MLE概率预测智能增强框架下的电力系统暂态稳定性评估  

Power System Transient Stability Assessment Based on Probability Prediction and Intelligent Enhancement of MLE

作　　者：刘嘉诚 刘俊[1] 李雨婷 杜正春[1] 默天啸 林凯威 彭鑫 LIU Jiacheng;LIU Jun;LI Yuting;DU Zhengchun;MO Tianxiao;LIN Kaiwei;PENG Xin(Shaanxi Key Laboratory of Smart Grid(School of Electrical Engineering,Xi’an Jiaotong University),Xi’an 710049,Shaanxi Province,China)

机构地区：[1]陕西省智能电网重点实验室(西安交通大学电气工程学院),陕西省西安市710049

出　　处：《中国电机工程学报》2024年第23期9225-9238,I0009,共15页PROCEEDINGS OF THE CHINESE SOCIETY FOR ELECTRICAL ENGINEERING

基　　金：国家重点研发计划项目(2021YFB2400800)。

摘　　要：准确可靠的暂态稳定性评估对于电力系统安全稳定运行具有重要意义。传统机理性判别方法和判据应用于复杂电力系统时仍然存在困难,人工智能类方法则存在可解释性差等问题。该文基于响应驱动的最大李雅普诺夫指数暂态稳定性判别机理,采用GAT-GRU耦合网络与扩散核密度估计方法对故障后的功角最大李雅普诺夫指数概率分布进行预测,以替代其响应数据计算过程;基于KL散度定义的距离测度,推导其参数梯度计算方法;进而提出一种权重自适应的邻域近似估计方法评估暂态稳定性以替代固定阈值判据。算例结果表明,该文提出的暂态稳定性预测框架能够提升机理判别的适用范围并增强智能方法的结果可解释性,仅依赖少量暂态初期响应信息即可实现稳定性的准确评估。Accurate and reliable transient stability assessment is of great significance for the secure and stable operation of power systems.Traditional theoretical judging methods and criteria still face some difficulties when applied to complex power systems,while problems such as poor interpretability still hold in the artificial intelligence related methods.In this paper,based on response-driven maximum Lyapunov exponent induced transient stability judgment mechanism,GAT-GRU coupled network and diffusion kernel density estimation methods are used to predict the probability distribution of maximum Lyapunov exponent to replace the calculation process.The gradient computation algorithm is deduced for KL divergence-based distance measurement.Then,neighborhood approximation estimation with adaptive weights is proposed as stability metrics of probability distribution in substitution of fixed threshold criterion.Results from case studies show that the framework of TSA proposed in this paper can improve the applicability of theoretical judging methods as well as enhance the interpretability of intelligent methods,which is able to realize accurate transient stability judgments with a very small amount of initial transient response information.

关 键 词：暂态稳定性 响应驱动 最大李雅普诺夫指数 智能增强 扩散核密度估计 邻域近似估计 

分 类 号：TM712[电气工程—电力系统及自动化]