Practical Considerations in the Design of Distribution State Estimation Techniques

Moosa Moghimi Haji, Omid Ardakanian
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引用次数: 2

Abstract

Distribution state estimation is crucial for planning and operation of active distribution networks. This paper extends two state-of-the-art state estimation techniques, namely Weighted Least Squares (WLS) and Ensemble Kalman Filter (EnKF), to unbalanced three-phase distribution networks. These networks are assumed to be equipped with smart meters and distribution- level phasor measurement units (D-PMUs), which are capable of measuring voltage and current phasors. We evaluate the two state estimation methods through extensive simulations in realistic settings where the secondary (low voltage) distribution system is accurately modelled, D-PMUs are installed only at a small number of buses in the primary system, and their measurements are noisy and become available for state estimation after a certain delay. Our results indicate that both methods achieve a sufficiently low error despite the small number of installed D-PMUs, and while EnKF outperforms WLS in some scenarios, the difference between the results gets smaller with more accurate D-PMU measurements. When both voltage and current phasor measurements are available, WLS yields more accurate results under realistic assumptions and is therefore more suitable for real-world applications.
分布状态估计技术设计中的实际考虑
配电状态估计对有功配电网的规划和运行至关重要。本文将加权最小二乘(WLS)和集成卡尔曼滤波(EnKF)这两种最先进的状态估计技术扩展到不平衡三相配电网中。这些电网假定配备了智能电表和配电级相量测量单元(d - pmu),能够测量电压和电流相量。我们在二次(低压)配电系统精确建模,d - pmu仅安装在一次系统的少数母线上,并且它们的测量值是有噪声的,并且在一定延迟后可用于状态估计的实际设置中,通过广泛的仿真来评估这两种状态估计方法。我们的研究结果表明,尽管安装的D-PMU数量很少,但两种方法的误差都足够低,虽然EnKF在某些情况下优于WLS,但随着D-PMU测量的准确性提高,结果之间的差异会变小。当电压和电流相量测量都可用时,WLS在现实假设下产生更准确的结果,因此更适合实际应用。
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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