摘要：

应用一种信息融合模型对电力系统暂态稳定进行分类评估。当电力系统发生故障时，采用该方法可以综合来自电网和发电机的多个信息源对电力系统的暂态稳定进行判别。利用D-S证据理论实现决策级融合，从而提高电力系统暂态稳定评估的可靠性。10机39节点系统被用来进行仿真研究，结果表明，提出的模型比原有的模型更有效。

关键词: 信息融合, 人工神经网络, D-S证据理论, 暂态稳定评估, 轨迹灵敏度

Abstract:

A power system transient stability assessment method is proposed based on an information fusion model. When accidents occur, much information obtained from power networks and generators is synthesized to diagnose power system transient stability by the method. D-S evidence theory is fused for further reducing the uncertainty of transient stability assessment. A 10-generator and 39-bus power system is simulated. The simulation result indicates that the proposed method is more precise than the old methods.

Key words: information fusion, artificial neural network, D-S evidence theory, transient stability assessment, trajectory sensitivity

中图分类号: 

• TP301