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State-space system identification-toward MIMO models for modal analysis and optimization of bulk power systems

机译:用于大功率系统模态分析和优化的状态空间系统识别-MIMO模型

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This paper provides an introduction to a reduced-order, small-signal identification approach to modal analysis and control of large power systems. Being based on system-wide responses to low-energy pulse excitations generated using conventional time-domain simulation software such as PSS/E or EMTSP, it readily takes full advantage of the large built-in model database. The proposed multi-input-multi-output (MIMO) minimal realization reveals naturally the dominant modes attached specifically to a given device, as well as the transfer functions relating selected measurement and observation sites. It plays a complementary role to direct computation of the full-scale linearized model using a comprehensive program such as MASS, after a summary of the theoretical work initiated at Hydro-Quebec in the early 1990s to promote this approach and put it into routine use, we present the main challenges in developing a production grade computer code. Detailed examples inspired by actual network studies at Hydro-Quebec are discussed, the most complex of them involving the identification of a 125th order MIMO model with 26 inputs and 26 outputs.
机译:本文介绍了用于大型电力系统的模态分析和控制的降阶小信号识别方法。基于对使用常规时域仿真软件(例如PSS / E或EMTSP)生成的低能量脉冲激励的系统范围响应,它很容易充分利用大型内置模型数据库。提议的多输入多输出(MIMO)最小实现自然揭示了特定于给定设备的主导模式,以及与所选测量和观测站点有关的传递函数。在总结了1990年代初期魁北克水电局为促进这种方法并将其投入日常使用而开展的理论工作总结之后,它起着补充作用,使用诸如MASS之类的综合程序直接计算全面线性模型我们提出了开发生产级计算机代码的主要挑战。讨论了受魁北克水电局实际网络研究启发的详细示例,其中最复杂的示例包括识别具有26个输入和26个输出的125阶MIMO模型。

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