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Power System Real-Time Monitoring by Using PMU-Based Robust State Estimation Method

机译:基于pmU的鲁棒状态估计方法在电力系统实时监测中的应用

摘要

Accurate real-time states provided by the state estimator are critical for power system reliable operation and control. This paper proposes a novel phasor measurement unit (PMU)-based robust state estimation method (PRSEM) to real-time monitor a power system under different operation conditions. To be specific, an adaptive weight assignment function to dynamically adjust the measurement weight based on the distance of big unwanted disturbances from the PMU measurements is proposed to increase algorithm robustness. Furthermore, a statistical test-based interpolation matrix H updating judgment strategy is proposed. The processed and resynced PMU information are used as priori information and incorporated to the modified weighted least square estimation to address the measurements imperfect synchronization between supervisory control and data acquisition and PMU measurements. Finally, the innovation analysis-based bad data (BD) detection method, which can handle the smearing effect and critical measurement errors, is presented. We evaluate PRSEM by using IEEE benchmark test systems and a realistic utility system. The numerical results indicate that, in short computation time, PRSEM can effectively track the system real-time states with good robustness and can address several kinds of BD.
机译:状态估计器提供的准确实时状态对于电力系统可靠的运行和控制至关重要。本文提出了一种基于相量测量单元(PMU)的鲁棒状态估计方法(PRSEM),用于在不同工况下实时监控电力系统。具体而言,提出了一种自适应权重分配函数,该函数可根据来自PMU测量的较大无用干扰的距离动态调整测量权重,以提高算法的鲁棒性。此外,提出了一种基于统计检验的插值矩阵H更新判断策略。经处理和重新同步的PMU信息用作先验信息,并结合到修改后的加权最小二乘估计中,以解决监控和数据采集与PMU测量之间的不完美同步。最后,提出了一种基于创新分析的不良数据(BD)检测方法,该方法可以处理拖尾效应和严重的测量误差。我们通过使用IEEE基准测试系统和实际的实用程序系统来评估PRSEM。数值结果表明,PRSEM可以在较短的计算时间内有效地跟踪系统的实时状态,具有良好的鲁棒性,并且可以处理多种BD。

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