利用所有SCADA和PMU测量的智能电网应用多区域状态估计

A. Sharma, S. Srivastava, S. Chakrabarti
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引用次数: 9

摘要

本文提出了一种利用监控与数据采集系统(SCADA)的远程终端单元(rtu)和广域监控系统(WAMS)的相量测量单元(pmu)接收到的所有现场测量数据的多区域状态估计(MASE)方法。在这种方法下,电力系统被划分为重叠的子区域。每个子区域独立并行地运行自己的状态估计(SE),使整个电力系统的状态估计在下一个测量集到达之前完成。在两个连续rtu测量集之间的时间间隔内,利用pmu测量值以及使用状态预测技术进行时间调整的子区域SE结果来运行线性SE,以提供状态估计的快速更新。在IEEE30总线系统和246总线精简的北方区域电网印度系统上验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi Area State Estimation for smart grid application utilizing all SCADA and PMU measurements
This paper proposes a new Multi Area State Estimation (MASE) approach which utilizes all the field measurements received from the Remote Terminal Units (RTUs) of the Supervisory Control and Data Acquisition (SCADA) system and the Phasor Measurement Units (PMUs) of the Wide Area Monitoring System (WAMS). Under this approach, a power system is divided into overlapping sub-areas. Each sub-area runs its own State Estimation (SE) independently and in parallel in such a way that the MASE of the complete power system completes before the arrival of the next measurement set. During the time gap between two successive RTUs measurement sets, the PMUs measurements along with the SE results of the sub-areas, time adjusted using state forecasting technique, are utilized to run the linear SE to provide fast update of the state estimates. The effectiveness of the proposed method has been demonstrated on IEEE30 bus system and 246-Bus reduced Northern Regional Power Grid (NRPG) Indian system.
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