用于电力系统稳定性分析的神经-解析能量函数
Neural-Analytica Energy Functions for Power System Stability Analysis
- School of Electrical and Electronic Engineering, Nanyang Technological University（南洋理工大学电气与电子工程学院）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本文提出一种神经-解析能量函数，结合神经网络与解析EF，用于电力系统稳定性分析，并通过迭代训练和定制损失函数实现，数值结果验证其优越性。
AI中文摘要：
本文提出了一种新型能量函数（EF），称为神经-解析EF，用于电力系统的稳定性分析。神经-解析EF被设计为基于神经网络（NNs）的组件与解析EF之和，其结构受现有解析推导的EF启发。因此，它结合了神经网络的表达能力与解析EF的泛化性和可扩展性。通过使用定制损失函数进行迭代神经网络训练，进一步推导出满意的神经-解析EF。数值结果最终证明了其优越性。
英文摘要：
This letter proposes a novel form of energy function (EF), called neural-analytic EF, for the stability analysis of power systems. The neural-analytic EF is designed as the sum of neural networks (NNs)-based components and an analytic EF, with the structure informed by the existing EFs derived analytically. It thus integrates NN's expressivity with the generalizability and scalability of analytic EFs. The satisfactory neural-analytic EF is further derived by iterative NN training with a tailored loss function. Numerical results finally demonstrate its superiority.
