Turbine–Generating Unit Model Automatic Verification Tool Design Based On PMU Data

Y. Tepikin, F. N. Gaidamakin, E. Satsuk, D. M. Dubinin
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引用次数: 3

Abstract

Quality control of mathematical simulation models of power system equipment is carried out by their verification. We assume verification is the process of mathematical model correctness estimation through comparison of the reference (measured) and the model response (simulated) signals with their current operating mode. The quality of power system equipment’s models affects the calculation tasks performance accuracy when determining appropriate modes and ensuring power systems reliable operation, upgrades monitoring and control efficiency in normal and abnormal modes, and also allows to find diagnostic solution to electrical equipment operational status in real time. Nowadays, power system equipment models are developed based on documents received from electric power facilities holders. The traditional approach is models’ parameters actualization by means of corresponding tests for it [2],[7]. It is quite an intensive and expensive procedure, therefore it is a rare case. In addition, it has a disadvantage related to the human factor. For this reason, the agenda is the "on-line" methods development based on PMU data [9],[10]. It is important to note that sometimes there is a need to update the model structure itself, which may have a generalized form and, thereby cause a significant error. These factors should be considered as stimuli to design the automatic verification tool for turbine-generating unit mathematical model based on PMU data. This calls for:
基于PMU数据的汽轮发电机组模型自动验证工具设计
通过对电力系统设备数学仿真模型的验证,实现对数学仿真模型的质量控制。我们假设验证是通过参考(测量)信号和模型响应(模拟)信号与其当前工作模式的比较来估计数学模型正确性的过程。电力系统设备模型的好坏,影响着确定合适模式、保证电力系统可靠运行的计算任务性能的准确性,提升了正常和异常模式下的监控效率,也可以实时找到电力设备运行状态的诊断解决方案。目前,电力系统设备模型是根据从电力设施所有者那里收到的文件制定的。传统的方法是通过对模型进行相应的测试来实现模型参数[2],[7]。这是一个相当密集和昂贵的程序,因此这是一个罕见的情况。此外,它还有一个与人为因素有关的缺点。因此,议程是基于PMU数据的“在线”方法开发[9],[10]。重要的是要注意,有时需要更新模型结构本身,它可能具有一般化的形式,从而导致重大错误。在设计基于PMU数据的汽轮发电机组数学模型自动验证工具时,应考虑这些因素作为激励因素。这需要:
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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