电力系统暂态稳定问题和迭代学习控制的研究

提出暂态稳定是解决电力系统稳定问题的重点，由于电力系统的非线性，模型和干扰 的不确定，寻找较少依赖于数学模型、具有较强适应性的控制策略是电力系统稳定控制的 重要课题。例如，在特定的条件下，重要的FACTS装置STATCOM如控制不当，则有可能出现负 阻尼现 象，诱发系统振荡。将迭代学习控制方法应用到FACTS装置的阻尼振荡控制中，对系统的各 种运行点具有很好的适应性，并可自动消除负阻尼的出现。同时证明了这种控制方法用于两 种FACTS装置的收敛性。仿真结果表明迭代学习控制法与常规PI控制相比，在很多情况下具 有较好的适应性。

A NEW ATTEMPT OF USING ITERATIVE LEARNING CONTROL IN SOLVING POWER SYSTEM TRANSIENT STABILITY PROBLEM

Transient stability is the key problem of power system stability research. Power system is a nonlinear complex system with uncertainty in both mathematical model and disturbances, so it is important to find an adaptive control strategy independent of the detailed model. In some load conditions, negative damping will appear and oscillation will be deteriorated if the controller of STATCOM is short of adaptability. Iterative learning control (ILC) is used as the supplementary control method of FACTS controller to damp inter-area oscillation for the first time. The convergence of the used algorithm is proved. The digital simulation results both on TCSC and STATCOM prove that ILC is more adaptive than the traditional fixed-gain control in FACTS device control.