统暂态过程的动态响应，具有较好的控制效果。而且控制结构简单，在无须知道系统的数学模型和具体参数的情况下，即可实现系统的大范围线性化，从而为逆系统方法的工程实现提供了一条有效途径。更多还原

【Abstract】 The stability of power system is a very important problem in its operating processing. The main means of improving stability of power system is by controlling.By combining the idea of inverse system and ANN ath-order inverse system, the optimal control theory and the strategy of decentralized and coordinated control, this paper studies the stability control of one machine and multi-machine power system.In this paper the method of inverse system and ath-order inverse system are introduced, then it studies the application of the method of inverse system and supervised neural controller in the excitation controlling of one machine infinite bus power system. After introducing the method of ANN a th-order inverse system it studies its application in the excitation controlling of one machine system. At last as t the emphasis of this paper, combining the theory of multi-machine decentralized and coordinated control, the method of ANN ath-order inverse system is studied how to be used in the excitation control of multi-machine power system. The multi-machine power system decentralized and coordinated controller is designed and which was based on the method of ANN a th-order inverse system.The simulation results show that: neural ath-order inverse system control method have good adaptability to the running point and network structure’s transformation, improve the stability of power system greatly and have good control performance when it was applied to the stability control of power system. At the same time it has a simple control structure and can linearize the system even it is unnecessary to know mathematical models and actual parameters of original system.更多还原