基于径向基函数网络的暂态稳定极限估计与预防控制

应用径向基函数网络进行电力系统中关键线路暂态稳定极限功率的在线估计，并结合训练后径向基函数网络所包含的输出对输入的偏导信息。提出了一种暂态稳定预防控制决策的方法。山东烟台一威海电网的实例仿真结果表明：径向基函数网络能够准确估计暂态稳定极限，包括关键线路极限功率和发电厂出力极限；所产生的预防控制决策可以防止发生预想事故后系统失稳，有效提高系统的暂态稳定性。

TRANSIENT STABILITY LIMIT ESTIMATION AND PREVENTIVE CONTROL BASED ON RADIAL BASIS FUNCTION NETWORKS

A preventive control decision-making method for transient stability is proposed. Radial basis function networks are applied to on-line estimation of transient stability limits of critical lines in a power system. Partial derivatives of the trained radial basis function networks' outputs to inputs are also used to make preventive control decisions. Simulation results of a real power system show that radial basis function networks are precise in estimation of transient stability limits including power transfer limits on critical lines and power generation limits of related power plants. Preventive control decisions made can prevent the power system from losing transient stability after contingencies so as to improve transient stability effectively.