带有内部发电机的工业厂房的参数识别

Chin-Chu Tsai, Weijen Lee, Shun-Hsien Huang, John Adams
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引用次数: 1

摘要

本文提出了一种利用相量测量单元(PMU)数据解决工业热电联产装置发电机参数辨识问题的新方法。首先,提出了一种无缝混合动态方法,并在商用软件中实现,以实现PMU边界总线外的外部系统等效。然后,采用轨迹灵敏度对关键参数进行筛选。最后,采用高维优化算法——同步摄动随机逼近(SPSA)来计算一组模型参数,以提供测量和模拟响应之间的最佳拟合。该方法是基于ISO的观点,即只有PMU测量数据是已知的,模型是不可改变的,系统在干扰时的状态是不确定的。通过对新安装发电机组的数据处理,验证了该方法的有效性和可行性。实验结果表明,该方法具有较好的参数识别精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Parameter identification for an industrial plant with in-house generators
This paper proposes a new identification process for solving generator parameter identification problem for industrial plants with co-generation facilities by using data from Phasor Measurement Unit (PMU). First of all, a seamless hybrid dynamic method is proposed to implement in commercially available software to realize the equivalent of an external-system outside the buses of PMU boundary. Then, the trajectory sensitivity is adopted to screen out the key parameters. Finally, a high dimension optimization algorithm, Simultaneous Perturbation Stochastic Approximation (SPSA) is used to compute a set of model parameters that provide a best fit between measurements and simulation response. This approach is based on ISO's view that only PMU measurement data is known, models are unchangeable and condition of system during disturbance is uncertain. The effectiveness and feasibility of the proposed process were demonstrated by processing data from newly installed generator unit in ERCOT system. The experiment showed encouraging results, verifying that the proposed approach was capable of identify parameters with better accuracy.
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