摘要翻译：
从单个电机的角度分析系统轨迹，为电力系统暂态稳定分析提供了一个独特的角度。这两篇论文提出了一种基于个体-机器等面积准则的直接时域方法。本文首先通过考察单个机械的轨迹与功率-角度曲线之间的映射关系，阐明了表征临界机械的稳定性。建立了系统轨迹与单机等面积准则之间的映射关系。在此基础上，提出了单机稳定性与系统稳定性的统一原则。证明了只要找到任意一个不稳定临界机，就可以确定系统的不稳定，从而在暂态稳定评估中可以对多机系统的暂态稳定进行单独监测。
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英文标题：
《Transient Stability Assessment Using Individual Machine Equal Area
  Criterion Part I: Unity Principle》
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作者：
Songyan Wang, Non-member, Jilai Yu, Wei Zhang
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最新提交年份：
2017
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分类信息：

一级分类：Electrical Engineering and Systems Science        电气工程与系统科学
二级分类：Signal Processing        信号处理
分类描述：Theory, algorithms, performance analysis and applications of signal and data analysis, including physical modeling, processing, detection and parameter estimation, learning, mining, retrieval, and information extraction. The term "signal" includes speech, audio, sonar, radar, geophysical, physiological, (bio-) medical, image, video, and multimodal natural and man-made signals, including communication signals and data. Topics of interest include: statistical signal processing, spectral estimation and system identification; filter design, adaptive filtering / stochastic learning; (compressive) sampling, sensing, and transform-domain methods including fast algorithms; signal processing for machine learning and machine learning for signal processing applications; in-network and graph signal processing; convex and nonconvex optimization methods for signal processing applications; radar, sonar, and sensor array beamforming and direction finding; communications signal processing; low power, multi-core and system-on-chip signal processing; sensing, communication, analysis and optimization for cyber-physical systems such as power grids and the Internet of Things.
信号和数据分析的理论、算法、性能分析和应用，包括物理建模、处理、检测和参数估计、学习、挖掘、检索和信息提取。“信号”一词包括语音、音频、声纳、雷达、地球物理、生理、（生物）医学、图像、视频和多模态自然和人为信号，包括通信信号和数据。感兴趣的主题包括：统计信号处理、谱估计和系统辨识；滤波器设计；自适应滤波/随机学习；（压缩）采样、传感和变换域方法，包括快速算法；用于机器学习的信号处理和用于信号处理应用的机器学习；网络与图形信号处理；信号处理中的凸和非凸优化方法；雷达、声纳和传感器阵列波束形成和测向；通信信号处理；低功耗、多核、片上系统信号处理；信息物理系统的传感、通信、分析和优化，如电网和物联网。
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一级分类：Computer Science        计算机科学
二级分类：Systems and Control        系统与控制
分类描述：cs.SY is an alias for eess.SY. This section includes theoretical and experimental research covering all facets of automatic control systems. The section is focused on methods of control system analysis and design using tools of modeling, simulation and optimization. Specific areas of research include nonlinear, distributed, adaptive, stochastic and robust control in addition to hybrid and discrete event systems. Application areas include automotive and aerospace control systems, network control, biological systems, multiagent and cooperative control, robotics, reinforcement learning, sensor networks, control of cyber-physical and energy-related systems, and control of computing systems.
cs.sy是eess.sy的别名。本部分包括理论和实验研究，涵盖了自动控制系统的各个方面。本节主要介绍利用建模、仿真和优化工具进行控制系统分析和设计的方法。具体研究领域包括非线性、分布式、自适应、随机和鲁棒控制，以及混合和离散事件系统。应用领域包括汽车和航空航天控制系统、网络控制、生物系统、多智能体和协作控制、机器人学、强化学习、传感器网络、信息物理和能源相关系统的控制以及计算系统的控制。
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英文摘要：
  Analyzing system trajectory from the perspective of individual machines provides a distinctive angle to analyze the transient stability of power systems. This two-paper series propose a direct-time-domain method that is based on the individual-machine equal area criterion. In the first paper, by examining the mapping between the trajectory and power-vs-angle curve of an individual machine, the stability property to characterize a critical machine is clarified. The mapping between the system trajectory and individual-machine equal area criterion is established. Furthermore, a unity principle between the individual-machine stability and system stability is proposed. It is proved that the instability of the system can be confirmed by finding any one unstable critical machine, thence, the transient stability of a multimachine system can be monitored in an individual-machine way in transient stability assessment.
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PDF链接：
https://arxiv.org/pdf/1712.00879